Advertisers and brands are hungry to capitalize on AI. But attempts to market and adopt the technology have grown so omnipresent that it seems the industry has skipped past gaining a solid understanding of what AI actually is.

Alex Castrounis is the Founder and CEO of Why of AI, an AI consultancy that educates and advises businesses on investing in AI in impactful ways. In this episode, he lays out the foundational knowledge marketers need to effectively harness this much hyped emerging technology.

Episode Transcript

Noor Naseer: Artificial intelligence has been a buzzword for a minute now and it will continue to be one across 2024 and beyond. The speed with which people have been talking about it, you might think you'd be well versed at this point. The reality is most people aren't and probably could use a solid primer to understand what it is from an unbiased source. And who better to discuss the topic than a real subject matter expert. Our guest today is Alex Castrounis. He's the best-selling author of a book on Artificial intelligence called “AI for People and Business - a framework for better human experiences in business success”. He's also a professor at Northwestern University's Kellogg McCormick MBAI program that is focused on innovation. He runs a consultancy and organization called Why of AI which consults clients and businesses on all things artificial intelligence and how they can leverage it in the smartest ways possible. Alex shares a ton of information on what AI is and its implications, purposes, and use cases are for ad tech and beyond. This episode with Alex to get the 101 on AI starts right now.  

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Alex thanks for joining me today. I know you're a busy guy. There's a lot of stuff happening in the artificial intelligence space, so the time is much appreciated. 

Alex Castrounis: Of course, yeah thanks for having me today.  

NN: AI has been around for a long time but this new revolution or renaissance around it has really just started. What has really changed about AI now compared to the AI that's been around for the last several years?  

AC: Yeah, I mean so as you said AI has been around a long time. In fact the term AI was coined in 1956. And even then, the origin of the idea of artificial intelligence included things, concepts and potential techniques like neural networks and things that we see today that are very much associated with artificial intelligence. So, indeed it's not new. Although AI as a field has gone through different kinds of periods of lots of investment, lots of innovation, lots of progress, followed by what they call “AI Winters” where things slow down a bit then pick up again and so on. At one point in time, we started to have a lot more data available, and the advent of the world wide web, and just the ability to transfer and move data around in much greater quantities and store more data. And more computing power and so on sort of led to this sort of growth of AI and ML capabilities.

And a lot of what was going on was really around things like forecasting or predictive analytics whether it's trying to predict numbers or sort automatically classify things. And then fromthere, other techniques started to gain traction and get more advanced as well like computer vision and natural language processing and so on. I think what led to this moment was really when certain kinds of what I would call “architecture” it's what most people refer to is kind of neural networks or deep learning architectures, started to be developed by researchers, like “The Transformer”. I'm not sure if you're familiar with that at all. But the Transformer sort of model and architecture that underlies models like large language models that we hear about today that power ChatGPT and GPT4, and now Claude and llama and Bard with Google and Palm; and the list just now goes on and on. It really is where this transition really happened in terms of capabilities from a generative perspective with language, as well as these models being able to do things people didn't explicitly train them to do. So, in other words, they could do different tasks almost on the fly and become very specialized or what they call ‘conditioned’ based on the intent that you have for them. So, just by introducing this idea of ‘prompts’ you could take a model and take the base model, and then condition it or specialize it in a certain way using certain kinds of examples. But also, you could ask it to do tasks that it was never explicitly trained on. And it turned out that these models are actually much more versatile and generalizable than people originally sort of expected them to be.    

Once that became better understood a lot of that came out of the research. In fact, papers like “Attention is All You Need”, the original Open AI GPT2 paper and the Open AI GPT3 paper where some of these concepts were really brought to the forefront are why we're at this point right now where you know exponential increase worldwide in terms of global AI awareness interests. And quite honestly people are sort of scrambling to figure out, “What is this stuff? How do we understand it? How do we demystify it? How do we use it?” I think it is largely because of the Open AI ChatGPT for example. And when they launched GPT 3 and some things like that started to add kind of a usability characteristic to this stuff, sort of a UX, UI if you will like a user interface that's easy to understand and use.  

With GPT3, it was a little more complex because the interface still required you to tune certain parameters and things like that that maybe the majority of people wouldn't be as familiar with. But I think with ChatGPT that launch sort of brought the honestly quite remarkable capabilities of these large language models to the public in an interface that's super easy to use quickly, super easy to understand and see results right away. It doesn't require any sort of tuning or configuration on the user's part. And I think just that helps really helps people sort of the light bulb go off and go, “Oh wow this is pretty remarkable stuff”. And now the potential applications and use cases are a little bit clearer; at least in the generative and large language model sense.  

NN: So, there's folks like you Alex who are in the bucket of people with deep subject matter expertise around artificial intelligence. Or even something tangential like they work in the predictive analytics space. They're knowledgeable about what neural networks are or they're just deeply researched and they're educating themselves. And then there's folks on the other side of the spectrum where there's curiosity and that might be the greatest extent to which I've tried Chat GPT. So, a lot of folks maybe want to be moving away from being all the way on one side and moving a little bit closer. They're not going to become subject matter experts, but they want to know more about the medium. How should people educate themselves? What recommendations would you make to folks besides just reading the next AI article that pops up in your newsfeed?

AC:  It's a great question because it does really depend largely on sort of what your goals are in terms of the understanding. On the one hand there's the practitioners. There's the data scientists, the data engineers, the machine learning engineers, the AI researchers and so on. In which case if that's of interest or doing any of the coding or understanding sort of these learning algorithms models and technical detail that go into these things, if that's something that someone's interested in then the path to learning is very different, than let's say you're a decision maker or business leader or entrepreneur or whatever the case may be. In which case for me in my company Why of AI actually focuses much more on that education piece with that type of audience. The more business folks' entrepreneurs, innovators, basically non-practitioners and not necessarily technical folks that still need to understand AI machine learning to some degree- sort of what I would refer to as the appropriate level for what they need to understand.  

One of the challenges with it is that AI and ML are huge fields. Even though right now a lot of people have like what I would call horse blinders on, in terms of this very focused view of AI as like generative AI or large language models or Chat GPT but there's still like a very large field of AI which is like other aspects of natural language processing, computer vision, unsupervised techniques like clustering and segmentation that are often used in marketing and advertising, and so on. There's forecasting, there's classification. There's personalization, recommender systems and sort of the list kind of goes on and on.  

So, it does depend on what it is but ultimately the key thing is that the way I help people understand it especially in the business sense, is ultimately it has to line up to some goals that you have either for your business. Or for a certain department within your business-like sales, operations, marketing, HR whatever it is. Or maybe you're looking at how to solve certain problems for your specific products or services or for your customers or users. So, there's going to be goals associated with those different areas, goals, needs, gaps or challenges. So, the question then becomes which sort of areas, and which specific types of tasks can you accomplish using artificial intelligence/machine learning depending on what those needs have been. And usually, it comes down to less about the really technical details of the models, or the algorithms or the tools or whatever and more about what are you trying to do exactly. Are you trying to predict something? Are you trying to augment something? Are you trying to answer certain questions based on some data you have? Are you trying to extract information in a certain way? Are you trying to categorize things in a certain way or recognize or detect things in images or things like that? So, I think part of it is learning more about how AI and machine learning help you functionally solve these problems. And what do those real-world use cases and applications look like for your business products, services, departments, whatever.  

So yeah, it depends on what you're trying to learn and what you're trying to keep up to date with. But the bare minimum, I think everyone should have some degree of understanding at this point of generally what artificial intelligence kind of means, what does machine learning mean and what are some of those different areas and how might they be used to accomplish certain goal-driven or goal-aligned tasks and results.  

NN: If an organization has come to the conclusion that you suggested, which is that their first responsibility is to figure out what their business objectives are that could leverage the upside of AI. Tell me the more granular details. How are organizations doing that before they're turning to you or other subject matter experts in AI space? Are they doing an audit across departments? I'll use an example specific to the advertising space where a lot of people work in sales. And a lot of people if they work at agencies there's a pitch and sales side of things. And then there's also the workflow piece, the processes piece, and you talked about operations where I think efficiencies are deeply desired. How do you help people help you if that makes sense when they're trying to share their business objectives? Because I think if you started asking everybody in your company, people could come up with an endless list of challenges they're trying to solve for.

AC: Well that's exactly it that's spot on. I mean, at this point you being an organization can benefit from AI and machine learning especially now with the generative stuff that's really accelerated some of this. How you can see results and value pretty quickly depending on what you're trying to do across the organization. You can help your organization at large you can help with every single business function you have. You can help implement and incorporate AI into product features that you have or your processes or customer experience. I mean, you just name it. So, you're right in that the options are sort of endless.  

I think what it comes down to is trying to really figure out where the biggest needs are at the moment, where the biggest gaps, challenges, needs, goals, objectives. Like what are the most important things? A big part of it is sort of a bit of a prioritization exercise.  In terms of that and filtering down a little bit and trying to narrow things down.

Going back to your first question though. In terms of what I see out there with companies and how they're approaching it, it's all over the place, quite honestly. In many ways it comes down to what I often refer to as “AI readiness” and “AI maturity”. There's a spectrum, there's a scale. There's everything from companies that have not done anything with artificial intelligence and machine learning, that just want to know more about and start to get their feet wet and get going. Then there's companies sort of in between—they prototyped some things, they've done some things but not necessarily gotten AI solutions into production and commercialized or at scale in any appreciable way. Then there's organizations that have a kind of a mature and experienced and sophisticated AI or machine learning team. But often what I see even in really big companies is they tend to be very narrowly focused in certain areas of AI machine learning based on sort of their core company offerings, let's say. So, they're sort of experts in specific things around what the core companies like products or services do. And so, they've developed these very sophisticated models and ways to maintain them and manage them, and improve them and monitor the results of them and so on. But they're in sort of a similar boat whereas AI advances literally at this point on a day-to-day week- to week basis and they're hearing about generative AI and large language models and all that. They're not necessarily either already doing stuff with it or have resources that have that kind of bandwidth to just tackle those problems either. And so, sometimes organizations get around that sort of thing by setting up centers of excellence or emerging technology innovation centers, things like that. But generally, yeah, it's all over the place. So, it really depends on the organization how much they've been doing with AI/ML, if at all. And do they only specialize in certain areas and still have a lot of opportunities to branch out and sort of figure out how to do more with it?  

NN: My guess is that for people who are in the AdTech and advertising space or the agency space, they’re less likely to be in the position where they've got in-house data scientists or people who are managing learning models that they're building out that are custom and to themselves. And it's more likely that they're going to leverage those tools. So, there's so many tools that have popped out of the woodwork in the last couple of months. So, I think a lot of people what they're doing is assessing those tools. So, you've mentioned a couple of times Chat GPT which is very visible. Google’s Bard as well, and I think a handful of other free tools. But I also wonder if there's some charlatans out there just selling snake oil. They're trying to jump on a hot new trend and get in with folks that don't have deep subject matter expertise. Have you seen anything like that out there Alex, like things that people should be wary of in the AI space? Or maybe it's not even their intention to offer something that is so lacking in legitimacy but it's just not as fruitful as what maybe people are looking to gain by looking at AI tools? 

AC: Yeah. Absolutely. And I don't think that's new right, like if you think back even quite a while ago there became a trend of everyone saying on their website their product was powered by AI in some way. You saw that a lot actually in things like advertising or marketing tools and platforms and whatever. And often they're not necessarily powered by AI. So, in that case I mean it could be a little hard to assess because companies aren't always 100% transparent. And nor should they be necessarily because that's kind of their bread-and-butter, secret sauce, confidential sort of proprietary information. If you're sort of like, “Hey, what exact algorithms or models are using or this or that?” So, sometimes it could be a little tricky to determine.

I will say that there are a lot of—to your point, I think one of the trends we started to see even before sort of this explosion of AI and machine learning interest was around no-code low-code. So there was a big movement to make coding more accessible to companies so that they could set up a website quicker like with Squarespace or Wix or something like that without necessarily having this programmer in house. Because to your point a lot of companies didn't necessarily have a software development team either and with that requires you know UX UI designers, QA folks, product managers and this big list. So, whenever you can kind of abstract away some of those like technical complexities and make these technologies a bit more accessible to others to use, that tends to be very attractive particularly for organizations that don't have that sort of expertise or core competency if you will in-house. I think we're seeing the same movement now with AI tools as well. So, we're seeing these platforms whether they’re cloud-based platforms that sort of can help manage the end-to-end process of AI and machine learning development and deployment of models and so on. Also, APIs that you can use on demand sort of like Open AI API and some of the other ones we're seeing like Claude and Anthropic and some other ones sort of making these tools accessible via API calls where you don't have to necessarily roll this all out yourself.  

Hugging Face is a great example as well. I don’t know if you're familiar with Hugging Face. But there's also the open- source movement and that's been around for quite some time. One of the organizations that's really big in the AI space right now is called Hugging Face and they've basically created this very capable and sort of comprehensive open-source Python-based library that wraps these Transformer models. So that organizations don't have to like sort of train or build these models from scratch, but they can benefit from this and use them in a much sort of simpler way within their own sort of tools.  

You're right in terms of, especially with generative AI, there's new companies coming out nonstop right they're saying they're doing generative AI stuff or natural language stuff. And then the question really becomes like are they really differentiated in any particular way or are they just a wrapper around something like Open AI's API. Because anyone could do that. Anyone can sort of just build a front end, connect it to Open AI's API and then collect some language somehow from a user whether they speak to the app or platform or they type something in. Send it off to the Open AI API, get the results back and then just show it to the user. In that case if that's all it is it's a wrapper more or less but if they're doing other things like maybe they're fine-tuning models or they're doing specific kind of sophisticated prompt engineering behind the scenes, or they're connecting not only to those kinds of APIs but also to some sort of database to like not just have all the outputs that you're returning to the user be generated purely by these large language models through their parameters; which is kind of like a statistical thing where the output is purely based on the parameters of the model. And what's the most probable output for the prompt you gave it. But rather either combining or shifting between outputs that come from real data that's relevant to that particular application, versus outputs that come purely from the model statistically generating the most likely probable output for whatever it received through the user interface or conversational interface. So, it's a bit Wild West out there, to summarize.  

NN: You use the words that I was searching for that there are some existing accessible and sometimes free tools like Chat GPT and anything else in that category that's now been popularized. And another organization has put a wrapper on it customized or repositioned it a little bit. And now they're putting that out there for some companies that might be worthwhile. Something else you had mentioned earlier on that people have concern about or they raise an eyebrow to is when people do not distinguish between what is machine learning versus what is AI. And I think we touched on this a little bit. It's been talked a lot about in the trades that some organizations are going out of their way to distinguish between one versus the other. How do you really describe the difference between them at a time when so many folks are just jumping on the bandwagon to associate themselves with artificial intelligence? 

AC: Yeah, I mean the way I've always sort of defined these things and explained these concepts is with artificial intelligence I sort of always go back to the sort of how you would define intelligence in general. If you look up the definition of intelligence for humans for example like human intelligence or animal type intelligence, it always boils down to something along the lines of you learn you understand things, and then you use that understanding to carry out tasks or accomplish goals and things like that. So, when we're babies were born with sort of a blank slate and then we learn from our parents, our school, our friends. As kids we do a lot of trial and error and experimenting. We just keep learning. We develop more and more knowledge that our brain sort of remembers and encodes if you will. That becomes accessible to us and it also gives us what we call common sense, which is really that we over time buy a world model that we just have operating in the background all the time, even if we don't think about it. All of that allows us to do things like have conversations so getting back to that thing of doing something with that learning and understanding. So, we can have conversations, we can get to work every day and get home. We can do the tasks we need to do as part of our job. We can assist clients in a consulting fashion if that's what we do and so on and so forth.  

Machine learning though is the learning part of that bigger picture equation. So that's intelligence as we think of humans and animals, that sort of thing. Artificial intelligence is literally just a natural extension of that by saying intelligence exhibited by machines. So, if you could get machines to also learn then understand and be able to carry out tasks like predict a stock price. Predict whether an email is spam. Make recommendations of songs you might be interested in listening to. Determine whether a skin lesion is cancerous or not. Figure out what's the best price or promotion for a given sort of target market for a given product as well. That's artificial intelligence. And the learning part of that for the machines, when it's machines that are exhibiting intelligence, comes from machine learning. So, really all machine learning is is certain algorithms, what they call “learning algorithms” that as long as you have data and usually that data is somewhat domain specific or industry specific or maybe it's functionally specific like in the case of sales or marketing. Or domain in the sense of advertising or insurance or financial services. Then these learning algorithms that fall under the machine learning umbrella can kind of automatically learn the underlying correlations, relationships patterns and so on that's encoded into that data, such that you can use it in an AI solution to do those tests.  

So, machine learning in and of itself is the learning part and the outcome of the learning part from those learning algorithms is usually a model. That model is then that understanding part. Like we said with AI or intelligence in general there's learning then there's understanding and then there's doing and carrying out tasks. These learning algorithms do the learning the understanding, and machine learning comes in the form of models. So, in the case of ChatGPT and GPT4 I use those as examples regularly just because people are now very familiar with them. Those are large language models that have already been pre-trained, and they've been made available via their API or their user interface. But those are just a bunch of model parameters. In the case of GPT4, it's like a trillion model parameters or something like that that was learned during that learning process. That model once you have it represents that sort of understanding of human language.  

Then what you do with it is what makes it AI. If you don't do anything with it, if all you do is learn, use learning algorithms to learn from data and create a trained model and the model just sits there on the shelf or does nothing, then that's not AI. It has to then predict something or classify something or automate something or help someone carry out certain tasks at their job every day or whatever the case may be.  

NN: Yeah, I think what I've seen a lot in the adtech space is that people have just a bandwagon to say, “we've always had AI”. And on some level, it's much more machine learning optimization than it is in fact artificial intelligence. There's also the intent to do dynamic customization or the dynamic delivery of ads. I don't have enough subject matter expertise to say how much they lean towards AI versus machine learning but I'm just harboring a guess that it's much more machine learning at this time than it is in fact artificial intelligence.  

Another question I have for you is just about not embracing AI. I think there have been some things in the past, in the recent past where businesses, marketers, advertisers. People from any other walk of life and business they've raised an eye and said, “You know this emerging technology, it's a trend, it's a fad it's not really going to become a part of our day-to-day”. Have you seen any of that skepticism showing up for companies where they're not taking it seriously? And if they're not taking it seriously do you have fears for companies that are refusing to put time and energy into understanding how they can adopt AI? 

AC: I love that question because yeah totally in the past I saw that a lot more where people like—you know it's funny ‘cause there's a lot of people like myself that have actually been working in this field for quite some time and we're sort of saying, “Hey there's this AI thing and machine learning thing and it can do these things that could be beneficial.” A lot of companies weren't taking it very seriously, or they just didn't understand it or they didn't get like what are those real world applications and use cases or whatever the case may be. So, there was more of that. And there was hesitation around it in general just sort of like “Oh, AI”.  

Then again, I think now the opposite happened because of the arrival of ChatGPT in these models but also genuinely the capabilities of these models like it really has advanced it's not just hype. These models do kind of remarkable things and if you understand sort of how they work under the hood and how they get to the point of being able to do these things. Not just with language but also with things like Dall-E where you can type text and it generates an image. It's pretty remarkable how we've gotten to this point and it's not stopping there. It's continuing to go. So, all of that combined sophistication has gotten a lot better. The advancements are a lot better and more capable; the interest awareness buzz is so much greater. It's less now of people like “Yeah, I don't know about if we need this AI thing”. It's more like scrambling everywhere. It seems like more and more everywhere I turn or people I talk to or organizations I talk to or hear about they're more scrambling now. They're very much worried about missing the boat on this thing or getting behind or somehow losing advantage or something like that.  

The two biggest questions I get today hands down are build versus buy. Sort of everybody wants to know should they build or buy solutions now in AI and then secondly is should we wait to build. So, it's not so much we don't think we need it or we're worried about going down that path or anything. It's more we're scrambling. We need it. We have horse blinders on and to us now AI just is synonymous with large language models and Chat GPT. And in some ways almost ignoring the rest of this, like a much bigger landscape that falls under the AI umbrella. But a concern now is more how do we invest time, effort and money in building solutions when all we're hearing is the stuff is advancing so quickly. And if we go and build on something and then it's out of date or deprecated or obsolete three weeks from now or two months from now or six months from now, have we sort of created problems for ourselves? 

NN: Yeah, the build or buy piece like that sounds exactly right and it's less of people saying “We're totally going to ignore this thing”. Because the way I'm seeing AI today it's kind of like saying you're going to ignore the internet and that it's not going to be a part of your business. It just doesn't make sense. It's baked into our expected vision for the future. Knowing whether or not you're spinning your wheels and wasting your time doing something that you don't need to be doing because there's something available for you and you could be wasting time and resources. Or acquiring resources that could otherwise be better spent doing other things that are necessary for your business. So, I imagine that's something that you're giving a lot of advice on, and that people are trying to get recommendations or referrals for what they can do at this moment in time. Is that fair? 

AC: Absolutely. It's completely fair. And you're right it is like the internet. I think that's a great analogy. The other thing is whether we like it or not or want it or not. Everyone is interacting with AI today now all the time- with all sorts of different tools that they use and software that they use. Even the people that are being served the ads. In the case of digital advertising there's AI algorithms behind the scenes there. When you're setting up campaigns there's AI algorithms sort of optimizing where those ads show up and so on, and when and all this sort of thing. So, it's just baked into so much at this point too. I don't think it really benefits anyone to ignore it.  

I think the bigger thing isn't so much whether you ignore AI or choose not to use it or something like that. But rather just making sure that you're using it responsibly, fairly, safely in a trustworthy way. So, I think the bigger thing is really just at the same time you're trying to figure out what is this AI/ML stuff and how do we use it for our business to benefit either our business, our customers, our users and so on. It's also how we do that in a very safe and sort of fair and responsible way. And, we create trustworthy solutions that we're confident in and that we trust.  

NN: I'll have to say any follow-up questions about potential concerns are at AI for another time. But just in the last few minutes that we have together, I do want to ask this question. For organizations that are small, that don't have dev teams available that want to make sure that they're staying on top of what they can like you mentioned people are developing Centers of Excellence or task force things of that nature. What should people do today when they are let's say less equipped and they don't have as many resources at their avail? What should those smaller teams be doing to stay on top of AI as best as they can? 

AC: I mean so shameless plug here so my company Why of AI, certainly helps at least on the education piece and the strategy consulting piece. We don't build AI/ML solutions, we work with partners that do. But I think one of it is if you want to start learning through a workshop type of thing whether it's us or someone else. There's that kind of things like getting help in terms of workshops or some sort of courses for small teams that sort of thing to understand AI and ML at the right level- again not super technical depending on whether you're a practitioner or not. But in terms of keeping up I have to say it's really hard. This is something I spend a tremendous amount of time on and it's not a trivial task uh to keep up with AI and machine learning today. So, I think the question is really more what aspects you are trying to keep up with. If you're not so focused on necessarily all the super technical details or the latest and greatest models or this or that. But you are in like advertising or digital marketing or you're in financial services or health care or whatever. I would really recommend at the minimum gaining enough sort of high-level understanding at least of the general concepts of AI and machine learning. Not the super technical stuff. Not the really in the weeds jargon. But like a high enough understanding that you can read some of the articles that come out or the news you're seeing in a specific industry that's relevant to you. And you can understand it.  

The other day I saw this really amazing thing where they're using sound to listen in the oceans for fish activity around coral reefs as a measure of whether the coral reef is healthy or not or dying or has died. And use that information to then take actions to sort of help maintain healthier coral reefs. Things like that. You don't necessarily need to know all the technical models and algorithms that are powering this solution. But you start to get a feeling of like, “Oh I get how you can use audio in certain ways. You can use images and video in certain ways. You can use text in certain ways. You can use structured data that might, maybe you have in spreadsheets or tables or a relational database like your CRM or your sales data in certain ways and so on”.

So, I think the biggest thing is if you're not a technical person or a practitioner is really just understanding what this stuff is at the right level. And how is it being used in real world use cases and applications and so on that are creating actual positive impacts and benefits and outcomes that are relevant to you. That would be a good starting place because otherwise the whole thing is just too massive. 

NN: It's great framing and perspective. I'll leave it here Alex. I know you have to run to another meeting. AI calls. Duty calls for artificial intelligence. So, this is just a kickoff point for us on this topic. There's much more to learn for everyone. So, maybe we'll touch base with you later on in future episodes.  

AC: Well, I can't thank you enough for having me join the show today. And thank you so much. Best of luck and I hope to talk again soon.  

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NN: That's it for this episode. Thanks to Alex Castrounis, Founder and CEO of Why of AI for all his insight. I'll just say I did not want to get a primer from anyone in adtech who might spin it to speak to a product or a product pitch or a product release at this time. It's a little bit questionable how AI-centric some of those releases are and I think this is a topic that has so many implications and is going to impact this industry for years to come and so many others. So, a lot more to be seen. We'll be touching on AI again and again. So, expect to hear it brought up in multiple episodes in the future. Until next time, more Adtech Unfiltered real soon.  

Advertisers have had a lot on their plates in recent years, as they’ve navigated the lasting impacts of the COVID-19 pandemic, economic uncertainty, ever-increasing media complexity, the emergence of AI and, of course, third-party cookie deprecation.

Amidst these dynamics, the allure of hype can be irresistible—particularly when a new technology, product, or solution promises a shortcut to making life better for marketers. But not all “trends” are alike, and while some of these technologies and solutions are real game changers, going all-in on the current hype won’t necessarily make a lasting impact on advertisers’ core challenges.

So, how can advertising leaders distinguish between solutions that are over-hyped from those that are hyped, well, appropriately?  

Noor Naseer, Basis Technologies’ VP of Media Innovations + Technology, dug into this issue in detail in her presentation at SXSW 2024 in Austin. Check out the recording below to see all her insights and recommendations around navigating hype cycles on-demand: 

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Want to dive further into Noor’s presentation? Click here to download the slides from her talk.

Automation is a game-changer for advertisers. As Co-Founder, President, and Chief Product Officer of Fluency, Eric Mayhew has made it his mission to build automation technologies that improve how people buy digital media.

In this episode, Eric joins host Noor Naseer to share how automation and AI can reduce low-value manual labor, minimize friction in workflows, and help organizations gain a competitive edge.

Episode Transcript

Noor Naseer: Automation: It's an oft-mentioned word in the advertising world that can mean a lot of different things. Understanding its potential is something more ad pros are determined to figure out especially in the last year since the popularization of AI. Eric Mayhew is the Co-Founder, President and Chief Product Officer of Fluency, an organization focused on automation solutions for digital media. He joins us to share wisdom from his 20-year plus career in digital marketing, ad tech and software engineering to highlight how automation can reduce low value manual labor, minimize friction and workflows and just help us in organizations not get bogged down by some of the needlessly laborious aspects of media buying. Let's get into this episode on automation and AI with Eric right now.

Eric, I just want to thank you for the time you've made so we can talk about another iteration of artificial intelligence and where it intersects with automation and these are things that you have a lot of passion around. So, I'm looking forward to this conversation. 

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Eric Mayhew: Absolutely. Thank you for having me today. 

NN: So, I'm going to take us a year plus back. Whenever the new renaissance of artificial intelligence really started, maybe you could say it was the end of 2022, early ‘23. I want to get everybody on the same page. How did we really start embracing artificial intelligence? If you can take us back there so we can kick off this conversation on where it intersects with automation.

EM: It is absolutely amazing that it's only been about a year where this has been this pervasive. I think open AI came out in November 2022 where it was at Chat GPT3 and pretty exciting to see what's happened since then. That natural language the fact that you can interact with it in such a natural way is really profound. So, I think that's why we're really here today to talk about AI in its use case especially in advertising where we're a vehicle and a voice piece to communicate between our clients and their clients. So we're trying to talk on a human level between the two. But I don't think that's when it really got started.

AI's kind of been around for a while I've been in some panels where even I was exposed to things that I didn't realize how much longer it's been in in our society. It's just been kind of guarded from the general population and practical use cases. But as it's become more prevalent and pervasive, because of those new innovations there's a scramble to find the great use case and get the efficacy from that that we think that and the promise that's there. 

So, if we take a year ago - I spent a lot of time in the Meta environment, spent a lot of time in Google and Microsoft and in the programmatic space. Take those first couple that I talked about with Google and and Meta and they've been in the space of trying to do AI type of content management and prediction capability for quite a while.

Google went to Smart Bidding a couple years ago. So Smart Bidding was kind of Google's first space into prediction of all these attributes about users and their proclivity to take an action. One of the bidding strategies that they have is maximize conversions or maximize conversion value. Those two things are all in the propensity for someone to actually submit a lead and it doesn't really tie as close as it once did to keywords. 

Now if we even rewind farther back, Google's broad match just as a concept, that is an AI type function. Here's a phrase somebody typed in, that phrase isn't exactly what you're bidding on as a keyword. But that keyword is for the same intention. So there's always been this interpretation. There's been this growing path through the ecosystem to get us to the spot where we can say that AI takes a simple concept a simple implementation and expands it out into something very tailored and curated and ready for the general public.

So, I think we've seen this journey over the last year. And in the last year with Chat GPT we've seen that we can actually automate something that's been elusive for a long time. And that elusivity has been around the creative side, talking to customers in a natural language in the way that they'd want to be spoken to. When you're going to generate creativity and you want it to resonate with a person it cannot look robotic. And the new LLMs and the new Large Language Models make that feel supernatural. 

NN: You jumped into also very specifically the advertising applications and considerations that have taken place across this last year so going further into that and just very much asking that question thinking more broadly about programmatic advertising and how we've seen AI show up in those spaces. Do you have any additional commentary on what that connectivity has looked like and how people who are media buyers or planners have already had a lot of just general exposure?

EM: You're right – it has had a much larger societal impact than just in the advertising space. Over the last bunch of years, we'll say even rewind seven or eight years ago in programmatic buying, real-time bidders have always been in the machine learning space trying to predict proclivity to interact. So, if you want to try to maximize your click-through rates (programmatic buying) that's usually done through some sort of machine learning algorithm that has been accumulating signals from users over time. Pretty amazing space.

We've had conversations around Google Smart Bidding. We're seeing it now in Google's responsive search ads and their responsive display ads where they go ahead and restitch assets together in compelling ways, and then measure the response for different user segments. That's all been done through large models through machine learning and through what they're doing with their algorithms. 

Meta is in this space all the time. Lookalikes as an example are definitely in that space. So lookalike audiences which have been around for a while that concept is pretty pervasive in Meta and they're doing a lot of that work over there. 

What I think happened in the last year however is that this is all in kind of the last mile buying that we've seen. It's bid management, it's proclivity to buy like these low-level signal type things. What we're seeing over the last year is that you can put it more in your workflow and the workflow can be very labor intensive. We collectively as an advertising community definitely find that as digital marketing gets more and more sophisticated, the levers to pull become more and more complex. They're more sophisticated. They interact together a lot. I'm going to guess a thousand different settings in any given campaign. And if that's the case if there are all those thousand different settings, there's a reason that there are ways you can set it in position A versus B (just as a concept why people have set those up that way). And it's not always obvious what the combination of settings are to reach your goal in the most productive way. 

So, people in digital agencies, digital advertising tend to spend an awful lot of time figuring out what those pure combinations are. How do we link these audience settings together with my bid strategy? How do I get my creativity optimized properly for the space? And configuring those settings has been complex and labor intense. And I think AI is coming into play here in a great spot. It's helping people make those decisions.

Even with all that there's still a lot of labor in just the creative content and content generation to communicate a special. You've got a four-bedroom apartment and there's a move in special and all those pieces to make that sound natural and bring that to a user that's been challenging over time as well. And, again, very labor intense when you look at the wide landscape of the number of accounts that agencies typically manage that takes a lot of time and energy to just manage all that creative generation. AI has done an amazing job here simplifying that entire process, helping you understand the settings that make the most sense and helping you effectively communicate with your client base with compelling assets, compelling content and creativity. 

NN: I think probably most people picked up on that when you're saying, by settings you mean different parameters or tactics that you can leverage, different data integrations that you can make selections around. To what extent do you think that there has been a shift in since the birth of (and I'm calling it the birth of generative AI) but I mean the accessible form that you were talking about at the top of this podcast has there been any notable shift? Because so much of the focus has been on generative AI. Have we seen any differences or distinctions whether it's AI specific or automation specific that you've perceived in the last 12 months?

EM: You're talking about out in the space. Am I seeing any signals that are coming back that say that the way we operate is different? 

NN: The way that we operate with advertising or programmatic advertising in mind. 

EM: I think the answer is absolutely that there are very simple ways to do these things. You can actually have fully AI generated campaigns through settings through messaging and that can exist now. I think there's some challenges with that but it does exist. Which means if we are trying to compare agency A to agency B. The labor savings that you can gain from AI and automation is astounding if you can really lean into it now. The first thing I want to say is I'm very cautious with how we do that. That wasn't a statement to say widen your margins immediately adopt AI and I think automation is solid and we'll talk about why automation is very cool in a little bit I'm sure. But AI can do so many things but it's a little bit non-deterministic. If you can tolerate a little bit of error - if you can tolerate a tone of voice that may or may not match with your client. I would never use it for a large brand that has an established voice. But if you don't have that case and you're using a lot of just data to power your information and trying to get a message out there, you can do an awful lot with it. That just changes the way we execute. So that we can offer more complete solutions at a lower labor point which means that margins can stay where they are. Businesses have to run. At the same time the end-advertiser gets a better experience, more long-tail on the advertising side and it's not paying for it on the other side, so it's prohibitive on the cost side. 

I think there's a lot that's gone on in there. You can definitely feel that the entire shift inside the Google Meta space Microsoft is leaning in extremely hard with OpenAI in that Google has an AdWords version that's fully AI driven. It gives you recommendations and walks you through the entire process. That's very difficult to use if you are trying to put together a bespoke campaign with deterministic outcomes. You're still going to get involved and you're going to make those choices but it's definitely coming and it's definitely getting better all the time. 

NN: There's been a lot of excitement around the potential of AI across this last year and we've established that. And I think that the automation component is something that I know you have a lot of energy around the words automation for whatever reason in the advertising world don't always resonate with everyone. It's not everyone's first priority. They have manpower. They have bandwidth. They have systems that are already in place. How do you think the word automation is being received today in a way differently than it was in the last couple of years?

EM: Well, I think we're in a spot where it's almost a necessity there are agencies that are doing it and doing extremely well and those agencies are able to offer a deeper service at a lower price at maybe the same or lower price point than where we've been before. So those services are now very feature complete. I think when you think about automation. First, we'll kind of define a little bit of the difference between AI and automation. AI is a natural thinker it will come up with something for you. It will feel creative whether it is or isn't it will feel creative it may feel new and it's a little non-deterministic (you don't know exactly what you're going to get out of it when you start).

Automation is effectively a rule system that is very deterministic. You should know based on whatever you put in the outcomes will be deterministic you will know what you'll get. So, for example you can do a lot of things if you had a data set of specials taking those specials and converting them into ad content it's pretty straightforward. We know what we would do as people. We can model it and if we model it we can automate it and I think that's a really important piece. So, if you are an agency and you can think about the decision trees that you go through as a person and your best practices because you're you're probably going to tell your clients exactly what your best practices are. “We do XYZ in this scenario and that's what makes us an amazing agency”. We do these things and if you can say those types of words why you make choices when you see certain data sets, then you can automate it. You can say, “When the weather changes and I'm representing an HVAC client I prioritize heating systems. When the weather gets cold.” I've actually heard people go the other direction because heating systems sell themselves when weather gets cold. So, you might want to say that our secret sauce is to reduce bids because you don't have to be as aggressive. 

So if you can articulate who you are and what your strategy is in scenarios then from that point forward you can go ahead and just set up your rule systems and let them run. I think it's had a negative connotation because we have two hemispheres really in advertising today and it's new. With digital advertising whenever anybody thinks advertising we think creative we think creative minds creative writers we think Mad Men a little bit. We think you know just splashing ideas on a wall and there is a place for that. But the digital advertiser today has a very technical job and that's new. So now you've got this one person that is expected to be both creative and technical.

So, what I see us doing with automation over the next several years is really taking that technical piece and simplifying it by putting it through the rule systems. Allowing creativity to flourish, that side of the house actually continues as is. But reduce the requirement of low-level settings knowledge on the digital advertiser, allowing them to be more on the creative side how they communicate with clients. I think AI has a great narrative on that side of the house specifically because that can be very time consuming also and as inspiration and creativity, super cool spot. For AI, I can go and ask it a question. I can get an idea, it could be my finished product, it could be just an idea spark and I love that about that side on the creative side of the house. But when it comes to the execution side that's a great spot for automation. The execution is going to take and process all that data, look at the scenarios out in the marketplace right now, bring in signals like the interest prime rate and the weather and the products that are in inventory that your account has and make decisions like you would make as a person and just stop requiring you to go and configure all these things over and over again. 

We just had a conversation. It's actually really timely. Just before we got on we were talking to a friendly partner that talked about how they do Facebook. And the cycle over month over month with campaign renews in Facebook is a many person multiple day job. And it's not a creative job. It's a workflow job and those are the places where automation just a no-brainer in my opinion. Why would you put your people through that? Even if you had the manpower it's such a tedious and painful existence it's not fun. It's a burnout machine. It's prone to error. And not because people are significantly prone to error but because it's tedious, it's mindless, it's repetitive and I would love to use a computer personally anytime that that scenario comes up. 

NN: You've given so many examples that clarify that the industry has progressed to a place where a larger slice of advertising responsibility falls into some of those that, they're not low value but sometimes the feeling is that they're mindless activities or they're less creative or they naturally shouldn't be sucking up so much manpower time. Are you finding that most agencies clients that fall into doing this type of work are making the shift and embracing automation to the extent that it's available? 

EM: It is a mental shift. The partners that I've gotten a chance to work with, when I get to work closely with them you can bring them through that process and it is a process. It's going to sound like a simple thing but if you're a software developer a “for” loop or an “if then” else statement is pretty natural it's common language. Automation works on similar concepts. I've got to loop through every one of these products. And if this scenario happens then I wanted to do this other thing and in natural speech that works but to set up automation can be daunting if you don't think like that. 

Once you have the idea of how looping works and iteration and logical blocks like that you can do a ton with it. I don't think it's as foreign as it seems. When you first hear it and if you don't communicate it in a proper way it looks really technical. It doesn't have to stay that way though. 

Expressing the concept once you get there, the savings are so wildly important. Businesses transform once they get there. If you can show them the win early. Like if you can give them a small small morsel of success, they can literally cross off labor intensive things like that thing we just talked about the Facebook campaign refresh. If you can show the value of that early in the process then the sky is the limit. 

NN: The analysis of achieving efficiencies and cost savings is a conversation that's had with a certain buyer. And it may not be just somebody who strictly and exclusively does media buying. Of course the role of what it means to be a media buyer is going to vary depending upon the organization and what their responsibilities are. But I take it back to my own experiences working in a holding company being a media buyer. I got exposed to basically publishers and publishers that were doing outreach to us and I talked to them. They had some suite of sites or portfolio of sites that I could buy from or they're representing a single solution. I wasn't the one who was responsible for understanding the economic upside. So who are you talking to about this? Because some people may fall outside of their wheelhouse who's really going to be bought into or do you need to talk to who cares about this when you're reaching out to an agency?

EM:  I mean, ultimately it's going to take executive sponsorship for us to take that leap with somebody. But I think before you even get to that point you've got to win the hearts and minds of the executor and the ad strategist. Long-term like overall we will have to also sell the economics. All software automation processes their process change, process change has cost, software has cost. Like all those things do end up having cost so you will have to get to the executive sponsor side. But we always start first in showing the person that does the job how their day will get easier. And once their day gets easier then the convince-up is a lot easier. It's basically saying you know they don't have to do that campaign refresh anymore. You can put them on more high value things. Have them talk with your clients more. Have them express your value. Let's have them grow budgets. Have them grow penetration and make your solution stickier. Let's mitigate some churn. They can be put on more high value business tasks which are really thinkers’ tasks anyhow. And get away from the tedium.

So, if we can show the value of the platform with people that do execution then talking to the executive sponsor that's going to actually fund this thing becomes really straightforward. Your team knows that they will not have to do this tedium anymore. The five person three-day job at the beginning of the month, every month has just gone away. When it comes to the economic side definitely we're talking more with the executive sponsor inside an organization. 

NN: Are there markers of an organization that is going to be more open to embracing the future of automation compared to an organization that seems less prepared and therefore less inclined to actually receiving what automation can do for them? 

EM: We definitely see that there are a lot of clients that if they are confident in what they offer as a service, if they can articulate why they are different than somebody else. You've got agencies always buying for the same clients and the same business and it's a competitive space. If you can articulate your value prop that means you have a set of values and rules systems that you operate by. That is different than somebody else. That's the first foundation that I always look for, someone that knows their business really well. 

The next side is that they have an appetite for growth. If you're already doing it and you don't have an appetite for growth, probably going to be settled in where you're at. But if you have an appetite for growth and you don't want it to linearly scale headcount with growth that's another really good candidate for that because you can get buried in this. Just even finding talent even if the economics started work finding the talent can be very challenging when you have large growth goals. 

And then finally progressive companies that want to get into the longer tale. I'll tell you a story from my background. I worked on an ad platform and then I left that company or I was about to leave that company and I was entertaining other places and I went to an audience company. I was going to sign with them and when I got to the end of that interview my little anxiety kicked in. I was having a hard time putting pen to paper and what was clicking with me was all this audience stuff is amazing. I believe in it. I was just at a place that was doing digital advertising and if they had brought those audiences to me to our organization I would have believed in them just as much there. And they still would never have seen the light a day just because we were underwater with the amount of labor it took to manage specials and to make ad copy updates, and to manage negative, keyword lists and keyword bids and etc. just all those settings that were just taking up all this time. Meanwhile running a very lean business that wasn't a gigantic margin business. Adding more on top of that advertiser's plate was very difficult. 

I want to help agencies do more for their clients while not burying them. That is definitely my goal. And what I would see is bringing them something like more audiences, more complexity. And I just want to make sure that we can make that as simple as possible and help them through this journey. I think when we do that their end advertisers (like the end advertiser that's outside the agency or brand) will feel the benefit of more compelling and more complete advertising and yet not feel the pain of the expense.

NN: If I hear everything that you've said and it sounds like we try to automate some things but we're clearly not doing it with the sophistication that we need so we can stay competitive. What would I need to do at this moment from a prerequisite perspective to best embrace the type of automation that you're describing? 

EM: Well automation is definitely a walk I don't think there's an all-in-one. You just made a statement that you know we're doing some things. I think anybody that's doing anything is off to a great start. You understand the benefit, you look for opportunities not to be repetitive and redundant. And now all we have to do is just more of those things as we go. Understand your business. Say you have a team of 35 strategists, understand where they spend their time. Where are those time syncs that pull them away? And evaluate each one of those things to say, “Is it value added?” Humans don't add a great multiplier effect to copy and paste. We have to do it because there isn't another thing that copies and pastes for us unless you get into automation. 

So, if you're really taking settings from one account and moving it to another doing a small trial on a singular account and then want the worst thing that happens is it's successful. And then you have a thousand other accounts to go apply that setting to. We want to make sure that that's a very easy thing and no longer a deterrent to going and doing the right thing. 

My last venture before this I was writing on a software and in the digital strategist pod and I like to work late. Every 7 o'clock on Friday I would look over and there were two people sitting at their desk with just a desk light on. And they were upset and frustrated and you could just see. And I'd find out what it is and someone had just asked them for a very complicated problem late in the day that needed to be done for Monday's solution. It's miserable. And I really wanted to make sure that that wasn't a requirement of the job. And I think as employers we are looking to help our digital strategist look for places that you can improve their life. I think when you improve their life it will reduce in some ways meaningful and tedious labor. So help them there and then it's great for the bottom line as well. 

NN: I want to ask you a question about talent, in particular. You mentioned talent earlier on, what type of talent are we looking for, so we can best embrace automation in our agencies and advertising organizations?

EM: Well this is going to be one of the bigger challenges in the space like I said there's that two hemispheres of an advertiser today. There's the creative hemisphere and the technical hemisphere and that person is rarer than I wish they were. So we have to talk about where we can level people up and help them make them superhuman with systems. I think there's a way that you can help someone that's not like I'm not strong in creative writing. I'm strong on the technical side and not so strong on the creative side. What I see is the AI generative side really can help augment that type of person. So if you can find someone that's biased to the digital world and weaker on the creative side, AI is a really good inspiration tool. Now they still have to be careful to look for tone of voice and compliance and things like that but they at least will get some ideas from the AI side.

If you've got someone on the creative side but they’re a little bit weaker on the execution and the technical side, I personally feel like automation isn't a great enhancement for that user. They can put something into the machine in the beginning with very simple inputs. And then let it do all of the marshaling and all the construction of the complicated campaigns and A/B groups and A/B sets and audience management and all those other settings that are more on the technical side. 

A technical marketer that has a creative flair is the ideal state and I think where you'll find is that everybody's got some bias. I am extremely biased on the technical side and not so much on the creative writing side. And then there are counterparts that I've met that are completely the other direction. And I believe that we are in a spot right now where you can level up either of those two sides appropriately and find your complete person with some augmentation. 

NN: If I am thinking about the opportunities that AI can afford my organization, maybe I'm a media buyer, maybe even some of what you just described in the last answer doesn't represent me strictly. Me being whoever is responsible for media buying but maybe a larger team. Maybe there's three, four or five people that cover the work that you're describing both technical and creative and what do you have. Who would I want to go to inside of my organization to get buy-in for some of these things? And that almost feels like a repetitive question because you said earlier on I guess if I'm the hands-on keyboard person then I would naturally want to go to somebody at the executive level or somebody who's responsible for bigger buying decisions. But I'm just curious what types of questions or information do I want to put forth or ask about so that there is a greater potential that we can be doing smarter media buying in our organization's future? 

EM: I've seen a few of these different cases and I'll kind of talk about what we've seen so far. As people want to be able to self-service more, you just described a scenario where there are four or five people involved in a singular process. And you know at each of those handoffs there's some overhead in the communication. I put together my part and then I had to write a document about it to send it off to the next person who had to read that document to do their next part etc. There's overhead in those transition spots. And if you were someone that really wanted to start to take singular ownership over more of the process. We've seen that as one of the use cases for trying to get into this transformative state. I'd like to do this on my own with these clients. I'd like to be able to go from end to end and I think we can save money because we'll have a shorter cycle.

If you can set your processes and automation up right, it can work for each of them. And now you've got the capacity instead of for one account. And I know we just use simple numbers there instead of five supporting ones. Now you have five supporting five and they're all whole. And the nice thing is the learnings can get shared at that point. So, if strategist A finds that a certain bidding strategy or placement position or audience works extremely well and they know why, they can say in these scenarios this works better that can get distributed and that can become best practices across all five of those users because it's an automation system. And they'll just immediately reap the benefit of that knowledge. That knowledge share becomes not just conversational not just in a document but actually in a living breathing piece of software that will help you propagate that through your entire business. It is a very cool spot to be there. 

So, I've definitely seen people who want to expand the scope and have fewer interfaces with handoffs from team to team that work extremely. 

NN: What we're going to see moving into the future and I'm sure many organizations have already seen this trending, is that smaller organizations will see people who have hands on keyboards building more of these use cases and rationale for why change and embracing a combination of AI and automation is important to do now. I think there's a lot of exciting things to come in the year ahead. So with that Eric thanks for the time and having this conversation with me. 

EM: I had a great time today. And the last thought I kind of want to leave with is that it levels the field for a lot of people. When you just mentioned the smaller agency. I think the smaller agencies can get overshadowed by large agencies that cast a big shadow. Take the same concept with large brands casting a big shadow over small brands. If you can do excellent work with the same pedigree of work that you could dedicate to a large brand but you can now dedicate it to even smaller brands, what an amazing spot to be. It kind of levels the playing field. The product stands on its own and you can tear up your narrative there. I think it's a great leveling system here with automation and AI. 

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NN: Thanks to Eric Mayhew for his wisdom on automation and AI, there's so much change we're struggling with right now in the ad tech space. Most notably the deprecation of third party cookies, reconciling MFA sites, managing brand safety, CTV measurement and more. On top of all that, organizations need to level up on any existing traditional systems that remain to ensure that they're inching out the competition. Now is the right time for agencies and brands to do that deeper analysis of their existing text deck to see what automation can do for them. That's all for now. This is Adtech Unfiltered with Noor Naseer. Another episode coming out real soon. 

In this episode, host Noor Naseer delves into the intricacies of supply path optimization (SPO) with Ian Trider, Basis Technologies' VP of Product (DSP).

Trider sheds light on the supply path’s crucial role in impactful programmatic media buying, and on how this strategy enhances transparency and efficiency in the digital advertising supply chain. Listen in to learn how advertisers can benefit from selecting optimal paths to reach their target audiences while minimizing costs and fraud, amongst other hot themes.

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Episode Transcript

Noor Naseer: This episode we're taking a closer look at the supply side. There's a rising consciousness around supply path optimization (SPO) in 2023. While not a new concept, adtech players are presenting new offerings to remove redundant intermediaries and streamline access to supply. Ian Trider, VP of Product for Basis DSP joins me to share his perspective on SPO and some other supply-oriented topics including header bidding, and also qualifying inventory types alongside the IAB Tech Lab, and more. Let's get into this episode with Ian now. 

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NN: This episode this week we are featuring an inside guest here at Basis. It's Ian Trider. He's a VP of product, specifically working on the DSP. Ian, how are you doing? 

Ian Trider: Great, Noor. How are you? 

NN: I am doing well. I'm noticing a lot of changes internally at Basis and, of course, there's a lot of changes happening in the industry. Very curious for your perspective. You're known both internally and externally as a person who's a truth teller. So today I wanted to focus on things on the supply side, so we'll just jump into one topic and then get into a couple of other ones, starting off with header bidding. Header bidding is not a new topic in the industry—it’s been around for, I want to say, eight plus years, maybe introduced around 2015. For people who aren't too familiar, and they want to get acquainted with what's happening on the supply side, can you give me a definition of what header bidding is? 

IT: Header bidding is a glorious messy hack. So, before header bidding, the idea of displaying the ad and asking for the ad were co-mingled. These were not separated in any way. So, there was no concept of being able to ask an ad exchange, do you have an ad for me for this ad slot? What's the bid worth? And then being able to make a decision based on that information. And header bidding solved for that and decoupled the idea of asking for something to show in the ad slot from actually displaying it. And so, in practice, header bidding involves some code that a publisher runs on their web page before their ad server actually starts and does anything, and that handles the part that requests from ad exchanges.

And the glorious hack part is where that client-side code sets some special targeting setting in the ad server. So that even though the ad server doesn't know about header bidding, it makes it possible through some roundabout means to cause the ad server to sort of trick it into valuing that. Suppose it's a bid coming in from an exchange like OpenX, it allows the ad server to know that OpenX is offering a bid at a $1.25 or whatever the case might be, and it enables a holistic auction. It enables full, actual real-time price competition between any exchanges that you're integrating via header bidding between Google's ad exchange, and also, with anything that's booked directly in the ad server. 

So, header bidding completely changed everything. It caused a lot of changes for the supply side because the interesting thing there is that suddenly there's very little differentiation to be found between ad exchanges for publishers. I mean, all of the exchanges are getting to compete equally in real time. So, as a publisher why do you care who is offering to fill the impression? All notable ad exchanges are integrated with all the same DSPs. So, it caused a lot of shake up on the supply side. 

NN: Are there any potential drawbacks or challenges associated with header bidding? Who would they be for? I think your answer already clarified this to an extent, but just to hear your follow-up take.  

IT: Yeah, I mean there's a couple of different ways to look at that. In the technical sense you can look at it, which is it needs to block display of the ads for a short period while this auction happens where all ad exchanges are solicited for the particular opportunity. And that's happening from the user's web browser. So that puts some burden on their device, consumes some bandwidth, but it also means a delay before those ad slots can load which can have some negative effect for the publisher in reducing the number of impressions that come to exist. Although the extent of adoption of this, I think indicates that publishers see the benefits as outweighing the costs. And there's different ways to mitigate that too. There's technology available that allows that to be moved completely away from the client side.

Certainly for ad exchanges it means that they need to find some other way to differentiate themselves. Because when a publisher can ask in real time for “What's your best price, OpenX?” and “What's your best price, PubMatic?” there's no reason for a publisher to not just plug as many of them in as possible. Right? There's very little opportunity cost for the publisher: They can simply plug in more and more and more of these and, in fact, they do. That does lead to an interesting side effect, though, for the buy side, which is if a publisher plugs in six ad exchanges and they're doing that because they want to try and maximize the opportunity that they'll get a valuable bid. But the problem is that means six bid requests going to DSPs. Six bid requests that all of those exchanges have to send out. But six bid requests are going to the DSP for what is actually one single impression opportunity. So, in that regard there's a fair bit of waste involved. 

NN: And when you say “waste,” how would you qualify what the metric of waste is?

IT: Bandwidth consumed, servers needed, resources needed—because a DSP has to have servers running that can listen to that bid request traffic. And it's kind of illogical to listen to six bid requests that are for exactly the same opportunity and for which the ability to bid and win on is the same. Because, again, if it's being evaluated in real time, if it's solely a question of “best price wins,” then it really doesn't matter which of those opportunities the DSP bids on. It can win it or not all the same, depending on what's in competition. In that regard, it's wasteful. 

NN: You mentioned a little bit earlier, Ian, that there has been incredible adoption of this. So, can you say a little bit more about what adoption has looked like? Would we say that most of the industry has adopted header bidding in some capacity?

IT: Yeah, the best source I know of that is—actually, I think it's discontinued now—Adzerk, which is now Kevel, was publishing a header bidding index where they tracked the adoption of header bidding across—I think it was the Comscore top 500 sites or somebody's top 500 sites. Anyway, the vast majority of major sites are now using header bidding, often with many different exchanges plugged in. So, I would say that at this point this is absolutely the industry norm for how publishers handle integrating with exchanges, publishers of any notable size, that is. 

NN: And have there been any updates in the header bidding space? Has there been ongoing conversation about the iterative improvement of header bidding in 2023? 

IT: Keep in mind header bidding, like I said, it's an incredible hack. All of this happens without the publisher ad server, and I'm talking about Google Ad Manager because, de facto, that's the only publisher ad server that matters. It's got probably 98% plus market share. This is happening without any explicit functionality in Google Ad Manager to support it. It's a workaround. At the beginning there was not any sort of standard framework for doing this. The way you set up header bidding with each ad exchange was totally customized to that exchange. 

Header bidding wrappers came to exist that standardized this, with the most popular being prebid.js, which is an open-source framework that is supported by all major exchanges and a lot of minor ones. And it is now the most common way publishers configure this, by using the prebid.js code and hooking up the adapters for the various exchanges they want. It makes it relatively easy to implement header bidding.

Further advancement includes moving this to the server side. Instead of having the user's web browser make the request to each and every ad exchange, what if we just have the user's web browser make one request to a server, and have that server make the request to all the ad exchanges? And that is facilitated in a couple of different ways. But the open-source sort of role would be with pre-bid server, which is a server-side implementation. It's something that a publisher can host or pay somebody to host that moves all of that to the server side. So, it is indeed the case that the web browser makes one request to the user's web browser and one request to the publisher servers. And then it fans out to however many exchanges they want to go to from there. But the interesting thing about that is before, when it was all client-side, publishers would have a practical upper limit on the number of exchanges that they could plug in. Because there's only so many things you can try and get a user's web browser to do simultaneously, especially if it's on a slow connection. But if you move that server-side it now becomes nearly infinite. So, this is the thing I was mentioning about the duplication of bid requests, the fact that a DSP could see like six requests for every one impression. In that regard, this server-to-server stuff does make it worse because it sort of removes the shackles of what the end user's device can feasibly do. 

NN: I want to extend from an introductory conversation around header bidding. Not that anything with you, Ian, ever feels introductory. I know you really get into the weeds on everything that you're knowledgeable about. But header bidding is one aspect of supply path optimization. Maybe we weren't calling it that back then. But now there has been this uprising very recently, in the last two plus months, around this breakage in the programmatic supply path with SPO. Can you give us an introduction to where that started and where there's been this link breakage in what has otherwise been a pretty tight-knit chain that's been around in the programmatic media space for quite some time? 

IT: Certainly. What do you mean by “link breakage”?

NN: That we're going directly to publishers for this inventory and taking out some of what would be defined as a middleman. 

IT: The interesting thing about that is if you ask five people for a definition of supply path optimization you will get five different definitions. The way that I would define it is about removing unnecessary indirection in the supply chain. And by unnecessary indirection I mean more people involved in the supply chain than is absolutely necessary. This ties back to header bidding because again header bidding made it possible to solicit all of the exchanges simultaneously, so there is no such thing. Nobody has preferred access; now all of the exchanges have equal access to all the same inventory via header bidding. So, at that point it's even a question of if the publisher has six exchanges integrated via header bidding, what's the point in listening to the traffic from all of those?

But beyond that, there's also indirect supply paths. A surprising number of companies in the ecosystem are heavily dependent on reselling supply to some other larger company. And you can see this in what happens from the publisher’s perspective with ads.txt. So, ads.txt of course being the specification that IAB Tech Lab rolled out to try and quash domain spoofing misrepresention—the ability for people to claim that they have inventory for some domain and just lie about it, ads.txt greatly mitigates that. And it requires the publisher to list all of their authorized supply paths. And a sort of tier-one, A-player sort of exchange will not be asking for anything in that file, other than one line representing that publisher's account on that exchange. But once you get below that you'll find that the sort of smaller players will ask for a large number of records to be added, because they want to or rely on reselling the supply. They lack many direct integrations with the DSPs and instead they rely on reselling the impression through larger exchanges. 

The amount of bid request duplication that a DSP can see as a result of that actually gets quite extreme, and it also introduces a lot of problems for fraud and other issues, because when an impression gets resold through many different parties it tends to obscure where it came from. Knowing where the traffic came from is absolutely essential to knowing that it's genuine. Moreover, if it passes through a lot of different hands, all of those hands have to get paid right. So, in any supply chain that is highly indirect, the adtech tax is much, much higher.

I see supply path optimization as an exercise in removing redundant, unnecessary, duplicative supply chains—inefficient supply chains. An example of that is, suppose we're directly integrated with an ad exchange. Maybe it's one of the smaller ad exchanges, but we're directly integrated with them. But they also hold an account on three or four of the major ad exchanges and resell all of their traffic through those major exchanges. As we implement supply path optimization, we are directly integrated with that exchange, so we don't accept the traffic from their accounts on the bigger exchanges. There's no point. It's exactly the same traffic we're seeing directly, but with less transparency and more adtech tax because that bigger exchange has to get paid. So that's the angle that we've focused on, although there's definitely multiple different interpretations of what supply path optimization should mean. 

NN: I want my next question to be about who's most impacted, but I think if I was listening to your answer carefully or not so carefully, you made it pretty clear that the core impacted parties include anyone who's selling it from a duplicative standpoint. Are there other parties who are also impacted in this shift?

IT: Yeah, well a very aggressive supply path optimization stance could attempt to deal with that scenario where the publisher is integrated with six exchanges via header bidding. This is not even forgetting about the indirect resale of their supply; we're just looking at direct exchange integrations. If you wanted to get really aggressive with the supply path optimization you could try and decide which of those six paths to listen to, because they should theoretically all be equivalent. Some of them might be less expensive and have lower adtech tax than others. This is not a level of supply path optimization that we're doing at the platform level. You start to get into this line where it starts to tamper with what the buyer would like to control over. And, so, we take a little less aggressive stance than that. But you could go that far. If you take it that far then it potentially affects all of the supply side players and has a likelihood of pushing some of the bit players out.

NN: So I want to explore a little bit about what you said further, As far as analyzing or evaluating who to go with if there are six supply partners that you could be working with and you're evaluating the fees and potential cost implications. What does that evaluation process look like for you to minimize duplication and just bring more efficiency to the overarching platform?

IT: One of the other reasons why we don't do that type of “figure out which of those six direct supply paths to listen to” is because fundamentally it's nearly impossible to actually reliably do that. The problem is there's no way to know that the six bid requests that you're receiving are all for the same impression and there's no way to reliably analyze that multiple supply paths are literally sending you the same opportunities. There's lots of subtleties in this: A publisher could work with some exchanges only for certain geographies or for certain ad formats. So there's a lot of complexity in that. And there are some efforts that have been made to try and give some more information that helps with this like a global placement ID, like the idea of a global transaction ID. Neither of those things is anywhere near universal though.

In practice, it would even be considered the question of fees. The fee information is not something that the buy side has. The buy side does not know precisely what the publisher is being charged by the exchange. Certainly, you could go ask the publisher. I'm sure there's plenty who wouldn't mind telling. But it's possible to see that indirectly: For example you could look at the win rate and you could say, “Well logically the exchange with the highest win rate must have, from the perspective of the buyer campaign, the exchange with the highest win rate must have the lowest fee because they're sending the highest effective bid into the publisher's auction.” But there's subtleties in that that interfere with doing that sort of analysis at a platform level. There are subtle technical differences in the way the exchanges operate. For example, some of them tell the DSP upfront what categories and advertisers are blocked. Some of them don't. And so, because of that one that doesn't provide that information, the DSP will bid not knowing that an ad is going to be blocked, and that's something that affects the win rate right. So, there is a surprising amount of subtlety in this. And it starts to get really risky really fast to try and duplicate those direct supply paths. 

So, at present we're not attempting to do that. We're just addressing the obviously, clearly indirect supply paths, intermediaries, and other low-value or questionable sellers. 

NN: How would you say that that philosophy that we're using at Basis compares to what's happening on a larger scale in the adtech industry? There are multiple adtech players who have really created a lot of noise around the development of products or solutions that are focused on—like there’s this nomenclature around this new SPO release. So how do we distinguish what we're doing from what other folks are doing?

IT: The thing about this is it's not necessarily bad for the buyer for a DSP to more directly integrate with the publisher, but there are a couple of considerations that you need to keep in mind. When there's this separation of concerns where the DSP is clearly working for the buyer and the SSPs are clearly working for the publisher. Up until a couple of weeks ago I was the vice president of RTB platform operations, so I was directly involved in the supply path optimization endeavors or anything to do with supply quality. And it's not a problem you can just block: So you know if there's fraud, or if there's some sort of supply quality concern of another sort, or it's an indirect supply path you can just block it. You don't have to ask anybody. It's real time bidding. A DSP doesn't owe anybody on the supply side anything and it doesn't have to bid on anything. However, if the DSP starts working directly with publishers, now there's human-based complications. Now it's not as easy as just blocking it because there's a publisher that you have a direct business relationship with that's expecting you to be buying their impressions. So, it starts to really muddy the waters in a way. There’re ways that it can be managed but it's something that a buyer would be warranted to make sure that the DSP has carefully considered so that the DSP isn't making choices that aren't aligned with the buyer’s interests. 

NN: If you were a media buyer, Ian, is there anything else worth knowing as a buyer as it relates to the progression of work from an SPO perspective from the DSP that you work with? 

IT: Yeah, it's not so much about the DSP they work with, but I would express a lot of skepticism about ad exchanges coming and offering SPO. Because the thing is, the nature of SPO in the sense I described of removing indirect supply paths can't just be a matter of cutting a deal with an exchange and giving all your money to them. How does that ensure that that's the most efficient supply path or that it's removing duplicate supply paths? So honestly the amount of subtle data that goes into analyzing this stuff is extreme. And I think that buyers are best served by working with DSPs that have good platform-wise policies, because as a buyer you would absolutely lose your mind trying to do this yourself. First if you can even get the data, because the necessary information for this is not typically in DSP reporting. You can probably get it out of log-level data from DSPs, but then you're going to need an ads.txt crawler and you're going to need a seller's json crawler. And you're going to need to parse supply chain data. And then you're going to have to have a bunch of analysts pore over it for a huge amount of time. And you could do that, or you could just let the DSP take care of it and do it once across all the DSP's customers. 

NN: I also wanted to talk to you today, Ian, about defining inventory. Something that you've worked on as a part of IAB Tech Lab has been the redefinition of some supply types and one of them being in-stream. Can you tell us a little bit more about your involvement there and how you've helped define this one supply type? 

IT: Look, here's my position: The definition of in-stream has fundamentally not changed. The definition of in-stream is an ad displayed before, in the middle of, or after some video content that the user chose to watch. Now, the problem is that there are some companies that have been really stretching that definition. There's a lot of ad space on the internet that's being called “in-stream pre-roll” that I don't think qualifies as content that the user chose to watch. I mean, when somebody says in-stream or when you talk to a buyer about in-stream, they're probably thinking something like YouTube, ads before some streaming video content that the user meant to watch..

They probably weren't thinking or expecting that it's going to be some floating player that pops up in the bottom corner of the screen on a recipe blog that just shows some unrelated video content that they never asked for and plays an ad before it. There's a lot of inventory being circulated that's being labeled in-stream that fits that definition. So, the adjustments to the definition are intended to clarify and bring us back to what in-stream is intended to mean. And put things like what I described into their own sort of category which is being called, “accompanying content”. Hopefully this should clean up and ensure that when buyers are bidding on in-stream inventory they're actually getting what they expect instead of these other formats that are only in-stream if you squint really hard at them. But it does mean that if people are expecting to get large volumes of in-stream video inventory at $7 CPM it's just not going to happen. 

The real in-stream inventory is inherently scarce and valuable and it will trade at those prices. But if that other format I described is of interest or desirable to buyers in the future, it'll be possible to explicitly target that format now. So, the inventory is not going anywhere, it's just being more correctly labeled. 

NN: Your focus as of late has been on in-stream, or recently has been on in-stream, but there is probably an issue with the definition of a lot of different inventory types. When did you really start picking up on the fact that there were people putting things into boxes that they didn't belong in? I'm sure it's been happening in the industry for as long as it's been in existence. But when did you decide to really get involved? 

IT: This conversation has been going on for a while in the Tech Lab working groups. And I don't want to speak too much about what happens inside there because it's private business until public release of something. Broadly, people lying about things is an ongoing, fundamental concern in real-time bidding because somebody once described it to me as trading bites for money. A publisher sending a bid request series of bites of information. And depending on what you set in there, depending on which bites you send it, affects how much money somebody's going to give you. And so there's a natural incentive to convey the inventory in a way that'll maximize what people are willing to bid on it. The problem is when that's not true it starts to look an awful lot like fraud. 

NN: That's the thing about fraud. We haven't talked about fraud in particular today, but I think there are some gray spaces and maybe redefining the terms of what something a client thinks they're buying is, versus what they're actually buying—it falls into that kind of gray space. So, I also wanted to ask you about other types of gray spaces that exist, including MFA or “Made For Advertising” websites. What are your thoughts there? I feel like I'm encountering MFA websites all over the place. They're not great environments for me as the user. But I think a lot of advertisers and marketers are unintentionally buying in those spaces. What do you think the advent of this is? Are clients not being advised? Do they not know? Can you give us a little bit of backstory on just MFAs in general? 

IT: First, I'd say it's not a new phenomenon. This has been around forever, and, in fact, is fundamentally nearly the entire online publishing industry—I mean all publishing is made for advertising, if you really think about it. Like, the point is to sell inventory. The point is to bring eyeballs to the site and the site has ad slots on it and you sell ad inventory. But of course, that's not what anybody means by “made for advertising.” They specifically mean sites that are not really intended to deliver real value to the user, that are almost always—like nearly exclusively—visited by paid traffic. So, users arrive there by clicking on paid links or things like that.

The value of a site is largely in its audience. People want to put ads in the New York Times because the New York Times has a certain audience, and that audience is valuable to advertisers. So, one of the problems with these made for advertising sites is they don't have any endemic audience. You can't say, you know, “here are the sort of people who visit the site.” It's just whoever clicked on the link in the recommendation widget. That doesn't mean that is valueless inventory. It's just that it's not got a lot of innate value. I mean, if you sprinkle some third-party audience data over it, it might have some value. But by itself, it's just sort of filler. It's just a sheer sort of tonnage. 

Related to this is the problem with this paid traffic sourcing, is that it's a very hard arbitrage. The objective here is you're going to buy eyeballs into the website and get people into the site. You want to make more money off the ads you serve to them than it costs you to get them to the site. That's really hard math to make work. One of the ways some of these sites do it is with the ridiculous slideshows, where they suck you in with some very sort of shocking or interesting thing in the thumbnail in the recommendation widget. And after you've clicked through 20 pages you find out that it was never a part of the slideshow in the first place. But they've now served a ridiculous number of ads to you. 

One thing that a lot of sites end up doing is resorting to very questionable sources of traffic. There's sort of a hierarchy of paid traffic sources and up at the top are things like Facebook traffic from Facebook ads and things like that. And then some of the higher-end native ad or like recommendation widget-type sources. But things start to go downhill very fast all the way to the point of just absolute blatant bots, because it is all about that arbitrage of “How do I make more money from serving ads than it costs to bring this person to the page?” And because that math is so tricky, it drives the owners of these sites toward the dodgier and dodgier traffic sources. And as a consequence, these sites tend to have a lot of invalid traffic, or it's certainly not high-value traffic in the best case, but in the worst case outright bots. 

NN: How often do you think the supply side or generally speaking has there been an uprising of rejection of these types of sites? Or do sometimes people try to create the opposite case of what you've said? You’re saying there isn't an inherent audience; some people might say, “No, but people are intentionally clicking on them.” And they might be seeing some value. They just have to do some extra labor, and that extra labor implies there's more clicks. So, people might be coming up with their own use case just to go back to the original question. Like has there been this rejection or the opposite? 

IT: I'd say there's an increasing rejection of this by the buy side. The sell side, on the other hand, it is important to keep in mind that nearly everybody gets paid a percent on what gets transacted. For an ad exchange, there's a natural incentive to add more and more inventory. More inventory means more money gets transacted, which means they make more money because they get a percent of the spend. And that's true for DSPs as well. But the thing is DSPs are exposed to the entire universe of inventory. It's a very big universe, it's too big of a universe. So, the incentives aren't quite the same. The DSP doesn't need to listen to all this. The DSP is probably looking at their hosting bills and going, “Oh my God how am I gonna pay these bills? They are getting out of control.” So, there isn't the same incentive to tolerate the traffic.

Then, as for buyers, I think it's going to vary. I think you will find buyers that are perfectly happy with it. The buyer incentives aren't always necessarily aligned with the advertisers either. So, it's sort of just a fundamental concern of this industry. I would say the interest in doing something about this is largely coming from the buy side. 

NN: That's fair. I am curious what you think is going to happen in the future as these gray spaces continue to mutate—if it's not in-stream tomorrow, it's going to be something else. And if it's not MFA, what do you think is going to be the next mutation? 

IT: The bad things always trend toward the novel spaces with less verification and more buyer excitement and higher CPMs; in other words, connected TV. The risks in that environment are substantial. I very strongly encourage people to heavily scrutinize precisely what they're buying and who they're buying it from, but it's the holy grail because it's got high CPM, scarce supply, very little actual verification of what it's served to or where it's served is technically possible, which is just a perfect storm for bad people to exploit. But I think we'll probably see this with other emerging formats, too. I think you can probably expect that problems will come up with audio, even digital out-of-home, perhaps. Digital out-of-home, for example, one simple way is there's this idea that one display of the ad is worth ‘n’ impressions. Where ‘n’ is more than one usually. Where does that number come from? And on a reputable exchange where that comes from is some sort of auditing organization like Geopath, that's actually physically audited and observed and done traffic counts and come up with an estimate of how many viewers that's expected to have. But in the worst case it could just be a number somebody makes up and if you make that number bigger you make more money. So, that's something it'll be necessary to watch out for in the future. 

NN: Ian Trider is the VP of Product on the DSP at Basis Technologies. Ian, I know you have a lot to share and there's going to be more conversations to be had, so thanks for the time. 

IT: Thanks, Noor.

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NN: Thanks again to Ian Trider, VP of Product for the DSP at Basis Technologies. I'm planning to feature Ian on a lot more episodes because he's very knowledgeable about intricacies in the adtech space, particularly aspects that not everyone is promoting and publicizing. And really, that's what we're here to do: to learn more about the adtech space and some of the things that are not always being discussed. So, until then, this is Noor Naseer. More Adtech Unfiltered real soon. 

What does it take to uncover what’s really going on in adtech? A whole lot of effort that not every advertising professional knows they need to put forth. In a fast-growing multibillion dollar industry, it’s increasingly challenging to discern truth from the carefully crafted narratives propagated by ad solution providers.

In this episode, industry thought leader and AdProfs founder Ratko Vidakovic joins host Noor Naseer to discuss how to find and distinguish adtech truths from not-so-hidden agendas.

Episode Transcript

Noor Naseer: How do you find the truth in adtech? The answer is… Not easily. Under piles of stylized marketing fluff, it can be challenging to discern the fundamentals changing the industry, from carefully crafted narratives propagated by solution providers. And once you do identify an important topic that needs discussion, it can be dense and complicated to break down. That's where Ratko comes in. He is the founder of Ad Tech Consultancy AdProfs and editor of the newsletter, This Week in Ad Tech. Ratko is someone who's putting in the work to break down topics in a big way. And he's got a ton of advice on how you can do the same. I’ll talk to him about the tools, tips and tricks you will want to employ so you can educate yourself, build perspective, and dismiss the things that you can skip prioritizing. Let's get into this conversation with Ratko. 

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NN: So Ratko, you and I we've known each other for a while. We have some professional history together. You came over to what was once Centro, that turned into now Basis and the time there was an acquisition of Site Scout for a DSP. And now you've moved into a space that I think there's a lot of interest in to educate people and give them the consultancy they need so they can be more informed in this adtech world. Can you tell me a little bit about what you do in ad tech so that we can talk today about how people can stay better informed in the industry?

Ratko Vidakovic: Sure. So I guess outside of consulting, probably most well-known for writing a newsletter called This Week Ad Tech. The premise is that keeping up with all the developments in ad tech is hard. And it's time consuming. And the newsletter helps readers save time by curating the most important stories of the week, summarizing them, highlighting interesting parts, just making it very digestible for the reader. That's kind of the core of it. There are also some other features like question of the week and tweet of the week, but those are like more side dishes. They're not the main course.

NN: I mentioned earlier that we used to work together. But it was this venture or a variation of this venture that you're now on that led you down this pathway. Can you tell me a little bit more about what led you to leave having a W2, actually, you're in Canada, so you don't have W2s, but you know what I mean?

RV: Sure. So primarily, it was feeling like there was a gap in the industry. And just in terms of general education and advisory. There were, to be sure, consultants, like ad tech consultants that existed, but I felt just given my background on the DSP side, helping build a DSP from scratch, that that was a unique experience. So that's kind of what got me into starting AdProfs and also just kind of coming from the marketing side and coming from a role, which was like product marketing, which is heavily content oriented, right, like creating a lot of content. It was very appealing to me to have that creative control over sort of publishing content and creating content. What sort of made me go down the pathway of the newsletter specifically was more like an evolution of the marketing strategy that I had for the consultancy. So I knew from the beginning that I wanted to make email the core of the marketing. And in the first year, I didn't really have a strong value proposition. It was just sort of like signing up for updates when people came to the website. And I knew I needed to change something, it had to be more frequent, it had to be relevant to ad tech and it had to be valuable. And sort of that's how This Week in Ad Tech was born.

NN: You sort of already answered this question I want to follow up with. There's no shortage of newsletters, whether it's related to—well, maybe there is somewhat of a shortage in the ad tech space. And we'll talk more about that. But there's plenty of material or content that's readily accessible on a daily basis in this space. How have you tried to distinguish yourself to make sure you're adding value so people can be truly informed?

RV: Yeah. So I think it really kind of comes down to adding perspective. Beyond just sort of common like off the cuff commentary, I tried to look at things from a variety of different lenses, different perspectives, thinking about the various stakeholders across the industry, when it comes to any piece of news. So for example, if we're talking about something like an article that's written by a publisher, and it's clearly written for a publisher audience, you can take the points from the article at face value, or you could look at it from an advertiser's or DSP’s perspective. Does it still make sense? Do any of the points conflict with what advertiser's value and what they prioritize? So I really approached it initially as a way of just sort of adding detailed analysis on top of sort of the summarization. So kind of asking myself like just scrutinizing, like, what's clear about this? What's unclear about this? What's certain to happen? What's uncertain to happen, likely, unlikely? What's important about this? What's not important? Trying to provide some kind of explanation for given the facts of like, why companies are doing certain things, why they're making certain choices, making certain investments; kind of almost like going through like a mental laundry list of questions and kind of going through it in that sort of way. 

NN: What you just did described, I think is something a lot of people in the tech, the martech, the advertising world, they want to do that. But it's such a struggle. And that really is the thesis of our conversation today is people aren't all in the business of developing a newsletter where they can make that their priority for the day or every day. Instead, what's happening to them is they're getting this random note from a client or some other invested party who sends them maybe a forwarded, let's say, piece of content. And the only line included is, “Thoughts?”, or, “What's your POV?”. And that really puts you on this long, twisty road to try to figure out a perspective on something you may know very little about, or you've heard about but really don't know how to provide perspective. So I want to expand into that and more of your process. I know you mentioned using some of your discerning skill sets so that you can break down topics, but it's easy to say it's very hard to do. Can you expand on what some of your processes or methods are to stay on top of things happening in the ad tech space?

RV: Absolutely. So maybe I can talk about some of the mistakes I made at the beginning. So one of the most inefficient things that I did in retrospect, while doing the newsletter for the first few years. So it took me some time to kind of realize my ways. But the first few years, I was combing through all of these different news sources every day, everything from the daily newsletters from the trades, Twitter, LinkedIn, Google Alerts. And so, I was just basically like, emailing links to myself. So, I would manually open each link, at the end of the week, read it in my browser, just sort of super manual, super time consuming. Then I remembered this kind of old thing called RSS that I sort of mentally wrote it off when Google Reader died. And I started looking into more new school RSS readers. And they've really kind of come a long way. 

I think that was a big part in sort of streamlining my workflow, because it more or less, puts all the information into one place, instead of like scrambling trying to go to all these different collection points. So from there, now that sort of everything is more or less centralized in the RSS reader, every morning, I go through the daily feed, and anything that I find interesting, I flag it, and it goes into a separate area of the reader. From there, I only read the articles that I flagged as interesting. And from there, I only choose the articles that I feel after reading them are newsworthy or interesting, and I shortlist them for inclusion in the newsletter. 

I know I'm kind of like jumping over a lot of details, because you could probably pause on each of those and say, “How do you decide what's interesting and all of that?” Maybe we can come back to that. And then from there, once I have that shortlist, I go through each of the articles with a fine-tooth comb. I scrutinize, like every word with some of those analytical lenses that I just mentioned. And that's where I kind of generate the questions in the comments, and make those kinds of connections between past events, and connections with research data, and connections like somebody's social media posts or whatever. This part is a bit harder to explain. Because it's like how our brains work. It's a little bit of a black box. So it's like, how do you make all these connections between this current information, nd ahistorical information, but I think like one way that does help is Googling, or, in my case, I go through some of my old newsletters, I see what I previously covered, I see what I previously wrote, that kind of gives me some ideas and some context for things. But at some point, in the process, it kind of becomes a little personal.

NN: You mentioned there's this grand process that you're going through. I think in theory, other people are trying to do the same thing. But it just ends up unraveling a lot of the time where your intention is to “Okay, I want to learn about this topic. I think I've subconsciously or consciously picked up on the fact that it's been mentioned a couple of times. But the second that somebody asks you to share something a little bit more comprehensive or thoughtful, it is hard to do what you are describing.” How do you make sure that you're going on a journey or a pathway to actually formulate perspective?

RV: I'm the same way. I have way too many tabs. I have a very powerful laptop that most people use for graphic design, and programming like heavy duty programming and stuff like that. And all of the resources go to running Chrome tabs. So I have a powerful machine that's just for the memory hog, which is Chrome. But that being said, I guess maybe this is not a satisfying answer. But some of those rabbit holes that you mentioned, actually, I don't avoid them. I love going down them and it gives us like a personal thing. That's just me. You do have to have a system for staying organized. And so for me, I'm fairly organized when it comes to note taking. It's not a perfect system. But if I go down rabbit holes, just like you, I want to learn about something I want to see how it actually works. I have to open like five or 10 different tabs, but I feel like the notes for that subject or for that newsletter always kind of bring me back to the original task or the original story. And so, I use tools like Evernote and Motion to sort of keep my notes organized.

NN: It's seemingly such simplistic advice. But I think not enough people are probably doing that including myself, like you said it might be our downfall, having 100 tabs open. And admittedly, I've had conversations with multiple people who have said that they're trying to research a topic and they just never turn their computers off. And then one day, they get like the blue screen, because they have hundreds of windows open for actually multiple, maybe failed attempts at trying to educate themselves on something amongst other windows. So it's definitely a challenge. But I think just like you said, tethering yourself back to what is the, like, the purpose of this journey that I'm on. So doing some note taking to keep yourself in check is definitely a good idea.

RV: If I could also just jump in and add a little extra on that, I think another part that was challenging for me for quite some time, and it probably is a challenge for a lot of other people, I'm guessing as well is what you do about PDFs. There's so much information that comes in PDF form, like those can be in browser tabs, for sure, they could also just be opened on your computer and minimized. I find that when there's something that's super long, like 50 pages, 100 pages, 300 pages, antitrust lawsuits, and stuff like that, the solution that I found was getting a PDF reader for my tablet. So in my case, it's an iPad, and I forget the name, I think it's like  PDF Viewer or something like that. But it links up with my Dropbox. So I created a Dropbox folder that has all the PDFs that I want to read. And then there is an integration that the PDF reader has with Evernote so that things that I highlight automatically go into Evernote. So it's like a way to bridge the tablet with my note taking system. So again, kind of like this concept of funneling everything into, like, a centralized place where you can actually make sense, I found that to be helpful in kind of consuming and processing information that's in these PDFs. And sometimes it's very hard to sit at a computer for hours trying to read a PDF. So it's a lot easier to just kind of lay down on the couch with a tablet, and then try to read it. 

NN: For anyone listening who's thinking like “These are just the mechanics of researching something with competence”, I will say I feel very confident that there are many people struggling with just addressing these very simple questions, because they're not processing it consciously. So there's definitely value to thinking about that. Because there's always these unsolved mysteries around why we can't answer questions, and why things are taking too long for us to offer valuable perspectives. I think if you work in the advertising and the martech, ad tech space, it is critical for you to advance in your career by bringing valuable opinions to the table. So I want to jump further into that. What does it take to actually formulate an opinion, especially in an industry where it seems like there's a lot of regurgitation, people will give you quote, unquote, insight, which is actually just copying and pasting what somebody else said, and then maybe restating that? How do you step away from that? I know you already talked a lot about connecting the dots. But how do you turn something that is raw, quote, unquote, information into actual perspective and insight?

RV: If all you rely on is articles that are from, like, industry trades, that's probably the easiest route to go. But if that's all you rely on, I think you might get some high-level information about the topic. So maybe we're talking about carbon emissions or something like that, or how carbon emissions affect ad tech, that's like a relatively new topic. If you just read the articles, you might see that it discusses supply chain efficiency, and kind of these things in broad strokes. I feel like a lot of articles miss out on the how, sort of the how question and answering that. And that's where I think it's important, or at least I personally feel compelled to kind of dig deeper and figure out how it works. So in that example, or case, for talking about carbon emissions, or sustainability and ad tech, I know from my own experience, kind of going down that rabbit hole, that there's a GitHub repository. So that's like, usually where developers, programmers kind of keep code. But some people also keep technical documentation and explainers and stuff like that there. So there is a GitHub repository from Scope Three. That's kind of like the new sustainability startup that Brian O’Kelley from App Nexus started. They published some preliminary sort of methodology documentation there, which explains how they're actually measuring things like the carbon footprint of ads. So from there, just kind of based on reading about some of the methodology, at least now, I feel more informed than I was if I didn't go down that rabbit hole and try to figure out kind of like, the how, if that makes sense.

NN: In the instance that people are ingesting different types of information about a topic and it's being sourced from a solution provider that benefits from talking about a topic. Let’s go down the identity pathway that I was talking about earlier. So there's, I want to say dozens? Let's start with dozens, not hundreds, but dozens of players who have thrown their hat into the ring, trying to be at the center of what the future of identity looks like. So what they'll do is be in touch with the trades, or they'll have some sort of article published that directly correlates with what they're bringing to the table. And it's not a sponsored article or advertorial. It's them having been able to position what they bring to the table as something that is going to be valid for the greater industry. So you start reading it, and what you're trying to do is—you being somebody who works in the ad tech space, and maybe you work at an agency or something else, where there's a responsibility for media buying—trying to figure out how important is this identifier or potential solution for me to consider. 

So I'm saying that very generally, I'm not trying to target any one identity mechanism out there. But if I was starting to read through that they're going to share some of their maybe push points to say like “This is in line with what's going to be beneficial for advertisers. This is what marketers are going to prioritize. This is going to be central to what you being able to target purposefully is going to look like. If you saw a piece like that—you’ve probably seen hundreds of pieces like that—how do you start to ask critical questions around the validity of what they've shared?

RV: So I definitely think especially working in ad tech, like all of us working in ad tech, there needs to be skepticism by default. I think it's just because there's so much BS. And also, like you said, there's a lot of veiled promotion, right, like stuff, that's it could be a Q&A with a company, it could just be like a puff piece, essentially. So there's definitely a lot to kind of filter through, it's kind of going back to the earlier point of like, sometimes you can tell just by the headline, like the title, the author, the publication. When you do it long enough, sometimes that's all you need to kind of filter things out. But I think personally, it's important to use a critical lens when reading anything about ad tech or in ad tech. But I think at the same time, you have to have a balance. So you never want to go completely negative or cynical about certain things, because I don't think that's necessarily helpful. And also, if you take that approach for too long, people will just tune you out, like they won't take you seriously. 

At the same time, you also don't want to be extremely optimistic, or pollyannaish because that kind of borders on delusion, and ignores the real issues that inform strategy and shape the path of the industry. So one example was a few years back, but Chris Kane from Johns Media did some research that kind of called out the practice of “Bit Caching” several years ago from certain SSPs. And I thought that was important, because if that wasn't called out, it wouldn't have been addressed. So it's definitely something that I think people need to force themselves to do. It's not easy. It's hard. But I think everyone needs to kind of force themselves to find a sort of balanced perspective. To me, I think that's one of the keys to good analysis, like good reading of any source material.

NN: It's a fair point, and maybe a part of my questioning has to do with the fact that I think there's a natural reluctance to do that, because that means there's going to be more time commitment to actually digging deeper. A lot of our conversation has been oriented around, you're going to need to do more, you're going to have to read more, you're going to have to connect these dots in a way that expands well beyond the scope of maybe what you want to hear. To that point, I wanted to ask you about sourcing, going to credible sources, not going to places where maybe you're more likely to get some of those puff pieces or information that isn't actually information. I'm sharing air quotes for anyone who's not watching this. So let's talk about some credible sources. You've done a lot of that vetting already. What are some top media sources or publications that you enjoy reading?

RV: So there's certain publications that we'll mention, but they more or less regurgitating press releases. And I don't think that's very valuable, in my opinion, because you could just go to PR Newswire and get that information. But I think there's definitely publications that do a good job of trying to inform and educate readers. I'll exclude myself there but AdExchanger I think is a good source for sort of steady industry news, not necessarily the best signal to noise ratio, but it is a core like it's a leading publication, you can't ignore it. Digitay is also good. Ad Week is good. Like these are all for the very specific like ad tech, niche. Marketing Brew is a relatively new player. Marketecture.tv is also a relatively new player as well. But they're interesting because they do sort of vendor0specific interviews and the interviews are done by sort of experts, like industry experts and practitioners. So it's sort of less of a media interview and more of the first call that you would have with your vendor. So it's more of an in-depth interview. There's also a bunch of general publications, Axios for example, they dropped some great scoops occasionally. Like it's not something that you can count on every single week, but it's worth following just for the sake of those scoops. Same thing with Business Insider, Wall Street Journal, Financial Times, but that's like a needle in the haystack kind of stuff. You don't want to be reading every single article from those if you're trying to search for ad tech. So it's not easy.

To your previous point, none of this stuff is necessarily easy. And it definitely requires putting in the time, like there's no getting around just the hard work of just reading and focusing on that. After doing it for a while you can safely say like, what places what publications are worthwhile reading, worth following and which ones perhaps aren't.

NN: I think what some people can walk away with, because obviously, I've made you hammer this point home, like multiple times across this interview is that you, you really have to just commit to doing the work. Depending upon your position, you have to commit other people to doing the work on your behalf, but somebody has to do it to just also expand away from doing the work. It's me getting a better sense of where you are actively doing research right now on hot topics. Like I was saying earlier, sometimes maybe there are things that someone or some entity, company wants to sensationalize as a big hot new trend, when really it has more to do with their business. And then there are legitimate things that are going to affect and change the shape of the ad tech ecosystem. I've recently heard you say that you do have interest and excitement in AI, if you can expand a little bit on this topic, I think there would be interest.

RV: It's interesting that you're talking about hype, like you framed it in terms of like some companies like GE just hype it up, because that's their domain, or category. But I think in terms like AI and machine learning, those terms were kind of tarnished to some degree, either through overuse or abuse, sort of as buzzwords, I think going back at least, like seven, eight years ago, even when we were working together I think at Centro, Rocket Fuel was around. And I think we all remember them talking about their artificial intelligence and rocket scientists and all of that. The reason I say that is because I think it's easy for someone to just kind of roll their eyes when they hear the term AI like it's kind of almost been tarnished. But I am genuinely excited about the rapid pace of development around AI and just about the potential for AI to just change how we do knowledge work. Even some of the stuff that we're talking about right now, I think there are new product opportunities that are possible. Everything from workflow to graphic design to transcription, it's an exciting time to be alive.

NN: Where or what have you read that's made you excited now, knowing that there was this excessive hype up seven or eight years ago, everybody, every news publication under the sun is covering it. So I think it's a very different topic and opportunity from many other things. Web3 was the hot topic of 2022. And for 2023, it's very much angled around AI. I think there's far less suspicion or skepticism around AI, given so many of the findings. So are there any findings, or things that you've read about that have legitimized AI and the opportunity for you?

RV: For me, it's maybe not so much things that I've read, it's actually things that I've done that legitimized it. So I've just been playing around with it. Like I've been “getting my hands dirty”, so to speak, using the open AI sandbox and even kind of not being a programmer, but knowing enough that I could play around with their API, and actually test this stuff out firsthand. And that's kind of what made me a true believer is, you know, something is not vaporware, when you can actually use it, and you see the value with your own eyes. I've played around with everything, from ChatGPT questions and answers, asking summarization questions, having it almost be like a personal assistant and like, explain the differences between certain things. And instead of having to just click through on all these different links in Google, it's like having a legit personal assistant that's answering stuff in a satisfying way. Even on the design side, image generation, playing around with like, MidJourney, and going down that rabbit hole, absolutely mind blowing, like, just from a marketing perspective, like taking something that's only in your imagination, and being able to describe it in just prose, right? Like, imagine, because the instructions for MidJourney are like slash imagine, and then you just describe what you want it to look like. And to take something from literally just a description in your head to seeing it visualized within a couple of minutes feels like magic. So I'm not sure if that answers your question or not, but maybe you can see. I'm like a nerdy guy, super excited about it.

NN: You're pumped. You’re pumped up. Yeah, it's the practicality of the applications. I think what we experienced a lot in 2022, and 2021, with many different elements in the Web3 space, was that it was a lot of describing the potential of something without a lot of substance behind it. It's like, “Well just believe that NFTs are going to be high value. And maybe you should make a lot of these associated with your brand”. And “Don't ask too many questions. But like, let me give you a little bit of that”. Going back to regurgitation of what other people have said. Admittedly, I've edited the Web3 spaces too when I share information, I'm just like consolidating what's already readily available. I don't pretend to be a crypto expert, I don't see this crystal-clear connection between tech and crypto outside of you know, if it became this super hyper legitimized currency that maybe we would be transacting on it, like we would in many other industries. What does that mean for you? I mean, I get it, we're in a business about pitching and showing the shiny side of things. But sometimes if the connection doesn't exist, we just have to be honest about that. So I'm with you, AI, a lot of applications across industries. Admittedly, some of the applications you just mentioned Ratko, expand into more larger advertising implications. For AI and ad tech, there is going to be this legitimization around targeting data aggregation, real time betting? Is that going to change? Do you think it is going to change with this forthcoming proliferation of AI technologies?

RV: On the part of like real time bidding, that part, I'm not so sure where the AI plays a role. I think there could be a role like, like a pre-bid or even a post-bid environment, just because real time bidding is so fast—everything's going in milliseconds. I think the AI can inform perhaps some of the targeting strategies, some of the targeting methods, some of the planning. I also think it can inform and execute on the optimizations. So like looking at the reporting that's coming out of the campaign, helping to provide insights, helping even just the people who have the fingers on the keyboard that are managing the campaign, helping them generate reports, like in a fraction of the time. So one thing that I also have, like firsthand experience playing around with, and again, I'm not an AI expert, I'm an amateur that's just playing around with this stuff. You can query databases using natural language. So typically, unless somebody builds an interface for it, you have to know, like, SQL, right, to kind of make these queries of databases, but you can actually get AI to help you generate those queries. So I think there can be a huge step forward and just workflow, personal productivity, like productivity across the board; helping individuals generate reports, helping individuals or teams optimize campaigns. I just think it has the opportunity to kind of touch on so many different aspects.

NN: I think we'll hopefully see some of that showing up faster than some of these past emerging trends or themes that were supposed to come to the table. And I also say like, never say never, just because a theme that became popular in the trades that people want perspective on, it maybe didn't work the first time around, it doesn't mean that it won't eventually become important and like central to the way that we do work. But it's definitely one of those things that I think will come to fruition in a big way. 

A quick, last question for you, Ratko. Are there any other topics? Obviously, you have a lot of energy around AI, but other things that you think are, if not interesting, exceptionally important for people to be reading about right now maybe like one or two topics that people should be digging into?

RV: If we're talking about ad tech, I think one thing that is important, may not be interesting to everybody. But it's definitely important, I think, for privacy overall, like data privacy, and its impacts on the ecosystem and its impacts on the future of the ecosystem as well. And we're sort of in the thick of it right now. Like we're in the middle of things. And they're evolving very quickly. One of the things that I think also just kind of, at least for me kind of keeps things interesting about it is that it's constantly moving. There's constantly new developments. But I can also understand at the same time, it can be a little bit impenetrable, because you have this force around privacy. But it touches on technical aspects of the industry, like fundamentally how the internet works type topics, like IP addresses, cookies, and so forth. So it gets really into, like, very low levels of how the internet works, which can be very technical for a lot of people that aren't technical. So that part can be challenging. 

The other part is legal. So we've all basically become armchair lawyers because these new laws and bills and stuff come out and judgments and cases in Europe and North America, and so forth. Truly without reading regurgitated information to read the source material, it can be very dry, but at the same time, that doesn't make it unimportant. So it kind of goes back to our common thread of like, it's not easy. This stuff is just not easy but at the same time, I think the work still needs to be done.

NN: The volume of armchair attorneys that have needed to pop up in the marketing and advertising space related to data privacy is astronomical. I don't think they're being paid hourly for the labor that they're attempting to do. So it's a challenging time for people who need to study up on the topic. Now this has been great. I know Ratko I’ve said to you earlier in past conversations, you're just a person who knows a lot legitimately about so many things. So, hopefully this is a start for more conversations and maybe we'll circle back sometime soon about another topic that is of interest.

RV: Yeah, no, it was great chatting.

NN: Thanks again to Ratko Vidakovic, founder of ad tech consultancy AdProfs and editor of newsletter This Week in Ad Tech. 

Look, we're not all running a consultancy like Ratko is, but in ad tech, we're all better off empowering our capacity for discernment, especially in a sector often filled with narrowly distinguished options in new developments and trends of varied importance. 

I know it won't be easy to put all these tips into practice, but that's what consultants and educational resources are for. Feel free to sign up for Ratko’s newsletter by going to AdProfs.co, that's AdProfs.co, and you can also find more resources at the Basis Technologies Resource Center. 

That's it for this episode, more AdTech Unfiltered very soon.

After a dip in ad spend in 2020 due to COVID-19 lockdowns, digital out-of-home is back in a big way, with programmatic DOOH (pDOOH) projected to be a billion dollar category by the end of next year.

In this episode, Ian Dallimore, VP of Digital Growth and GM of Programmatic at Lamar Advertising, joins host Noor Naseer to discuss what digital and programmatic buyers should know about this channel, from misconceptions to big opportunities.

Episode Transcript

Noor Naseer: Digital out-of-home hit a rough patch with the start of the pandemic in 2020, with consumers’ usual outdoor habits pulling back dramatically. That same pullback in behavior resulted in slashed budgets, with reports of global out-of-home spending dropping by over 10% at the time. Now in 2023, out-of-home is back in full force with more ways to buy it than ever before. I spoke to Ian Dallimore, VP of Digital Growth at Lamar, about the renewed curiosity around how to incorporate the medium intermediate plans, and leverage innovations that these out-of-home placements uniquely offer. We also discussed opportunities and considerations for programmatic buyers, and how digital out-of-home is becoming an increasing priority for omnichannel planners and buyers. This episode on digital out-of-home with Ian Dallimore starts right now.

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NN: Obviously, you're an expert in the digital out-of-home space and the out-of-home space, you've been working in it for a really long time, Ian. So I feel like there has been maybe an uprising of curiosity around digital out-of-home and other things that are emerging from that space. I figured we could start off this conversation by just asking you how people have been thinking about digital out-of-home now? What kind of perspectives have you been bringing to clients that are looking to get introduced, who otherwise haven’t had familiarity?

Ian Dallimore: Yeah, and that's a great question and I'm really excited to be on. The medium has evolved. Lamar specifically has been around, we're in our 121st year, and obviously out-of-home since the days of the caveman had been around. So for us seeing that evolution, and the very beginning, it was very much around, exit here or just very much branded as the evolution has evolved. What digital out-of-home has allowed us to bring to the table is really this new way of thinking. And when I talk about a new way that was 20 years ago, when we first launched our first roadside, digital billboard, Lamar was kind of the first in that space. But very quickly, we started to say, “Okay, well, this product is a bit different from the traditional direct product, you know, what can we do with it?” So we first ingested data.

So we worked with IBM Watson to trigger creativity. We then teetered around with streaming live tweets and Instagram posts. To fast forward to today Noor, over the last 10 years, Lamar has been playing in the programmatic space. It's really allowed us to not only continue to evolve with our agency out-of-home specialist partners, which is kind of our day to day, then our local advertisers to really kind of be flexible with creative and change it out. But now, in my universe there is the ability to have impression-based buys, or outcome-based buys. So I.e. here's 50 markets. I don't want to run any time, because the pollen level is at a certain threshold. I want to run until the pollen count drops, and then the markets that don't have high pollen, I don't want to run anything. And then obviously, you can play in all sorts of weather conditions.

Then as far as the impression base in the programmatic world, we can dive deeper into this. But the short answer is, is it now allows out-of-home to live in the same world as online, mobile, social, and CTV, and really be an impression based by across all media, because as much as you and I live in this universe, none of us, including myself, woke up and I was like, “Man, I can't wait to see that ad on Instagram” “I can't wait to see that B roll on YouTube or TikTok or see that billboard.” It's just not how we're built. It's just what's our journey throughout the day, and different variations of screens impact us. And we know that dead space used to be out-of-home wasn't involved in that impression-based journey across different digital screens. So now we are.

NN: A big piece of the conversation is that it is impression based and there are no data sources or data considerations we can bring to the table that historically have not been a part of the out-of-home conversation. From the perspective of also the buyer and challenges that the media buyer faces, are there any benefits associated with the buying process that people can take advantage of?

ID: Yeah, and I love that question because so often people treat the word programmatic, when that first came out and really introduced itself to the out-of-home space, we had to be very careful—actually the topic of my team's focus this year is protecting the true integrity of programmatic or RTB real time bidding. Because it’s so easy, you're right, Noor is, “Hey, it's Friday, or today, it's four o'clock. The client just hit me with this budget. I'm an out-of-home specialists-focus. I'm not an online media buyer. Let me just log in to this platform and push through a buy.” That's great. I think that that's what's made Lamar specifically and even our friends at Out Front begin to evolve and look at, “Okay, we've solved for programmatic, we're seeing significant growth there. But that same API that we've built out with real time availability, maybe we need to start to focus on the direct side of our business.” So if it's truly more about that out-of-home specialist is more about automation then let's do that. So we've since done that, we've rolled out that product. And we'll watch that evolution. What we don't want is cannibalization of existing buys from a certain subset of agencies within the larger hold co.’s to just move over to programmatic because it's easier to do. So it really helped our industry on the back end to begin to evolve. We're really in our infancy right now.

NN: It feels that way. I know that digital out-of-home/programmatic digital out-of-home have been around for a little bit. But I think in terms of true accessibility, that's really just starting to rise. So I think some of what you just said now Ian begs this question, what's the ratio look like? There's still a lot of traditional out-of-home billboards out in the world. Then there are these now rising digital out-of-home options. What does the split look like, if you can give us some background on that?

ID: It makes up around 10% of our overall inventory compensation. But it makes up revenue wise, almost 35% of our overall revenue comes from those 4500 screens, which from a revenue perspective, that's fascinating. Now, as the evolution evolves, we, as a publisher, need to make sure we're very careful because we look at cannibalization within the marketplace as well, because there is a time and a place where both digital and static play together. Where traditional static makes more sense, programmatic, obviously, digital only makes sense.

So even within the marketplace, I get asked this question on stage a lot. It's like, “Well, are you going to transition all 325,000 screens to digital?” And the answer is quickly “No”, because of the latter response I just gave you, but it does play a role. But we're really looking to evolve in markets that maybe don't have digital or the marketplace itself is a new community pops up, a new town center pops up and really kind of focusing on okay, that's a new location, that's where people move, let's roll out a new digital 2345, etc.

NN: Reasonable to not have the plan to do a mass conversion and turn everything into digital; it makes me also think of this, which is that of course, there are going to be buyers out there who have been waiting for transition or increase in digital boards, because they're focused on digital buying. If there isn't a digital component, maybe that's not in their wheelhouse based on politics or whatever the structure of labor is in relation to media buying. Then on the flip side, I wonder for traditional buyers, whether that be businesses that work directly with Lamar or other out-of-home companies, or its full-service agencies, holding companies, whoever it is that's doing a lot of out-of-home buying, where sometimes they see it as a negative in the sense of there being a proliferation and the growth of these digital boards.

I work for a digital company, so digital always sounds good to me. But one thing that comes to mind is I'm on the highway, and I'm looking at a screen, there's an impression, and then it flips to something else. Whereas the static board stays there, it's stagnant, I can look at it for a suspended period of time. That's just one example. But is that ever a question that comes up? Are there people who prefer to only be on static billboards versus those impression-based billboards or whatever that out-of-home structure is? I wanted to get some of your perspective on how people react to that.

ID: Yeah, so obviously, digital has attracted on the programmatic side, a lot of the omnichannel DSPs. So they live in that universe, all they care about is that impression. And what you're talking about is extremely important in the out-of-home space, and it's what the medium does really well. But I'll give you a real-life example, one of my favorite brands, Gooder Sunglasses, we'll give them a shout out. They're an absolutely amazing company, but they've never utilized out-of-home. They kind of shied away from it. They liked the idea of the traditional direct and maybe doing something fun. This past summer was the first time they ever utilized digital and traditional static. So I'll kind of quickly walk you through it. So like what you guys deal with on a day to day basis, they have their audience segmentations and they have their first party data and they basically said like, “Okay, programmatically, we can overlay that first party data, and you can insert any brand that has been doing this for quite some time with Lamar on the programmatic side”. Insert X, audience segmentation, first party data, pipe that in and then here's the DMA market list. “Oh, by the way, we're going to drop a pixel on our website. We're going to do device ID pass backs to then track the effectiveness of the digital campaign”. So you have that one campaign.

Simultaneously, they took a very important market to them, which I'm being very facetious here. Their CEO is a flamingo, obviously not in real life, but his name is Carl. So we collaborated with them. And we said, “Okay, we actually have a Carl, Georgia. And in Carl, Georgia, there's a mayor. And how much fun would it be, if we did this massive build out, we gain PR, you flew your entire social team down, you did TikToks of the billboard. You even got to go into City Hall and have the mayor and the whole city of 169 people, you hand out free glasses.

So really quickly, to kind of summarize that example, if you have first party data digital very impression based, and then you're utilizing the same category out-of-home on the traditional direct side. You build out this 3D Flamingo. You introduce them to the town you integrated now in social, you also integrated in obviously PR. Those are two drastically different mediums. But it's one cohesive campaign that has used both new age technology with digital, and data and measurement, and social, and then you utilize the traditional direct sides to really just capture your attention for a while. So a long-winded way of saying, if done correctly, we see brands utilizing both.

NN: So you really launched into a pretty sophisticated example of the way that people can really bring in a lot of different data sources to the table as Gooder particularly decided to, and also leveraging the wow factor of what out-of-home brings to the table. So maybe the best of both worlds. If someone is looking to understand what those opportunities could look like, maybe they're not looking to go as big as what you're describing. But they want to bring their data into the equation, and they haven't executed in the digital out-of-home space before. How do you set them up for success? What do you ask them to share with you so that they can build a pretty sophisticated digital out-of-home plan?

ID: Yeah, we get asked actually, we had a call earlier this morning with an actual regional local client. And the short answer is, if they're like, “Hey, we really just want to do an impression-based buy. We have our audience, and we use this third-party data company.” And it's fascinating because the conversation happens pretty quickly. It's like, “Well, it's a pharma company. You know what, we have cross x data as well.” So the first question is, like, okay, what are your KPIs for your campaign? So if you want to run digital, and we see it very much like, okay, that's this is an audience impression-based target campaign, then we quickly shift you over to programmatic? The first question is, do you have a seat? And do you have a seat on a platform? And very quickly, they kind of get confused. They're like, “Wait out-of-home, seat?” And we're like, “Yeah, do you have a seat on any of the omnichannel DSPs?” And most of them even at the local level, they're like, “Well, yeah, that's how I buy CTV and all other media”.

So quickly, what we do is we understand what the KPIs are for the campaign, we understand, in that format example, what data sets are they using across other media? So if online for pharma, they're using cross x, we say, Okay, perfect. We have cross x, we are then based on the DMAs, and the markets, which is a bit different for digital, obviously, because in the digital universe, traditional digital that you guys live in, it's the impressions, it's the audience. For us, we take it another step further, and we narrow it down to “Hey, what audience are you looking to target? Okay, here's the third-party data, we have access to that as well. What markets do you want to be in? And what's your flight?” And then just like any other traditional digital media, online, mobile, social, we just build that ideal idea, and we push it towards that seed, which that right there, that conversation wouldn't happen three years ago. And that's what got the industry to where it is today, in order for us to participate and get those massive digital budgets and be a part of the consumer journey, path to purchase. The only way that you can do that is if your inventory is accessible to DSPs, whether they're omni-channels or not.

NN: What does the matching process look like in the digital out-of-home space? So just to elaborate on that question, I've got a certain number of files. Let's say I have 500,000 files, like email files or other types of data that I'm looking to pass along. It's a more complicated matching process because we're looking to go up against billboards and bus shelters. And wherever Lamar potentially has these like digital out-of-home or out-of-home opportunities. It's going to be different than trying to reach people, match it back to like people's TV screens at home or their computers. So can you tell me a little bit about the variation and what that matching process looks like?

ID: Yeah, so we're talking about MAIDs and device IDs. I tell people this all the time, and it may ruffle some feathers with some other out-of-home companies. But we're a billboard company, our job is to make the product more sophisticated. And our connections are our sweet sauce that then connects to these elaborate platforms. So I say that because it's not our job in the out-of-home space, nor should it be because it'd be a little sketchy. But when we work programmatically with these SSPs, we're working with the same companies, whether it's LiveRamp and their robust matchup platforms, all we're doing is just passing off those timestamps on when that ad plays. And then in return, our job is to pass the timestamps along to the different third-party companies that we work with, they're capturing those MAIDs, they're automatically capturing those exposed files that were exposed to that digital out-of-home. The third-party platforms are the ones that are collecting that data, whether it's LiveRamp or others, and then if it's utilized correctly, in a third-party, omni channel DSP, those files are captured. And then they're able to take those captured files and then retarget them on mobile, social, online, CTV. Again, going back, it's not the responsibility of the publisher and the out-of-home space, because that starts to become a little iffy on, “Well, how'd you get all these device IDs? Did my ad actually play?” Our job is just to verify, and then the third-party data platforms, that's their responsibility to capture.

NN: From there, I wanted to also ask you about people coming back to the digital out-of-home space. So kind of a pivot in our conversation, knowing that we were just a little over two years ago, in a world where the vast majority of people were still working from home and a lot of out-of-home buying had taken a setback. People were saying, “People aren't on the road, people aren't out in public, people have to be at home. How can we continue to justify having this on plans?” Now it's two years later. Has it been a massive comeback? In what types of industries? Is there an even stronger initiative or push for out-of-home? And are there some industries where there's been a pullback or some sort of strategic reason for why buying is just continuing to lag?

ID: Yeah, great question. I loved the fact from the publisher's media side that we were early on in programmatic whenever the pandemic hit, immediately, our numbers on March 30, started to decline, March 15, is when it went to zero on programmatic as it relates to the other side of our business. I won't go deep into that. I was excited about that. I'm like, this proves that these are not just, “Hey, we're just lazy buyers. So we're just going to buy.” It also proved that we weren't talking to the motor home specialists, these were true omnichannel DSP buys, and they shut off everything. I'm sure you guys experienced that as well. Everything was cut off, it was like, “Okay, we're going to either cut it off, or we're going to slow it down a little to nothing.” We're going to take a step back and figure out what's happening, right? Obviously, the first easy one was rightfully so, okay, assumption, no one's on the road. Everyone stayed home for two weeks. So we saw that. But what was interesting, and I love this is so often in our space, out-of-home, not on the local side, obviously, but on the national side of brands, you know, the top 250 brands, oftentimes, they're very hesitant out-of-home anyway. Or if they do spin out-of-home, it's very much like, “I have to be in New York, LA, Chicago, San Francisco, those kind of tent poles”. I've always laughed, you know, obviously, being a Baton Rouge-based company and where I am in the south here and remind me? You're in Chicago?

NN: Chicago.

ID: Perfect example. Right. So for you what the pandemic meant and looked like was massively different from what it looked like here in Baton Rouge, Texas, Florida, Arizona, where I always like to play this game because it's not about a billboard. It's not about a mobile device or CTV. Going back to the multiple screens, it's really about like, “Okay, well, what does your journey look like?” And in the pandemic situation, “What are your life patterns?” Obviously in New York, you can't have millions of people jumping on the subway so immediately, there's nobody on the subway, which means nobody's advertising on the out-front network and this subway. But we started to see these buys that they started to uptick because again they're looking at real mobility data. And they started to see like “Wait, I can't spend my money in New York, LA, Chicago because obviously there are lockdowns.” But by June, July, we started to see those budgets that typically would go to New York, LA, Chicago, and other large markets began to say like “Okay, well there's still people moving out and about, we see this with the mobility data that we're utilizing on these third-party platforms. So we started to see a shift in budgets to where typical brands that would spend in New York and LA, were starting to spend in Houston, Dallas, New Orleans, Jacksonville, Florida, Atlanta. So as these markets came online, and some of them came online quicker than others, some of them came on, turned off, leveled out.

But to answer your question, now, we really focused in and programmatic allowed us to really hone in and say like, Okay, this really is about data, it really is about who is moving out and about. But that was a tough year for out-of-home, which was really tough. Because we came out of the previous year, we were scheduled to have an epic year, the next the following year, when the pandemic hit, and we were on the rise, January, February. And then when March hit, we dropped local, we did fine, it came back pretty quick. But roadside the next year, took over 60% of programmatic revenue, where in the past, we lived around 40% of the overall revenue on these SSPs. were capturing roadside billboards, at 30/40. It hits 60, the next year, because you still had significant lockdowns. So obviously elevator networks and gyms were still locked down. So you had those networks that were down to zero and making zero money. But that budget again had to go somewhere, because they saw the mobility of data. So it leveled out. We're beyond that next year, we jump back quickly.

Overall, as a company, we did significantly well the following year. So the growth and trajectory of out-of-home spin. I think what it's done overall is it's really changed out the perception, which again, being a southern boy, I love, I always used to have to mess with our friends out in LA on the movie house this like, “Hey, by the way, people in New York, don't go to the movies. You know where they go to the movies? They live in Baton Rouge, they live in Kansas City, they live in Birmingham.” We don't just need to buy the tentpoles, we need to be very strategic on when and where to buy. And oh, by the way out-of-home has shown its flexibility that we can turn it on and off, not just because of a pandemic or the previous year, this past year was, “Hey, if we have supply chain issues, we could turn it off, we can turn it back on we can level it out.” So I think it really allowed out-of-home to shine in so many ways.

NN: Are there any resettling things that have occurred? I know you mentioned just a little while ago that it's back and maybe better than ever before. But have there been any instances in which there's been a shift in the way that the market is approaching holistically digital out-of-home or out-of-home in general?

ID: Yeah, I think over the last couple of years D2C. Before the pandemic, we started to see a handful of the Caspers of the world, the Ro, those types of companies, DSC would purchase in these larger markets and they were utilized out-of-home. I think now that they've experienced what they have in the out-of-home space, they begin to look at it out-of-home, completely different than they would have before. Before it was very much branded. So if I'm in a brand I'd rather brand where the bulk of people are aware I can get the most impressions. Also, Lamar has been doing programmatic for 10 years, but most everyone else came on board about three years ago, and really significantly with a lot of the play space screens has been the last two and a half years.

So it's interesting to watch how they can now buy traditional direct, whether they're buying digital static transit airports, or they can also buy that same exact media programmatically. So I think it's now allowed them to live in that space.

I also think that people are very particular about what type of media and what type of products in the out-of-home space that they purchase. Or in the past, they may have just been freely Licious, by all screens in the New York DMA. Now they look at it a little bit differently and kind of focus on “Okay, well, what does that product mean? How does the data now play a role?”

So we have had our moments like all media right now and all publishers, it's, are we going to be in a recession? Are we not? So we still see these like little teeters. Are we approaching a significant war that may impact? So I think now we're beginning to be treated the same way that all other media where in the past, it's just been like, well cut out-of-home because we can't measure it and we don't know its effectiveness.

NN: You just brought up measurement. And admittedly, I have a couple other questions that have come to mind given some of what you just said. But I think it's important to pivot in that direction, especially knowing that our audience is focused on the ad tech space and programmatic buying. There's a lot of energy around performance.

Now to go back to some of what you've said: There's the presumption that if we're talking about out-of-home and anybody that's working with Lamar or anybody else in the out-of-home space that people understand strategically, what is the value of this medium relative to other media types, but there are people who have been sitting on the fence. Some of those people who sit on the fence, it's because they're so accustomed to digital buying where there's this one-to-one attribution process. You see, you click, there's a lookback window. And now I can say, X volume of people has made this purchase relative to this amount of media investment. What type of conversation do you have with them if there are performance-oriented expectations?

ID: Measurement is a big component, right? So we talked about the device ID pass backs, anonymous device IDs, that allows us to be the medium that helps generate more of the campaign and have a more impactful, “Oh, wow, I saw that Travel Texas ad, people kayaking down the Red River. I want to go there.” “Oh, wow, I just got on my Instagram ad, Travel Texas, same exact creative but smaller. Click here. Wow now I got a banner ad. Now I'm on their website.” Now, what I just explained to you not only was the device ID passed back, but also, as I mentioned, we can drop in pixels.

The other way that we can measure is through exposure. And then where did that anonymous device ID end. So I was exposed to that target ad, whether I realize that or not on a roadside billboard, that device ID over the next 10 days then ended up at a target. Those are attributable to the out-of-home space. And then the last thing that we do is we work with a handful of brand lift study companies like M4 or Mira, just like in the online world where you can do brand lift studies; exposed, unexposed.

So we've really gone the extra mile to make sure like, “Okay, we understood what our limitations were in the past”. It was like, “Okay, I know, I'm buying 1.8 billion impressions over a six-week period across 25 markets.” We recognize that we said, “Okay, well, what does measurement look like in the online world? What does it look like in the mobile world? How can we help complement? How can we help amplify a campaign? But most importantly, how can we utilize that same data, the same measurement.” So that way, we become a part of the campaign because we're not blind to the fact that we're not a one-to-one medium, I believe if we wouldn't be a one-to-one medium, it'd be very awkward, right? Because if you walked past a billboard, and we were able to tap into your search, browser history, or Instagram history, envision yourself walking down Las Vegas Boulevard, and having our digital bus shelters change based on what you've searched in the last 20 minutes. That would be a very bad experience. Maybe comical to some of us. But we do understand now with data, we can be one to target, hey, I want to target a mom with two plus kids that has an affinity towards discount big box retailers and visited an MLB stadium within the last 60 days.

NN: So I was going to say I do envision that because in a lot of my presentations, if I'm just talking about innovation, the future of innovation, whether it's related to out-of-home, or maybe I'm referring to the metaverse, I'll use the Tom Cruise Minority Report example and I'm sure you bring it up in the out-of-home space all the time. Where it says like, “Do you need a new pair of pants,” whatever his name is in Minority Report. It's using presumed technology that's aligned with something that you're referring to, which is one to one. They're doing some sort of retina scan. We're presuming it's a world that we don't want to live in. Again, I assume that in the instance of someone who is approaching the out-of-home space, that there is a reasonable understanding of what out-of-home can bring to the table. You're probably doing a lot of educating too. Sometimes people are so deeply in the weeds with performance, they just figure if there's now the letter D added onto out-of-home, or now there's a programmatic opportunity. That means it must be much more precise. I think you can bring people back down to earth in understanding that maybe even if you could have that you wouldn't want to give the user experience and also privacy regulation, which is going to increasingly make that challenging, maybe more challenging than it even is today.

ID: Yeah, and I think we've all probably in the ad world have heard the story of even, you know, somewhere to out-of-home direct mail. We've all heard the story out of Target where there was a 15- or 16-year-old that was pregnant, became pregnant their parents didn't know. And obviously over the next three weeks the target was sending direct mail for Pampers diapers and formula, and it was kind of like “What the hell are we getting this for?” We're whatever, 55 plus, we're not pregnant. So even the static traditional direct mail piece was being too hyper-targeted, and that created all sorts of laws etc.

So we have to be careful because we're in people's space. So when we go to audience segmentation, the one that I just described, that happens a good bit, and we look at it as this way is yes, it's more precise towards the audience segmentation. We would rather hit “Hey, this panel during this time of day, highest indexes towards the audience that you're looking to hit Brand X, therefore we're going to bid and buy”. Obviously, it's not a one-to-one experience, but we know we want to help amplify that conversation.

The other benefit that out-of-home does to where you may get served a one-to-one ad on mobile or social is that experience in that brand interaction is only between the two of you. If I display something, programmatically, or just traditional direct digital, you may now be targeting a certain audience segmentation. But you have I guess, in the online space, it's called “Spillage” or “Overage”. You're now hitting people that maybe you thought wasn't your brand segmentation, and they see it. And that's not at all who you were targeting. But with great creativity, and great use of retargeting you were then able to pick up another consumer. That's the way that we kind of look at that space.

We have a lot of regulations, we have a lot of privacy, especially with our airport inventory. Could we use facial recognition? 100%. Have we tested it? Yes, we've tested cameras within our shelters within our airport inventory. Or it could take at, at minimum, your emotion, your ethnicity, and how your facial expressions are. But for us, there's a significant amount of privacy and impacts that we stay away from. So when we talk about brand safety, we are brand safe in the sense that even down to we have a restriction code. So if we have digital or static and other mediums that's in and around schools, churches, graveyards, we don't allow for alcohol, we don't allow for that medium. So even in the programmatic side of out-of-home, those restriction codes are built in to where you're not even able to run your ads based on those restriction codes.

So we're very much at the forefront of technology. And could the day exist when Mr. Yakamoto needs to buy a new pair of khakis? Maybe. But it definitely won't be on a roadside billboard. And it would be in a very much closed one-to-one scenario.

NN: I did want to also ask you about thinking about the funnel, if you're going after a buyer who's not digital out-of-home or out-of-home exclusive, and they're putting together a strategy and they want to figure out what my expectations should be for whatever the yield is from out-of-home or traditional programmatic or digital out-of-home, what reasonable KPIs related to the out-of-home space.

ID: Yeah, and that's the beauty of it, it varies, right? Your KPIs may be, hey, I want to hit more people that download Spotify, I think if we're the only medium that's involved; and I'm talking more on the national brand side, not local advertisers. But if I'm utilizing the only vehicle that I'm using is billboards, or airports, or transit. And that's the only medium, I think you're not going to find your outcome to be as great as it could be, it's going to do its job, it's going to drive brand awareness. Statistically, it's people that are exposed to at home.

Most recently, and the Nielsen report that we had with the AAA was 48% of consumers that are exposed to an out-of-home ad, then go onto social to check out their social page, the other stats 56% of consumers that are exposed to out-of-home, then go on to search that product on Google or make some sort of search about that product. So Noor what that does is really validates the fact that like, “Hey, if you're going to do a billboard campaign, you need to make sure that your search engine optimization is up to par.” Like we do this test. I did one last night. And I was like, well, that's a cool campaign. I went to search it on Google, literally wasn't even on the first three pages.

We do the same thing with social if you're going to push a specific brand or product, understand, and our local clients do this really well because we really advise them. Understand that over half of the people that are exposed to those billboards are then going to go to your social sites, whether it's TikTok, Instagram, Snapchat, whatever it may be, you need to make sure there's some posting or some stories or reels that are relevant to what you have currently running out-of-home. As far as KPIs, every category is different. And every strategy is different. And I think that that's what really differentiates out-of-home is creativity drives the conversation, the call to action. So you may just want to have the most beautiful portrait again, going back to travel and tourism. You may want to have the most beautiful, picturesque while you're in Chicago and we do this a lot with cruises. And it's a beautiful cruise and you're getting off the island of St. Lucia. And there's the beautiful Carnival cruise ship. And you're sitting there in the middle of a blizzard in March, that has a different impact than a mobile ad while you're sitting at home or watching a CTV ad while you're stuck at home.

So the KPIs vary but understanding that we now have the ability to measure that impact is something that in the past, we just haven't, we're just kind of like, well, we know it worked, because you have a beautiful brand. And the creative looks great. And it's hitting hundreds of thousands of people a day. I guess it's working. Those days are gone. The measurement’s there.

NN: Something else I wanted to ask you about Ian was you just mentioned making sure that there's somewhere for people to go to after they've experienced your out-of-home activation? And that may require that there is some sort of call to action. So are there recommended CTAs? People oftentimes will joke about “Make sure that people aren't trying to scan a QR code as they're driving down the highway because they'll hurt somebody, or they'll get in an accident.” But are there some best practices that you suggest in a series of different instances where someone will want to make that fast connection? Because they're not going to put in some long URL? Because they'll never remember that?

ID: Yeah, so if you asked me that question, when I first started, it would probably be even before that, but the big thing that people used to do and out-of-home, and then the general was like, “Oh, we got to put a phone number on there”. Noor we still deal with that at the local level, or like, “Well, I want to put my phone number on there.” It's like, nobody calls you anymore. So my point is, I'm glad you said no QR codes on roadside billboards. Because first off, they don't work. You know, we have clients that are like, Yeah, but I still want to do it. And I'm like, “Well, A, we restrict those because again, we want to not only be brand safe, but we also want to have a safe experience. But more importantly, go try it for yourself, just run down the street and have your daughter hold up a QR code and tell me how that works out for you just doesn't work.” But it does work on other mediums. So we do see a good bit of on transit or ports, other walkable out-of-home experiences where we encourage QR codes. So yeah, so we encourage people on the transit pedestrian stuff. If a movie has blitzes, a bus, shelter market and a certain city, then yes, we encourage QR we actually play and RFID tags, we play with the push notification abilities.

But as it relates to best practices for call to actions outside of those mediums, we live in a world today where curiosity is the most important thing. So if you have defender, and have fantastic, beautiful creative, and maybe it is contextually relevant, because you utilize data, and you have baseball bags on the back of it, and you show the rough ruggedness of the product, we're very curious humans, and we know that we have the vehicle, we have the ability to say, “Alright, perfect, that's a defender, I'm going to go search it, and I'm going to learn more about it. It's almost like you don't need a call to action, because the call to action was creative and it was that beautiful experience that you had.” So very rarely do we see certain call-to-actions.

Now we may have something simple like Travel Texas, which I love their campaign that's running, it just says “Traveltexas.com” very subtly, just to remind me, that's what it is. But for the most part, the brands tell the story themselves and out-of-home allows the experience, but it is why I go back to my point, you have to be buttoned up. You have to make sure that if you're going to have the defender creative, that when I go to that website, that giant experience may be the same creative or some variation of it. And then that's when I'm going to go do my research. I don't need you to give me the website, the handle the backslash etc. You may just have that Instagram logo with the ad handle on it just to tell me where to go.

NN: In those instances, I imagine that brands like, for example, Land Rover or Travel Texas or whatever the particular big out-of-home buyer is. They don't have an attribution expectation; meaning that they're not trying to necessarily connect back directly to that campaign, but rather, maybe they're looking for lift, like lift in website visitation, but it can't be directly connected back to that campaign, or that media type. So long as that's not a priority for them, are there, in the event that an advertiser is really concerned and they're not going to use a QR code or they want an alternative, are there ever things that are suggested that people can remember so it doesn't just boil down to them having to Google something else?

ID: Yeah, I think it depends on the notoriety of the brand itself. You know, obviously if I see the Land Rover logo, I can quickly figure it out even if I didn't know that that was a Defender. If you want to go more at the local level, yeah, that's important. But that's where the creative really shines. So simplicity of, you know, hey, if my KPI is I want to drive more people to download a certain app, then on top of the fact that I should be retargeting those consumers with an experience on the mobile device that are exposed to out-of-home, but it may simply be the Apple logo, and the Android logo, you know, download today, again, we're very savvy consumers, we've especially, during the pandemic, we've really seen this heightened attitude of like, hey, I can go out and find whatever I want, you know, the web is, is a beautiful place, social has now blown and blossomed into this organic creativity experience, I just need to have some sort of guidance, like, here's the Instagram logo, very subtle. And here's the handle to learn more.

So just start me down the path to make sure that I didn't think that that was, my wife thinks that the Ford Broncos look exactly like the Defenders. And I'm like, “They're completely different vehicles.” But what you don't want to experience is you didn't have that Land Rover logo on there, maybe you put the local Peretti, who's the Land Rover dealer if you're at the local level, to where you at least guide them. My overall point is that you don't have to have that call to action, whether you're a local, national brand. We're very intuitive, and we're very curious people. But again, it's why I'm so infatuated with the omnichannel approach is out-of-home could be that initial driver, that where you then hit them with that Spotify, push notification of like, here's the most recent country album that just dropped by music singer X.

NN: For a lot of folks that are going to be listening to this particular podcast, there is going to be curiosity around that. Attribution is so central to a lot of the ways that they're trying to prove out the value of any medium. So it's good to hear that I know, this has already been a long conversation. But I think I've been thinking about a lot of different things and have curiosity to ask about them. So to bring it back to programmatic buying or programmatic digital out-of-home. I know much earlier on in our conversation, you mentioned that, ultimately, digital is a smaller component of the much larger out-of-home footprint and that I imagined programmatic as a smaller segment of that, since then, some of that digital is going to be exclusively bought site direct through individual sales points of contact.

So in terms of what you can uniquely do programmatically, are there any things for programmatic buyers to learn about from you, that they may otherwise not know because they're not exposed to this style of buying? The simplicity of targeting the speed with which they can find markets, or any other details like that from a strategic planning and targeting perspective?

ID: Yeah, and look, we've built out a team here that, I have zero sales reps, because education is the most important thing. So the team and I spend most of our time educating the omnichannel DSPs, educating the brands directly. So we get this question a lot. And it's very much what you're doing today. For your brand, whether it's online, mobile, social, what you're doing today, we have that same ability. And not only do we have that ability, but you can do it in the same exact platform. And whoever you have your seat on.

As it relates to ability, that's something different, going back to creativity, creative is the most important thing. So we've already touched on the fact that it's massive and scale itself, you have this blank canvas that you can do so many beautiful things. Well, one of the things that we've also brought into the programmatic space that we've been doing for quite some time in the out-of-home digital side was dynamic content. So we have Bally's for the Atlanta Braves programmatically that runs live scores, so their games only begin, they only buy whenever their games begin. So obviously they're doing an impression-based audience targeting baseball enthusiasts, blah, blah, blah. But the coolest part for them is the ability to have real live scores. We touched on the weather, for example the NBA. Depending on when this launches during the playoffs, we're going to be streaming live tweets from the NBA, as well as live scores all the way down to, and this is the most basic thing that out-of-home does, because location and proximity are the most important thing.

I'm making an assumption here: a good friend of mine played for the Cubs forever. I'm a Cubs fan myself. And we have a digital network that downtown, near Wrigleyville, our creative can play content based off of real time outcomes. So Noor, you're in Chicago as you're walking around Wrigleyville, and you may be having lunch and next thing you know it's not necessarily the Cubs that are promoting or the MLB. But you may be a closet gambler and you have a certain app on your phone, and you love to bet on baseball, which I highly recommend don't ever bet on baseball. But based on your app, and based on those consumers that are walking by, you may have DraftKings. It shows you the real timelines, the betting lines during that game that's about to happen in three hours. So again, context and location are key. The last point of going to location is from a creative perspective, one of the benefits of out-of-home is what's in proximity, what's in the area. We've had campaigns such as New Balance, and others, where they're targeting over 75 to 100, different New Balance stores across so many cities, as opposed to that they're able to provide one piece of creative and dynamically based on when and where that buyer is happening. And the location of that board, when you're bidding and buying, we're passing that information back. And dynamically, the location of the store in the correct font that that creative team uses is displayed. So you have the New Balance shoe. You have available now at and then dynamically that's dropping it in.

I would say that that's probably the biggest differentiator is creative, and then the dynamic side of it. And then obviously, the ease of buying. So the ability just for us to build out a deal. Whether that's a specific deal ID for a specific PMP for a specific campaign and KPIs or very simplistic just like they do in the online and mobile space, we can just build an evergreen deal for your brand and just push it over to you. When and wherever you want to buy, whether it's Open Exchange or PMP, you don't have to contact a sales rep. So the process doesn't slow down. It's very much I'm buying in real time. And based on the measurement across all other media I ad spend; I can remove spend just the way that you can do and all of the media.

NN: I’ll wrap this question up. You've mentioned to me earlier, we've talked about this in the past that you do a lot of speaking engagements, you know, you have your own podcast. So, a part of you continuing to tour the country and have those conversations is that you must be involved in a lot of dialogue about the future of digital out-of-home and maybe programmatic digital out-of-home as well. What are you excited about that people are having conversations about as far as innovation in this realm?

ID: You know, I think if you're going to the far future, I think being a part of the driverless car itself or even driverless car for where the Teslas are moving towards and a handful of others. How does that of home then drive to that car screen? Don't freak out everybody. This would be an opt-in thing and we would work with each different vehicle. Then wearables you know, we all live in this world now where we have an Apple Watch, or we have some sort of wearable. I wear Whoop, how great would it be if you're standing next to a digital bus shelter, and it shows it knows that you burn 700 calories this morning, and then it triggers a Smoothie King ad for one of their products. That's kind of future stuff.

What excites me today is the ability to continue to educate people on the medium. Because so often, we get the conversation where it's like, “I had no idea out-of-home could be a part of my conversation.” “I had no idea that you could do device ID pass back.” The evolution of e-commerce is going to be big in the out-of-home space, not just programmatic, but the traditional direct side, that excites me. And honestly, we didn't talk about this, but AI and ChatGPT from a creative perspective. And from a rate optimization perspective, I think that that's going to be super exciting. And it's something that we're focused on. And I know the industry, half of us in one camp, half of us and the other, but again, embracing technologies and better understanding how and what it does for us, I think is imperative.

NN: I had a lot of questions over this hour for you because my mind is spinning in so many directions. I imagine for folks who haven't bought in space or have thought about it and haven't quite made the jump yet, this is a good starting place to start thinking and brainstorming more deeply. So thanks for the conversation Ian.

ID: Yeah, I love it. This was so much fun. Again, for us, our biggest hurdle is like all other medium is just evolving and educating. I'm grateful for you and the platform to do this. But this has been a lot of fun.

NN: Thanks for the time.

While many players in the advertising industry have reprioritized diversity, equity, and inclusion in the past few years, underrepresentation of historically marginalized communities in programmatic media inventory is an ongoing problem. 

President of Advertising at Group Black, Kerel Cooper, is working to change that by building a publisher collective that aggregates programmatic inventory focused on reaching Black audiences. In this episode, Kerel discusses what advertisers and marketers can do to support the advancement of the Black media ecosystem.

Episode Transcript:

Noor Naseer: 2020 was a year of colossal change for brands and advertisers, as many were finding their footing around sustainability, equity, social justice, and other topics they historically had taken less of a stance on. This social awakening impacted the digital media world by changing how brands plan their media investments, the variety of suppliers or publishers they work with, and the types of initiatives they support.

Our guest for this episode is Kerel Cooper, president of advertising at Group Black, a Black-owned media collective focused on creating a more sustainable and equitable media landscape. Kerel talks to me about what's been going on in the past few years since 2020, how brands and media buyers should be thinking about DEI when it comes to programmatic media buying, and how marketers and digital media professionals can do better as they plan to execute campaigns more inclusively. This episode with Kerel on programmatic buying with diversity and inclusion in mind starts right now.

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NN: First things first Kerel: Thanks for joining me to chat today.

Kerel Cooper: Absolutely, super excited about this conversation. I'm thrilled that we got a chance to meet in person for the first time a few months back at Ad Color. You were on my podcast two years ago, but we had actually never met in person until very recently. So that was awesome.

NN: It is very strange since I guess I met you amidst the pandemic and maybe I already knew you before. I think there is this shift in what it means to know somebody because I felt like I already knew you like I had already met you. I think that's just what living in this kind of post-pandemic world is like.

KC: Absolutely. I agree. There are so many people that I met, virtually, that I got a chance to know over the last two and a half years that meeting them for the first time in person was exciting. But it was also like we were just picking up conversations like old friends, because we've known each other for so long.

NN: I’m excited to do more of that and have some more of those conversations via the podcast as well. So I'm going to kick things off and ask you a little bit about where you work. You come from the legacy digital media and adtech space. And since then, you've moved over relatively recently to Group Black. So I'm going to frame my question specifically, because I know Group Black does a lot of different things. But can you spell out the offerings that are digital in nature, and the vital purposes they serve for brands and advertisers?

KC: Yeah, sure. So first, for those of you listening who don't know me, my name is Kerel Cooper, I'm President of Advertising at Group Black. If you're unfamiliar with Group Black, we are essentially a collective and accelerator focused on the advancement of the Black media ecosystem. And I know we'll sort of get more into what that means in this conversation. 

In terms of our specific offerings, we're in the market today with three main opportunities. First, as a media opportunity. Today we work with, like I said, a collective of about 200 Black-owned media publishers, and are representing their inventory and market. So we've essentially consolidated their inventory and offer it as a scalable media solution and market. The specific products within that include standard display, video, audio, CTV, and digital out of home. So that all sort of encompasses our media offering.

We also have a content and creators offering as well. So really working with creators and content creators who are authentically telling great stories in the marketplace, we work with them on sort of amplification of their content and connecting them with the right agencies and brands who have a strategy around content or social offering as well. The third offering is focused on events. So in 2022, we worked very closely with Essence, partnering with them on sponsorships and activations at Essence Fest and Afropunk. But as we look at 2023, Group Black will be standing up for our own events in the market. And a couple of notable events are, we'll be doing something soon around web3 and NFT's and the sort of the education around that market, as well as programming around hip hop's 50th anniversary, which happens to be this year. And again, working with brands on sponsorships and activations at those events.

NN: You might have touched on some things I am probably going to ask you about, but we'll reframe them a little bit. I also want to just clarify what is the nature of the conversation that I'm looking to have today with Kerel and there is just this inclination and just this uprising of advertisers and marketers and brands out there that are looking to put together strategies to reach Black and Brown audiences and other types of marginalized audiences. And oftentimes, they're looking to do that in programmatic adtech oriented spaces. Everyone doesn't have a full-blown strategic team or AOR in place to make those strategies come into existence, but they've been tasked with making those buys come together and come together successfully. So we'll talk more about that. But I'm going to connect back again to Kerel’s history in the adtech and digital media space. How is your background distinguishing you for the purposes of Group Black?

KC: Yeah, it's a great question. I don't know if anyone's ever asked me that question before, you made me sort of think about my career, my career journey. I've been in the adtech and martech space for over 23 years now. Fortunately, I had the opportunity to work at some great companies, some really great organizations, and have had the opportunity to do a lot of different things within my career, right, you know, I would say the first 14 years of my career were mainly spent in ad operations. And coming up through sort of the ad operations funnel and running teams there and building out adtech stacks, so on and so forth. I then moved over to LiveIntent in 2014. So moving from the publisher side of the space to the adtech platform side of the space. And from there, I made a career switch to move into account management and ran the account management organization for a couple of years before again, pivoting into leading product marketing, and then ultimately all of marketing. 

So my career in a snapshot has been across ad operations, account management, product marketing, and marketing. I think from the role that I'm in now, which consists of heading up an organization that consists of the sales team, account management and operations and insights and analytics, all of my previous experience, put me in a really good position to sort of lead an organization that covers so many different areas of revenue and operations. 

Second to that I'm super passionate about diversity, equity and inclusion, as we've talked about, you know, I run my own podcast with my cohost, Erik Requidan, that we started in 2018, which focuses on diverse individuals within media, business and technology. And I've always been involved in my company and my organization's diversity, equity and inclusion initiatives and social outreach initiatives. So if you combine my experience plus my passion around diversity, equity and inclusion and marry that with our mission and vision at Group Black, it's a really good fit for me. And I think for the company as well.

NN: To expand on that, I know you've given a little bit of background on Group Black and some of the activations or opportunities that they've stepped into some of the new things that we're anticipating for 2023. But I think a lot of people out there, who maybe they've worked in the adtech space, or programmatic media space, or just advertising in general, they're not as close as either you or I when it comes down to thinking about why it's so important to craft these more specialized organizations that are focusing on unique populations. So can you share some background to highlight why scaling Black media ownership is critical for programmatic and the digital media industry?

KC: Yeah, I mean, I think historically, Black-owned media and other diverse-owned media companies have not had the investment in them that other companies have had, or maybe that they should have had. So from that perspective, they haven't been able to have the financial resources to have the right technologies in place, or to maybe have the right media expertise on staff. And because their staffing is small, maybe they don't have the right connections at the agencies and brands to unlock more revenue. When you think of it from that perspective, that is one of the values that Group Black is providing to our collective. How do we make buying Black-owned media easier to do at scale? How do we create opportunities for our collective but also, how do we bring to them these additional areas of expertise, whether that be on the media side, the technology side, so on and so forth. 

I think when you look at the Black-media ecosystem landscape, I still feel that there's a lot of untapped sources of inventory from a programmatic perspective, because there are hundreds of local Black news organizations across the country today. But because of the lack of investment, as we just talked about, and their localized nature, a lot of them are very small. So a lot of them get overlooked by bigger brands and agencies when they're spending dollars and if we from a Group Black perspective can pull together those inventory sources, those unique small inventory sources that are untapped to create a more scalable offering, I think that that is something that a lot of agencies and brands would be willing to tap into.

NN: Absolutely. I mean, that's where there's this incredible loss on both sides, right that, like you mentioned earlier, it's that the technology hasn't been tapped into, people don't have the awareness that the opportunities exist. And even when the opportunities exist, they really need, especially if we're talking about some of the bigger brands out there, they need to be glued together with a lot of the other inventory sources that are available. 

KC: So right.

NN: Technology is key to that. So if you can also share how Group Black is helping to make Black-owned digital media companies more accessible, maybe in ways that go beyond some of what you already described in terms of like gluing some of the inventory sources together? Are there other things that are happening from a digital media perspective that you all are supporting?

KC: Yeah, I think in terms of making it more accessible, so I think it goes back to the technology piece. You know, from being in the adtech and programmatic space, connecting the pipes is so important. We love to say that in our space: “Are the pipes connected? Are we ready to do buying?” And so we've had to look at that as part of our solution for making inventory accessible, making it available, creating opportunities for maybe some of the smaller publishers who wouldn't normally have that opportunity. So opening the pipes and connecting programmatically is one thing. 

The flip side of that is marketing. I think our marketing team, our brand team has done a fantastic job in the year and a half that Group Black has been around in sort of promoting who we are, what we're doing and making sure that the marketplace knows that we exist. And within that it's not just about the Group Black brand. It's about the 200-plus publishers that are part of our collective that we are helping promote. So part of it is technology, in terms of making sure pipes are connected. The other part of it is brand marketing.

NN: Why is the adtech industry so behind when it comes to having solid sources of inventory related to Black-owned real time biddable inventory?

KC: There's a couple of reasons for that. If you think about the black media ecosystem, landscape, and Black-owned media inventory, there isn't a lot out there, there aren't a lot of Black-owned media companies. Our mission at Group Black is to dramatically transform the face of media ownership and investment. As part of who we are and what we're trying to do we are trying to address that. So the first part is there isn't a lot of Black-owned media that exists. And there's a number of reasons for that. Investment is at the top of the list, so we need to address that. 

The other side of it, I think, is the inherent way that buying has been done for so long creates some biases when it comes to Black-owned media and diverse-owned media as well. I'll give you an example. From a buying perspective there are companies that when they buy programmatically, they do keyword blocking for brand safety reasons. We've seen some examples where companies will block terms like “Black Lives Matter.” If you say you want to spend money with Black-owned media and you block a term like “Black Lives Matter,” you're automatically going to negate spending going to a lot of local news organizations, so on and so forth. “Obama” is another term that seems to get blocked as well, too. I think that that's more from a political perspective. Companies sometimes will block politics. How many years has it been since Obama's been in the White House? Most of the news today about him and about his wife and about his kids is more sort of lifestyle and educational type news. So I think going back and looking at how we buy today and making sure that the way we buy from a programmatic perspective in terms of keyword blocking, brand safety, the entire RFP process, I think is an exercise worthwhile for companies who are really serious about spending money with diverse-owned media companies.

NN: Kerel, I want to take our conversation back to what happened across the course of the pandemic, especially surrounding mid-2020. When there wasn't just an upheaval from a political standpoint, and from a social justice perspective, it definitely bled right into agency life and advertising and adtech culture of there being these proclamations of dedicating dollars and media investment to Black-owned businesses and Black-owned causes and things that we should be seeing the impact of. I wanted to ask you more about that. I imagine Group Black has a lot of visibility into whether or not that investment is actually occurring. So I just wanted to ask you a little bit about how those pledges and that commitment are coming along for advertisers and brands.

KC: Yeah, I think if you look at it on a case-by-case basis, some companies are doing better than others with their commitments, right. To your point, we speak to a lot of brands and agencies that have pledged to spend hundreds of millions of dollars supporting Black-owned media companies, supporting diverse-owned media companies, right. Obviously, I'm not going to get into the point of naming names or anything like that. But some are doing better than others. From a sales perspective it's our job at Group Black to continue to educate the market. From a sales perspective, it's our job to continue to show the power of running with diverse-owned media, Black-owned media. And that's the job that we're doing. We're making some headway there. But to answer your question, some are doing better than others. 

NN: To the extent that you want to comment on this, I know, it's kind of a tricky question, what do you think is holding some of those organizations back? Are there legitimate reasons? Do they not understand the complexities, or is putting together the plans more challenging than they were anticipating? Can you share a little bit about what some of the general rationale might be?

KC: Yeah, I think you named some of the reasoning behind that. I think that there, maybe there were a little bit more complexities than some had anticipated. Some folks put out headlines a couple years ago, but they didn't really have any real intention of doing anything there. Right. And again, I think that's a small part. I want to make sure I'm not generalizing because I think a lot of, pretty much all, of the partners that we work with today are serious about their commitments. But it's more about making sure that they understand the complexities, we help them navigate some of that. And then also on our side, and I think we've done a good job of this over the last year or so is making sure that we've got the right product offering for the brands that want to spend dollars. At the end of the day, we're still running a business. So brands and agencies need to hit specific KPIs. So we need to make sure that we're delivering the right products and services, which I believe we are today.

NN: You mentioned that there are a lot of advertisers out there that are standing firm with their commitment. And those are the types of folks that you are looking to partner with, to elaborate on the types of clients that seek to partner with your organization.

KC: Over the course of the year and a half we've been in business, we've seen all different types of partners come our way, large publishers, mid publishers, and very small publishers. I think a couple of things stand out that are consistent across the board. One, publishers have inventory that they want to offer up and be a part of what we're doing. Two, they share very similar beliefs and values that we share at Group Black and want to be a part of this sort of movement that we've created. I think all of those exist with that sort of common thread across a lot of the collective members that we work with today.

NN: Where is the typical brand or agency behind when it comes to developing a thoughtful programmatic strategy to reach Black audiences?

KC: That's an interesting question in terms of behind, I think it goes back to what I was saying earlier about really looking at your buying tactics. Obviously, you're going to come up with the goals of your campaigns, you're going to come up with your KPIs for what you want to do. But do your buying tactics negate you from getting there and create more challenges and hurdles for you getting there? Right, like looking at your keyword list, looking at the domains that you're running on? I think that is an area where I still think from a programmatic perspective, there needs to be a reset and a little bit more sort of digging into and investigating.

NN: Yeah, I think I also asked the question because I think from the perspective of a buyer and I know you haven't been in a media planner, per se, role for a minute now, Kerel. When I think about the question, I think about somebody, in the event that you are just not knowledgeable about the type of inventory sources that you're looking to ideally source from, what are you turning to? You’re trying to turn to Comscore? Are you trying to turn to your neighbor in the workplace to ask you what types of suppliers or sources you should be turning to? Maybe everybody's turning to the one singular supplier, and I feel like that's definitely a hang up to saying, like, “We're not pulling from a diversified enough source.” Then also to your earlier point, there's only so much you can source from to begin with, and that's a part of what you guys are focusing on too. It's the short-term, but it's also the long-term strategy.

KC: Exactly, yeah, there's only so many places you can source from. And I think that if we don't operate the largest programmatic offering of Black-owned media, we are certainly towards the top of the list there. So from that perspective, I think we've done a good job of pulling together as much inventory out there as we can. We're always looking for more, we have a team that is dedicated to finding more sources of inventory that fit into what we're doing and trying to accomplish as Group Black.

NN: If there are brands or media buyers out there listening now, and they're thinking about their strategies and that they want to be doing better, what type of advice would you offer to them as far as embarking on a more thoughtful strategy to reach Black audiences across digital media platforms in 2023?

KC: Yeah, whenever anyone asked me about the question around advice for how people can do better, I think the first thing is figuring out where you're at in the process today, and why you actually haven't done better up until this point, looking internally and understanding what's held you back or stopped you from doing better up until this point, I think, is super important. That's the first thing.

Two, I think reaching out to suppliers, like Group Black, we're happy to chat with anyone out there that wants to talk about best practices for targeting Black-owned media, the best practices around targeting African American audiences as well. We can guide you and help you from that perspective, to accomplish your goals. Again, from our perspective, yes, programmatic and the digital media offering is important to what we do, but it's not the only thing we do. So if you want to spend dollars with Black-owned media, if you want to reach diverse audiences, we can help you really with an integrated approach, reaching your audience at scale.

NN: What are big goals you have your sights set on when it comes to reaching Black consumers and leveraging Black-owned programmatic sources?

KC: Yeah, I think first and foremost is continuing to drive scale. You know this just as well as I do. What marketers are always looking for is scale and performance. So continuing to drive that I think is super important for us to share. Continuing to educate the market, on who we are, what we do, best practices for buying Black-owned media, diverse owned media through us is important. And really looking at sort of larger, more integrated campaigns, as I mentioned a moment ago, I think is important for us as well, too. We feel like we have really an offer for any marketer that's out there that wants to work with diverse-owned media.

NN: I am feeling optimistic about the future, you know, just even seeing Group Black at Ad Color and so many of the initiatives that you're supporting and having this conversation now, it makes me feel good about what's to come because it is also a long journey. 

KC: It is.

NN: You’ve made the serious commitment of leaving a former organization to become the president of a new one and keep things moving forward. So excited about the things that are coming next at Group Black and what you have coming next personally Kerel.

KC: Thanks, I appreciate it. We are excited about the year ahead we're going to continue to keep pushing our message in the market and doing the right things because if we succeed at what we're trying to do, which we will, it will have an impact from a social perspective for generations to come. 

NN: Great. Looking forward to it. Thanks for the time, Kerel.

KC: Thank you. Appreciate it.

NN: Thanks to Kerel Cooper, President of Advertising at Group Black, for discussing the cross section between digital media buying and executing campaigns that better represent the diverse world we live in. There's going to be some uphill climbing required to see the type of change that organizations like Group Black are working towards. But the adtech industry is better off when we can all more effectively reach the audiences we seek to engage with. Kerel also has a great podcast where he features interviews with leaders of diverse backgrounds across the business, media and tech landscape called Minority Report. Find it on Apple Podcasts, Spotify, or wherever you listen. And while you're doing that, give more episodes of this podcast to listen and feel free to subscribe. I'm Noor Naseer, more AdTech Unfiltered coming up real soon.

For nearly two decades, brands and businesses across industries have relied on third-party cookies to generate billions of dollars of ad revenue. From selling products to driving college enrollment to collecting political donations, this small but mighty identifier made tracking and identifying specific audiences pretty easy. With cookies now expected to expire in 2024 and with 80% of advertisers still dependent on them, today’s marketer faces an identity crisis and is desperately trying to figure out what to do next.

At SXSW 2023, Basis Technologies' VP of Media Innovations + Technology, Noor Naseer, broke down everything we need to know—and what we need to do now—about an evolved web ecosystem that is increasingly privacy-centric while also expecting brands to reaching audiences with precision.

Not able to make it to make it to Austin this year? Never fear! We're here. Click below to watch a recording of Noor's presentation:

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Want to dive further into the presentation and gain in-depth analysis of digital advertising's cookieless future? Click here to download slides from Noor’s talk, full of takeaways you can apply to your campaigns, plus a free copy of our guide “Beyond Third-Party Cookies: Your Guide to Overcoming the Identity Crisis.”

Noor Naseer is VP of Media Innovations & Technology at Basis Technologies. Her presentation earlier this month at SXSW 2023 explored a question at the forefront of many advertisers’ minds: Will data privacy kill advertising?

Here, Noor offers a framework for what advertising teams can do today to set themselves up for success in a privacy-focused future.

The State of Data Privacy Today

Scroll through any major news site, and it’s clear that data privacy in advertising is a burning topic. The last few years have ushered in a staggering amount of privacy-focused regulation and legislation, and regulators are cracking down on holding companies accountable to these new standards. At the same time, more and more consumers are concerned about data privacy—86% of US consumers, to be precise—and people today have greater control over how companies use and share their personal information. Couple these factors with the impending deprecation of third-party cookies in Google Chrome, and it’s no surprise that advertisers are concerned about the future.

The question on everyone’s mind is this: How can marketers connect with consumers in a way that’s scalable, personalized, and privacy-friendly?

The most important thing to know is that the right approach will look different for everyone. Even more, it will involve a massive investigative undertaking to figure out what solution (or combination of solutions) works best for your target audiences and your marketing team. As of yet, there’s no one-size-fits-all replacement that advertisers can employ in place of third-party cookies. And, though it might be tempting to wait around for someone to come up with such a solution, those who choose progress over procrastination when exploring privacy-friendly solutions will come out on top.    

Reaching Consumers in a Privacy-Friendly Way

As I explored earlier, consumers are demanding increased privacy when it comes to their data. But, they still want personalized experiences with the brands they’re interacting with. One recent report found that 73% of all consumers say they expect companies to understand their unique needs, and more than half say they expect all offers to be personalized.

Without third-party cookies, what’s a marketing team to do?

First, teams should develop a healthy appreciation that this is a complex shift and there will likely be a margin of difference between the third-party cookie targeting of the past and the cookieless solutions of the present.    

Then, teams should embrace this opportunity to experiment and test available alternative solutions. The reality is that not every solution is right for every brand or company. Without testing what’s available, it will be difficult to determine what will work best for your unique team and audience.

Here are some of the solutions that digital advertisers can explore and test—whether alone or in concert with one another—as they adapt to the data privacy demands of today:  

First-Party Data

As advertisers move beyond third-party cookies, first-party data will become increasingly important. Since this is data that consumers willingly give to brands, it is inherently privacy-friendly. And, because it comes directly from users, it is both high-quality and accurate.  

For advertisers looking to make the most of their first-party data, here are a few questions to consider:

• What data are you already collecting?
• What proposition(s) do you want to make to your target audience that you would need to collect data for?
• How can you ensure you’re using first-party data to create meaningful experiences so that users see the value in sharing their data?

Contextual Targeting

There’s a reason that contextual targeting is having a moment in digital advertising: It’s a privacy-friendly solution that’s both time-tested and cost-efficient. Contextual advertising works by allowing advertisers to place their ads in contextually relevant environments. For example, a bakeware brand could use contextual targeting to place display ads alongside recipes on a website, or a snack food company could target their ads to digital out-of-home (DOOH) screens at gas station pumps to entice hungry travelers.

Geotargeting

Though it still relies on some user data for personalization, geotargeting is an accessible targeting solution that is more privacy-friendly than cookie-based IDs. Advertisers can harness the power of geotargeting and location targeting to reach audiences at the right time, in the right way, and with the right message. And via targeting by country, city, or even zip code, advertisers can utilize available information about specific locations—such as language, food, weather, and local landmarks—to create personalized ads for users in those areas.

Artificial Intelligence

Recent advancements in machine learning and artificial intelligence (AI) present additional opportunities for privacy-friendly targeting. Take, for instance, Basis’ integration with TransUnion Audience Platform (TAP). TAP’s technology allows advertisers to pair their first-party data with TAP’s audience pool (which covers 99% of the US population). Through machine learning, that first-party data can then be enhanced with more data points across a variety of categories to create holistic consumer profiles for more personalized messaging and targeting. Similar to geotargeting, AI does rely upon some personal user data and, as such, will be worth examining and evaluating as it continues to develop.

Next Steps: The Privacy-Friendly Present

It’s clear that the digital advertising landscape is undergoing a significant shift, with the push for increased data privacy at its center. And while it’s true that we have a little time before the loss of third-party cookies in Chrome, it’s imperative that marketing teams use that time wisely.

How? My recommendation is to start testing some of the privacy-friendly options discussed above as soon as possible. In doing so, you’ll be on your way to determining the unique combination of cookie alternatives that works best for your brand(s) and your audiences.

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Want to learn more about how your team can overcome the challenges posed by data privacy? Check out our guide, Beyond Third-Party Cookies, where we do a deeper dive on how advertisers can overcome the identity crisis.