Google’s AI Overviews (AIOs) are quickly reshaping search marketing and advertising. As AIO prevalence grows, early data reveal effects on both organic and paid media performance. And while AIOs are still fairly new and studies on their impact are preliminary, these findings provide meaningful insights for search advertisers looking to adapt their strategies.
Since Google introduced AIOs, their prevalence has varied.
When AIOs came out in May 2024, they appeared in about 10% of all Google search queries. Since then, their appearance rate has fluctuated, dropping to a low of 7% in August 2024, but has generally increased. By late February 2025, AIOs appeared in 17% of all Google search queries.
While the prevalence of AIOs is generally increasing, it varies based on the search vertical. The industries most likely to surface AIOs have fluctuated over time, but searches related to healthcare, B2B technology, and education have had some of the highest likelihoods to date. AIO prevalence also depends on the type of query, with research finding that informational queries—specifically, searches starting with the words “what,” why,” and “how”—trigger the vast majority of AIOs, as opposed to navigational, commercial, or transactional queries. Search queries made up of four or more words were also 31.6% more likely to trigger AIO results. This is likely why queries related to healthcare, B2B, and education are more likely to surface AIOs, as many of these searches are informational.
Since the rollout of AIOs, studies have observed a general decrease in organic traffic for publishers.
A 2023 study on the effects of AIOs (then known as Search Generative Experience) across 23 websites found that organic traffic declined by 18% to 64%. A September 2024 study found that organic traffic declined by about 70% when AIOs were present in search results. Interestingly, that same 2024 study also found that links included as AIO sources saw incremental increases in organic click-through rate (CTR) compared to links not cited in AIOs (1.08% vs. 0.6%, respectively). More recently, an April 2025 study found that search results featuring an AI Overview were associated with a 34.5% lower average click-through rate.
Representatives at Google and Bing have claimed that advertisers are getting higher-quality clicks on searches that surface AIOs, since those users get a sneak peek at the page content before clicking. However, as only a few websites are linked in an AIO, only that small number are receiving those higher quality clicks.
Knowing that Google’s AIOs are driving a drop in CTR—as well as allowing more relevant (but often lesser ranked) listings to drive answers—marketing teams may want to develop a separate SEO strategy for appearing in AIOs. The strategy should focus on optimizing content, not just so that it appears as a direct answer to searchers’ inquiries, but in a way that addresses potential follow-up questions while offering context, rationale, and detailed information about the products or services being promoted.
AIOs are affecting paid click-through rates (CTRs) and cost per click (CPC) in much the same way they’re impacting organic traffic: adversely. Ads within AIOs are currently limited to mobile, and placements running on Google Search or Shopping are automatically included—although there’s currently no way to tell how often a brand’s ads are showing in AIOs without a third-party tool such as ZipTie.dev.
A September 2024 study found that AI Overviews in search results led to a sharp decrease in paid ad click-through rates: When an AIO was present, the average paid CTR was 9.87% CTR, compared to 21.27% CTR when an AIO wasn’t present. And as advertisers try to maintain their impression and click volumes in reaction to this shift, CPCs on the queries and keywords that trigger AIOs will increase in turn.
In light of this, advertisers seeking lower CTRs should prioritize conversions over preserving impression share on keywords and queries likely to trigger AIOs. Some of the recent CPC increases tied to AIOs are being driven by efforts to maintain impression volume by raising bids. Focusing on conversions ensures that ad spend is tied to tangible outcomes, rather than being inflated by efforts to maintain visibility.
From a CPC perspective, advertisers can mitigate this impact by focusing bidding strategies on conversion-based goals, like ROAS and CPA, to control the potential costs. If an AIO is present, it will often make sense for advertisers not to try to bid up on that search. While the brand may lose that click, there’s a good chance it wouldn’t have been a high-value click—for example, if the user was solely looking for a definition or doing homework.
The impact of AIOs is still developing in real-time, but early indicators suggest a clear need for strategic adaptation. By developing a strategy for appearing in AIOs—if, of course, it makes sense for the specific keyword/query and brand—as well as focusing on conversion-based goals, advertisers can better navigate shifting user behavior and manage rising CPCs in an evolving search landscape.
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Looking for more insights around how AI is transforming the search landscape? Check out AI and the Future of Search Engine Marketing for a deep dive into how AI is changing search behavior, fragmenting the search market, and impacting paid advertising opportunities.
When it comes to media plans, one of the most engaged digital ecosystems is often overlooked.
With billions of players across the globe, and particularly strong traction with younger audiences, the in-game advertising opportunity is a massive one—yet it’s still flying under the radar for many media buyers. By incorporating gaming within a holistic media mix and treating it as more than just an entertainment channel, advertising teams can both connect with audiences today and build momentum with up-and-coming generations.
Gaming offers broad reach with engaged audiences across generations. In 2025, approximately 57% of the US population is a digital gamer—with penetration being highest among Gen Z—and average time spent with digital gaming by gamers will reach one hour and 48 minutes per day. Unlike more passive media formats, gaming usually requires players to be actively engaged, offering advertisers a chance to connect in high-attention moments that drive higher brand recall.
However, ad spend on the channel accounts for just 5% of digital advertising budgets, and ad investment still trails significantly behind other digital channels. This disconnect presents a clear opportunity for advertisers: less competition, more share of voice, and greater impact for those willing to invest.
Though gaming spans all age groups, it’s especially embedded in the lives of younger generations. Gen Z holds the highest rate of adoption, with nearly three-quarters forecasted to be digital gamers by 2027. Early indications show that Gen Alpha is also deeply invested in gaming, with 70% gaming four to five times per week. For these younger audiences, gaming is more than a pastime—it’s a social hub and a space to build community.
Reaching younger generations when and where they spend their time is critical, especially as their influence grows. Gen Z is projected to hold $12 trillion in spending power by 2030, while Gen Alpha already drives $300 billion in spending power through parental influence. For brands, building connections and fostering trust now will unlock long-term value.
Gamers aren’t just deeply engaged in gameplay—they’re highly active across the broader media landscape. In fact, weekly gamers are heavier media consumers than the global average and are more likely to engage with all major media types, especially video, streaming music, and social media.
This makes them prime audiences for omnichannel strategies. As digital natives, younger consumers move seamlessly between screens, platforms, and content types throughout the day. Since so many are also digital gamers, in-game advertising can serve as a natural and impactful touchpoint.
For instance, advertisers could reach a Gen Z gamer through in-game product placement, reinforce the message with a podcast ad, and drive conversion through a follow-up video ad on TikTok, YouTube, or another social media platform. With gaming as a core touchpoint, brands and advertisers can create cohesive, multichannel experiences that meet young audiences across multiple platforms and moments of influence.
For Gen Alpha, gaming isn’t just about entertainment. It’s where they socialize, learn, and build community. Where game enthusiasts in general still spend more time on social media than on gaming, Gen Alpha game enthusiasts spend more time on gaming than on social media. And according to the IAB UK, gaming is expected to become a core part of Gen Alpha’s daily life by 2030, much like social media is for Gen Z today.
For advertisers, adapting to this shift is critical. Brands looking to engage with Gen Alpha should treat gaming as a primary channel, rather than an afterthought. That means developing strategies that show up authentically in-game, aligning with the social dynamics of these platforms, and extending engagement across other digital touchpoints.
Gaming delivers scale, attention, and engagement for advertisers, but it remains underrepresented in ad budgets. Gamers, especially younger ones, aren’t just playing: They’re building community, engaging across platforms, and influencing digital culture. For advertisers, then, gaming presents a unique opportunity that bridges generations, powers omnichannel strategies, and offers a rare chance to build authentic connections in digital spaces that aren’t yet saturated.
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Looking for more insights about how to connect with Gen Alpha as they grow into the next generation of consumers? In Gen Alpha: Online Habits and Media Preferences by the Numbers, we dive into their online behaviors today and what brands need to know to engage them in the future.
The TV upfronts may still be a fixture in the industry calendar, but their influence is shrinking. As streaming viewership continues to rise and more households opt for connected TV (CTV) over traditional channels, advertisers are shifting dollars away from fixed linear commitments. Even more, they’re gravitating towards the reach, efficiency, and flexibility offered by programmatic buying. The clear new winner in this evolving landscape? Programmatic connected TV.
Total CTV ad spending is projected to grow 16.8% in 2025, reaching $33.48 billion (though that growth could become stagnant this year due to tariffs set in place by the Trump Administration). And within that growth, programmatic CTV is a particularly dominant force: More than 90% of both display and video ad spending on CTV will be transacted programmatically in 2025. This shift reflects how advertisers are increasingly embracing ad-supported streaming environments and dynamic, data-driven buying models.
“The biggest change to the way that brands are approaching TV buying now is the flexibility,” says Christina Fortuna, Director of Media Investment at Basis. “With the upfronts, brands used to have to commit a large part of their budget to linear placements early on. With programmatic CTV, they can pivot quickly, adjusting strategy as they go or reacting to market changes in real time.”
In today’s landscape, TV is no longer a locked-in, ‘set it and forget it’ buy. Programmatic CTV puts advertisers in control, with the flexibility to pivot, optimize, and scale on demand. By leaning into this flexibility, leveraging AI, prioritizing brand safety, and embracing new measurement solutions, teams can maximize the programmatic connected TV advertising opportunity in 2025 and beyond.
As programmatic CTV continues to evolve, artificial intelligence is pushing rapid innovation in the space. “While AI has long powered programmatic advertising, recent advancements are enhancing its impact on programmatic CTV specifically,” says Fortuna. “It’s not only driving improved efficiency in both bidding and optimization, but also in contextual targeting and relevancy.”
Historically, the metadata associated with programming on streaming TV has been very broad. Advertisers could see the genre of a TV show, but couldn’t tell if the sentiment was more serious or comedic. “Recent advances in AI are allowing teams to dig deeper into the metadata, providing richer insights around episodes, specific topics mentioned within a show, and visual scenes within the frame. AI is giving advertisers a broader range of contextual targeting within the programmatic CTV space, allowing ads to be more personalized and relevant,” says Fortuna.
For example, providers like IRIS.TV now enable the use of AI-enriched segmenting on programmatic CTV inventory based on the content’s actual context, helping advertisers serve ads that align more precisely with what viewers are watching. And this precision matters: One study found that consumers pay nearly four times more attention to ads that are hyper-relevant to the content on screen. And compared to standard demographic-based targeting, AI-powered contextual ads delivered 300% higher aided brand recall and twice the unaided brand recall.
Additionally, solutions like Peer39 now offer more granular content-level reporting that goes beyond identifying just the app where the ad appeared. “For instance, a programmatic media buyer who previously saw only a broad category like ‘Sports’ in their reports can now access deeper insights—such as the specific sport being played, the teams involved, and even the location of the game,” says Fortuna. This more specific reporting can help teams optimize their programmatic CTV placements and maximize their spending.
As programmatic CTV continues to mature, so too do the tools and strategies available to protect brand safety. This is especially critical in the programmatic space, where automated buying at scale introduces new complexities and potential risks around ad placement. Considering this, the same AI-powered contextual targeting that allows brands to reach audiences with greater precision can support brand safety by empowering greater control over where ads are placed and what types of content they appear alongside.
Focusing on premium programmatic inventory also gives advertisers more control over where their CTV ads appear, making them all the more relevant and impactful for audiences. “In 2025, we’re seeing an increase in activity in the custom PMP space for programmatic CTV buys,” says Fortuna. “Advertisers are refining their inventory sources for programmatic buys to create curated, approved inventory lists—for example, teams can work with supply-side providers (SSPs) to include or exclude certain publishers or verticals based on a client’s specific needs.”
The key? Partner with platforms that work closely with their SSPs to ensure a clean, trusted inventory pool.
Accurate measurement and attribution have long been a challenge in the programmatic CTV space, but providers and measurement partners have made some significant strides to address these gaps.
“Before, we were backed into metrics like reach or completion rate, which don’t tell the full story,” Fortuna says. “With so many brands relying on last-touch attribution models, CTV rarely got credit—it would be search or social instead. That created a feedback loop for investment. But with more sophisticated measurement solutions available, it’s easier to demonstrate the full value of programmatic CTV.”
Some partners now offer QR code integrations to track programmatic CTV impact, while others have expanded their offerings to include outcome-based metrics like incremental lift, brand lift, and brand sentiment. Ultimately, maximizing programmatic CTV measurement in 2025 comes down to choosing the right partners and evaluating which metrics align with campaign goals. With better visibility into impact, advertisers can optimize with confidence, prove the value of programmatic CTV investment, and unlock the full potential of the channel.
Programmatic CTV offers advertisers the big screen, lean-in viewing of traditional linear TV as well as the flexibility, precision, and real-time optimization inherent to programmatic technology. By leveraging advancements in AI-driven contextual targeting and reporting, implementing a strong brand safety plan, and embracing new measurement solutions, advertisers can make the most of programmatic CTV advertising.
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Looking for even more insights on the state of CTV advertising in 2025? In our recent webinar, Mastering CTV: Strategies to Maximize Impact in 2025, Comscore’s Becca Marco joins Basis’ Noor Naseer to break down the latest trends, evolutions, and strategies to help advertisers maximize the channel in 2025 and beyond.
AI is swiftly transforming the search landscape.
As generative AI reshapes the user experience on search giants like Google and Bing and AI-powered chatbots like ChatGPT and Perplexity gain traction with consumers, advertisers are preparing for a search landscape whose future looks markedly different than its past.
Although Google still dominates the market, early signs of fragmentation are emerging. Last year, Google’s market share dropped below 90% for the first time since 2015. While much of that volume went to established competitors like Bing, Yandex, and Yahoo, newer AI search agents are gaining ground as well, with Gartner predicting that traditional search engine volume will decline by 25% by 2026 due to chatbot-like applications. Gen AI pioneer ChatGPT is projected to claim 1% of search market share this year, and OpenAI’s SearchGPT—which is currently in beta—could further challenge Google’s supremacy.
Future fragmentation aside, the shift towards conversational interfaces on traditional search engines is already impacting organic traffic and advertising opportunities, leaving media teams questioning how to adapt. To succeed in today’s evolving search landscape and ready themselves for success in the future of search engine marketing, advertising leaders must understand how AI is reshaping user behavior and take proactive measures to evolve how their search teams operate.
AI is driving a fundamental change in how consumers search online. Historically, people have used keywords to search (ex. “Miami beachside hotel.”) But AI is spurring a shift from keyword searching to natural language conversations (ex. "Can you find me a beachside hotel in Miami with vacancy on May 23rd?”) This can be seen with the growing popularity of AI agents like ChatGPT and Perplexity, as well as in traditional search engines with features like Google’s AI overviews (AIOs).
The shift towards conversational interactions could also lead to a larger focus on voice search. Google appears to be embracing the possibility, with a recent update to its Gemini tool that allows users to engage with AI much like they would with another person—similar to how Iron Man talks to Jarvis in the Marvel movies. Manus, an AI agent that recently went viral, is another AI agent that offers advanced conversational voice interactivity, and OpenAI has offered an Advanced Voice Mode since Q3 2024.
As consumer adoption of generative AI increases in the coming years—and competition among companies providing AI-powered chatbots rises—the overall search market will likely grow increasingly fragmented. While we’ll eventually see a decline in the use of traditional search engines, we’ll likely also see a net positive engagement with generative AI-powered search engine-like queries.
Currently, the biggest AI-related change that marketers are seeing with their search performance is a drop in organic traffic from Google and other traditional search engines. Industry experts predict that AIOs could result in as much as a 60% decrease in organic traffic, and an April 2025 study found that search results featuring an AI Overview were associated with a 34.5% lower average clickthrough rate (CTR).
While Google could work to mitigate the drop off in organic traffic with future updates, the current outlook has advertisers and businesses concerned. Earlier this year, education technology company Chegg filed a lawsuit against Google, claiming that AIOs have negatively impacted the company’s traffic and revenue.
AIOs are also making brands feel like they have fewer avenues for effectively leveraging search advertising (at least for the time being). This change might push advertisers to invest more in programmatic, video, and other non-search channels.
In my conversations with brand and agency leaders, I’ve heard an equal amount of fear and excitement around how AI will change both the search landscape and digital advertising as a whole. Ensuring teams grow their AI expertise and increase their familiarity with these new tools is one way organizations can prepare for—and adapt to—the coming changes.
Marketing teams should use AI-powered targeting to continuously test and learn what resonates with target audiences in today’s evolving search environment. This tactic is growing even more important in the context of signal loss, offering a privacy-friendly way to reach target audiences on search platforms like Google and Bing, while simultaneously giving media teams hands-on experience with the machine learning-based systems that are increasingly shaping search. By leaning into these tools now, teams can build the agility and expertise they’ll need to stay competitive as search becomes increasingly AI-driven.
Nearly all (97.7%) advertising agencies are using generative AI today, with 38.6% of agency professionals using it daily and over 90% using it at least weekly. To make the most of the technology, marketing teams should actively experiment with various generative AI tools to better understand how and where they can make the campaign process more efficient and data driven.
At the same time, AI comes with risks such as inaccuracies and bias, and leaders must make sure to put the proper guardrails in place to minimize risk—particularly when it comes to generating creative content and analyzing consumer data.
Google’s Performance Max (PMax) is one of the most prominent examples of how AI is shaping the future of advertising, particularly when it comes to using generative AI to create ads. For instance, within PMax, an advertiser can upload a picture of their product and tell PMax to generate an image of that product on a beach at sunset. PMax will then spit out four variations of that basic image for use in an ensuing campaign. There are some enormous time- and cost-efficiency benefits to this: Advertisers can cut thousands of dollars that would typically be spent on production and go to market much more quickly. They can even download that asset and use it on other channels for greater creative continuity.
While advertisers may not love the levels of control and transparency offered by PMax, using it to test and learn will help marketing teams gain expertise with AI-driven systems and better understand their benefits and drawbacks.
The shift to AI overviews and resulting decline in organic traffic doesn’t mean that brands should deprioritize their SEO efforts. Brands that continue to invest in SEO will be better positioned to have their content featured as a source in Google’s AI overviews, which often include clickable links that drive traffic back to a brand’s site.
However, knowing that Google’s AIOs are driving a drop in clickthrough rate, as well as allowing more relevant—but often lesser ranked—listings to drive answers, marketing teams should also develop a separate strategy for appearing in AIOs. This strategy should focus on optimizing content not just to appear as a direct answer, but also to address potential follow-up questions and offer context, rationale, and detailed information about the products or services being promoted.
One of the greatest benefits that AI offers advertisers is its ability to quickly process and analyze huge amounts of data. As the technology develops, data-related insights will become more widely available, and businesses will need the infrastructure and the know-how to use those insights effectively.
Data-driven cultures prioritize using data to guide decision-making—and invest time, energy, and money into the people, processes, and tools that make it possible. For leaders, this might mean improving data quality and consolidation workflows, conducting audits of all existing data sources (e.g., social media, website analytics, customer surveys, etc.), or investing in a CDP to better capitalize on first-party data.
By investing in AI-powered tools, data-facing teams will be able to generate new insights, improve accuracy, and automate tasks. And because they’ll be using AI for data-related tasks, teams will likely grow increasingly comfortable with these kinds of tools, which will make it easier for organizations to leverage additional AI-powered solutions as they emerge.
With 67% of marketing and business professionals reporting that a lack of education and training is the top barrier to AI adoption, it’s clear that empowering teams with continuing AI education should be a priority for leaders. This is especially true given how rapidly AI is evolving, and how quickly new tools are coming to market. By partnering with vendors or consultants for tailored workshops, creating AI-focused knowledge-sharing forums, and investing in training and education platforms, advertising leaders can grow teams whose AI expertise gives them an edge over their competitors. Advertising leaders should also work to upskill their teams by prioritizing AI-related skills when hiring new employees.
Lastly, leaders should aim to stay on top of news related to how search engines are changing, monitor what new AI-driven advertising opportunities are available, and pay attention to what successes and failures their peers are having with artificial intelligence tools.
In particular, leaders must stay attuned to the potential challenges and pitfalls posed by artificial intelligence. 100% of marketers agree that generative AI presents a brand safety and misinformation risk. A hallucinating AI chatbot, for example, can make up fake “facts” and generate misinformation that can be difficult for content moderation tools to spot, and the resulting content can represent a threat to brand safety.
There are also many unanswered questions related to AI-generated content and copyright infringement—from the legality of chatbots being trained on unlicensed content, to questions around who owns AI-generated media. In the short term, be sure to keep an eye on how the regulatory landscape develops. While we don’t know exactly how governments will legislate the use of these technologies, it’s all but certain that they will eventually take regulatory action, and staying updated on those developments will be critical.
The quickly evolving search landscape asks a lot of marketing and advertising leaders. Advertisers will need to get comfortable with being uncomfortable in the coming years as artificial intelligence moves the industry towards an uncertain future. Teams that use AI to test and learn, grow data driven cultures, and stay learning will have a leg up on those who are less proactive about adapting to how AI is changing search.
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Want to learn more about how your peers are leveraging AI? We surveyed marketing professionals across brands, agencies, and publishers to find out what tasks marketing teams are using AI for, how AI tools are impacting efficiency, how they predict AI will transform the future of marketing, and more. Check out AI and the Future of Marketing for all the findings.
Advertising agencies are experiencing a period of extraordinary transformation, caught between rising client expectations, mounting operational pressures, and revolutionary technological opportunities. To better understand the industry’s greatest obstacles and opportunities, Basis conducted a comprehensive survey of 100s of professionals at leading advertising agencies. The findings offer a window into the brewing challenges, strategic priorities, and future outlook shaping the agency landscape.
Our 2025 Advertising Agency Report explores those findings while providing agency leaders with actionable, data-driven insights to navigate this changing environment and position themselves for sustainable growth in the years ahead.
Here are some of the key findings from the report:
To get more insights into the state of advertising agencies, as well as an in-depth look at key takeaways and strategic opportunities based on the findings, download the full report today.
Advertising agencies are facing mounting pressure from all directions.
Economic volatility and decreased consumer spending are pushing marketers to make their budgets go further. Signal loss and privacy regulations are complicating the task of effectively reaching and engaging audiences. And, brand safety concerns are skyrocketing, driven by content moderation rollbacks on social media platforms, the proliferation of AI-generated mis- and disinformation, and low-quality content like made-for-advertising sites (MFAs) increasing across the open web. Clients are demanding greater transparency in everything from reporting to fees, putting additional strain on agency-client relationships. On top of it all, the digital media landscape is increasingly fragmented, and tech stack sprawl and siloed systems are making it harder to work in a connected, streamlined way.
In this context, it’s no wonder a growing majority of agency professionals agree that digital advertising has gotten harder over the last two years.
Though the challenges facing agencies are varied, inefficiency is a common thread either driving or aggravating many of them—indeed, agency leaders rank inefficient processes as the most pressing issue facing their businesses today. As such, by working to improve efficiency, agency leaders can make significant progress towards alleviating some of their biggest problems. Specifically, unifying data and embracing automation will allow agencies to work faster, drive better performance, and strengthen their relationships with clients.
Tech sprawl is at the heart of agencies’ efficiency problem. More than half of agency professionals say they now rely on eight or more tools to manage client campaigns, and 40% are juggling 10 or more. Teams are increasingly weighed down by fragmented systems and inefficient workflows, forcing marketers to operate in silos or waste valuable hours reconciling data manually.
The issue is further compounded by the fact that media fragmentation is at an all-time high. In fact, agency leaders rank siloed and disconnected systems as the second-most pressing challenge facing their organizations today. Without a unified view of performance, real-time optimization becomes inefficient and difficult, limiting agencies’ abilities to drive meaningful results.
Adding to the challenge, half of marketers agree that martech is complicated and difficult to use, and 63% of martech leaders say marketing teams lack the technical skills to successfully implement and use their tech stacks. These inefficiencies create operational bottlenecks that ultimately impact both agency performance and client satisfaction.
Finally, AI in advertising adds a new and often complicated layer to agency operations. While AI presents powerful opportunities to drive revenue, adding new AI tools to a tech stack can also increase the complexity of workflows. Without thoughtful implementation, proper training, and quality data, AI can contribute to inefficiencies rather than resolve them.
Unifying data and having a single source of truth should be a key priority for agency leaders in 2025. Centralizing data enables teams to deliver strategic recommendations that drive performance and craft compelling performance narratives for clients, rather than spending time pulling data from many different sources and attempting to unify it manually, which inevitably leads to errors.
Unifying data doesn’t necessarily mean overhauling entire tech stacks or tossing existing tools out the window, but rather finding solutions that bring existing systems together to ensure visibility, efficiency, and smarter decision making. With such solutions, teams can access real-time insights in a centralized dashboard—rather than spending hours pulling reports and reconciling data—allowing them to make faster, data-driven decisions. Unified reporting also empowers agencies to tell powerful performance stories with greater confidence, reinforcing their value and strengthening client relationships in an increasingly competitive landscape.
Additionally, a strong data foundation can help agencies to better harness AI. Right now, 58% of ad industry professionals say data quality or accessibility issues are a challenge for adopting AI in their media campaigns. Agency leaders that prioritize unifying their company’s data now will be better positioned to integrate AI-driven efficiencies and maintain a competitive edge in the evolving media landscape.
Even with a strong data foundation, agencies can lose valuable time to inefficient processes. Many teams still rely on manual reporting, campaign management, and optimization—practices that not only waste time but also increase the risk of errors. Media fragmentation compounds the issue, forcing teams to toggle between multiple platforms to pull performance insights, manually adjust bids across different channels, and use spreadsheets to reconcile data from various sources to create client reports.
Automation software addresses such inefficiencies by streamlining workflows and eliminating redundant tasks across the campaign life cycle. In reducing operational inefficiencies, automation frees up agency teams to focus on higher-value strategic work, which in turn drives stronger performance and strengthens client relationships. It makes sense, then, that 77.8% of agency professionals say their organization has plans to invest in tech to automate or streamline processes, and over a third of marketing decision-makers say the type of martech they plan to invest in the most over the next 12 months is marketing automation technology.
In an increasingly fragmented and complex digital landscape, agency leaders that focus on reducing inefficiencies by unifying their data and streamlining their operations will maintain a competitive edge. By embracing these strategies, agencies can ensure ad dollars are maximized and operations run smoothly. In turn, this will allow agencies to deliver stronger results, strengthen client relationships, and drive revenue in today’s ever-evolving digital advertising ecosystem.
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Want to learn more about how advertising agencies are navigating today’s complex digital media landscape? We surveyed professionals from agencies across the US to gather their insights on agency performance, industry trends, key challenges and opportunities, the impact of AI, and the future of agencies. Dive into the full findings in our 2025 Advertising Agency Report.
2025 is shaping up to be a critical year for advertising agencies.
Agencies are experiencing a period of extraordinary transformation, caught between rising client expectations, mounting operational pressures, and revolutionary technological opportunities. To better understand the industry’s greatest obstacles and opportunities, we conducted a comprehensive survey of 100s of professionals at leading advertising agencies. The findings offer a window into the brewing challenges, strategic priorities, and future outlook shaping the agency landscape. This report explores those findings while providing agency leaders with actionable, data-driven insights to navigate this changing landscape and position themselves for sustainable growth in the years ahead.
Select findings include:
Download the full report today to get more insights into the state of advertising agencies, as well as key takeaways and strategic opportunities based on the findings.
In the fast-evolving world of programmatic media and adtech, staying informed is key to advertising success. In this episode, U of Digital Founder Shiv Gupta joins host Noor Naseer to discuss how advertisers need sources of credible information to build sound adtech perspective.
Gupta explores how education can help advertisers adapt to rapid industry evolutions, from AI-driven programmatic advertising to evolving privacy regulations. This episode equips advertisers with the mindset shift needed to stay competitive as changes like these redefine the advertising ecosystem.
Noor Naseer: Maybe you want to understand AdTech like a pro, get into the weeds on a particular topic or something in between. That's what Shiv Gupta is helping address in the advertising industry. He's the founder of UofDigital, an education company that focuses on teaching professionals about digital advertising, AdTech, and martech. Shiv shares his perspective on why AdTech education is more important than ever before, who needs to know more, topics to prioritize and much, much more. Let's get into this episode with Shiv now.
Well, thanks for joining me today, Shiv. I'm excited to talk about everything that's happening from an AdTech perspective and getting educated and knowledgeable. So just want to thank you for the time.
Shiv Gupta: Yeah, thanks for having me, Noor. I'm very excited for this conversation.
NN: So I wanted to start off with a really kind of baseline question over here around AdTech education, and that is why is it more important now than it ever has been before?
SG: Yeah, I'd say there's a few reasons. So one is the obvious point of like the pace of change in our industry is accelerating. And you know, every year we say, Oh, it's changing faster this year than ever. And hey, guess what, we're gonna say that every year, we're gonna keep saying that year after year after year, because that's how technology works, right? Technology exponentially kind of increases pace of change. And that's true for our industry as well. So in a fast moving industry, that's only getting faster and faster, in order to be effective in your role, whether you're a buyer, whether you're a seller, whether you're, you know, an operator, a builder, you know, somebody commercializing products, you have to stay on the cutting edge of the space. Otherwise, you're not going to be able to do those things effectively.
So pace of change, number one, obvious thing. Number two, I think, really interesting in our industry is we're seeing a lot of convergence right now, between AdTech and martech, between like social media and programmatic advertising, linear and streaming, you know, you go down the line, like, everything is converging. And I think in the past, you know, let's say 10 years ago, we had these little bubbles, and we still have bubbles. But the bubbles are starting to coalesce, they're starting to come together. And so, you know, I'll use a simple example, like, if you used to be, you know, somebody that worked at DSPs, I could talk DSP all day long, and you were really good at it, maybe 10 years ago, that was totally fine. You're in a bubble, you're in your lane, you're doing a great job building, commercializing, etc. But today, if you're commercializing a DSP, you also need to know how to talk about CDPs, right? You also need to know how to talk about data clean rooms. You also need to know how to talk about martech more broadly, you need to know how to talk about cloud, because everything is starting to converge, all these areas are starting to converge. And because of that convergence, people have this increased need to be upskilled, right? Like that person that was able to talk DSP, well, it's cool to say, hey, now you need to talk CDP. But how do they talk CDP, you can't just like flip a switch and talk CDP, like, CDPs are a whole part of the LUMAscape on their own, they require actual like formal learning and formal upscaling and knowledge, you know, sharing and structured education for all intents and purposes, right?
So I'd say pace of change, number one, convergence, number two, I think those are the two key things I want to highlight right now.
NN: I think in so many ways you're already addressing this next question, but what is it in particular that people have to lose by not leveling up and having an intentional plan in place?
SG: Yeah, that's a great question. So I'm going to use another example or analogy, as you can tell, I like doing that. So if you think back, let's say to like the paper industry, right, or the oil industry, right, if you're somebody that was kind of in these industries, 10, 20, 30, 40, 50 years ago, those industries, because they're not necessarily like technology, you could argue they're technology industries today, but they didn't used to be, those industries didn't change very fast, right? Like once you're in it, you know it, you know how it works, then it's all about like, okay, who are the key players, do I build relationships, you know, etc, etc, right?
Now, today, we're in a technological space, you have to be tech savvy, and the pace of change, like I said, is increasing, right? So I think mentality wise, like we have inertia as humans, right, society, we have inertia, I think people have been slow to kind of get to this idea of like, oh, no, like, I am in AdTech or martech, I've been in this for 20 years, but I actually need to be in some kind of structured learning program, to be able to keep up with everything and learn about all the things I know, I'm not going to just learn it through osmosis, right? Because there's so much information and because of the pace of the change, because of convergence, right? So I think that kind of explains it in a nutshell, like, that's why you need formal education, we're not in the paper industry from the 1980s, right? We're not in oil from the 1960s and 70s, we're in a fast paced technology industry, and you have to stay on top of it. And listen, reading headlines is great. That's the first step. A lot of people aren't even doing some of that, right? So like, having an intellectual curiosity and going out and reading some of those things is great. But I think there's a difference between structured education and reading headlines. Because like, reading headlines, a lot of times, the purpose of that content is not to educate, the purpose of that content may be used to inform. And I think that's an important nuance, right? If I'm reading an article, that journalist or that reporter is trying to give me all the information associated with that news story. But they're not necessarily trying to teach me what happened in that partnership or what to take away from it or what it means for the industry moving forward, or how it applies to my day to day. They're not trying to teach me those things. They're trying to inform me about what happened. And so reading articles is very different than learning about what is going on.
NN: Who needs to get educated out there? I think there's so many different parties that can benefit from it, and it's not as narrow in scope as some may think.
I'd love to know who are some of those audiences that are leaning into you and are getting a lot of benefit from it.
SG: I mean, I'm biased, so I'm going to say everybody, right? Everybody needs it to a certain extent.
You'll be surprised. We get all sorts of different personas saying, hey, we need this. We get newcomers to the industry. That's an obvious one, right? If you're new to the space, obviously, there's no degree for EdTech and MarTech in college. And so typically in the past, we've just put people on the job and said, learn through osmosis. Hey, there's a better way. We don't have to do it that way and waste the first three years of someone's career just learning through osmosis. You can actually teach them some of these things. That's persona number one. Persona number two, I'd say, is people that have been in the space for a long time, 15, 20, 25 years, they're commercial people, they're sales people, they're account people, they're strategy people, they're marketing people, and they just have a need to keep up and also get upskilled on those adjacent areas that are outside their bubble that they need to learn about to do their jobs better. So I'd say that's another persona.
You'd be surprised, but we get a lot of leadership teams coming to us, CROs, CEOs, CTOs, saying, hey, I have to run a big company. That's more than a full-time job, but that means I can't keep up with all this stuff that I need to learn about. Can you help create a leadership track for things we need to know about? So leadership training.
I think on the buy side, you have marketers and agency folks that they're getting pitched all the time by vendors, but the pitches are obviously all biased. And so they have a need to get more unbiased objective knowledge so that they can make better buying decisions.
I think back office folks and engineers and product people, that's a really interesting use case as well, because those folks a lot of times, especially technical folks, they may not come from this industry, they may have great engineering skills, but they were from some other place, building SaaS products or something completely different. And then all of a sudden, it's like, hey, build an AdTech thing. And the context of AdTech really matters if you're going to build all sorts of personas. We've mapped out at U of Digital what all the different personas need, what level of depth they need, whether you're new to the industry or you're very senior. But frankly, everyone has a use case for education and knowledge.
NN: On a previous episode, I've spoken to a couple of different people on this topic, and I think a repeated theme is something you just brought up, which is that the proxy for education outside of headlines or industry trades is sales collateral, which is highly biased material and definitely incomplete. That's the baseline for so many people who are getting educated in this space.
There's massive gaps and space for more learning.
SG: Yeah. And I think to that point, right? Like I credit the big tech companies and all of the tech companies that are trying to educate their customers through like Google has a thing called skill shop and Facebook has blueprint and all these things are great. And they have some really great material.
A lot of it ends up becoming a bit of a product pitch. Cause that's the point. That's why they're doing it in the first place. They want people to learn about, yes, the industry, but from their lens and from their point of view, which then guides people to buy their thing. I think having objective information and knowledge and education is critical.
NN: At Basis we have a program called AdTech Academy. And we have an incredible team that's focused on education.
But we have our scope, our scope corresponds to whether it's our product suite, our service suite, and goes maybe a little bit beyond. But there's so much more right to your point as far as adjacencies and tangential information that can really expand learning. All of these organizations, whether it's like the really big guys, or everybody in between, they have a little bit of a more narrow parameter. So there's need for more education, for sure. I wanted to dive into some points with you around what are some trouble areas that people have consistently struggled with. And maybe we can talk about one or two different points. But I'm sure you're very familiar with what people are struggling with.
SG: I'm going to answer your question, but I'm going to caveat it, right? So my caveat is like, depending on where you sit in the industry, your experience level, your job function, the company you work at, there are different answers. And so it's hard to kind of make a blanket statement on that.
I would say right now, if you kind of like froze this moment, right now, AI is top of mind for everybody, right? Just in terms of like learning about it, what is it? How does it work? What's the future hold? And so right now, that's probably our most popular kind of request, like, hey, teach us about AI in advertising, in marketing and AdTech, more tech, et cetera. So I'd say that's number one, I'd say number two is probably CTV. I think connected TV is such a big opportunity in our industry. And everyone recognizes that it's changing super fast, like everything else, we're trying to smash together linear TV principles with digital principles. And that's connected TV right now. And like, you have people from different sides, you have linear TV buyers, you have more digital buyers. And that creates like this big mishmash of confusion and complexity. And that's how we're building products, right? Like we still, for example, measure CTV using old school linear TV measurement methods, right? We still track GRPs and TRPs for CTV buys, which is crazy. But we do that, right? And that's, that's an inertia thing, that's a traditional media thing. And so, you know, I'd say like, emerging channels in general, right, I kind of highlighted CTV, but any kind of channel or format that is transitioning, let's say from more traditional means into a more digital means, right? So that's digital out of home, that's streaming audio, I think those are the key ones, right? CTV streaming audio, digital out of home, those are kind of the key channels right now that are making that transition. And that creates a lot of complexity, which people don't feel comfortable with and need to learn about and need to unpack.
NN: So let's dive a little more into the CTV piece. It's very obvious why there's so much interest in CTV. There's, you know, if you're on the sell side, there's the most money to be made. And I guess that trickles down the supply chain.
What is it that people are struggling with the most? I think it's clear in many cases, but I'd love to hear from you what those struggle points are for CTV.
SG: Sure. I think, first of all, CTV, it's so complex on the supply side and the content side first. You have content that originates with one party, but then that content can be distributed in so many different ways. It can be distributed directly from that publisher. It can go into an MVPD. It can be packaged in with a SVOT or AVOT app, streamed live. It can be sold linearly. There's 25 different ways in which a piece of content, TV content, can make its way to a user. That in itself creates all sorts of complexity in terms of how that content can be monetized. I think unpacking that and understanding that is the root of the education gap.
Then you get into the nuances of, because we were trying to make this bridge between linear and CTV, the measurement is complex. We train a lot on the measurement of how can it be measured. Also, the targetability and the data aspect of CTV is very complex. What can you target? How can you target them? What's actually real and what is not? How do these ID solutions work for CTV? I think that's pretty complex. I'd say it's measurement. It's targeting an identity. Then last but not least, it is just understanding the ecosystem of players. Because in classic AdTech fashion, CTV has its own LUMAscape now with a bunch of different boxes. It's like, okay, well, you're a content producer, but you control everything through your own app. Oh, but no, there's another content producer that only distributes to third party apps. Okay, well, there's three buckets within the content producer square. Now we get to OEMs. OEMs, there's the Roku's and the Samsung's and the LG's of the world. Then there's Comcast, because they're technically an OEM as well or a device owner. Then there's all sorts of blurred lines and different boxes within that box. Then you get an AdTech and it's like, oh, we have CTV specific SSPs. We have CTV specific DSPs. Now we have startups that are just like Vibe and the Jam loop. These guys are just focused maybe on the mid market. There's CTV DSP for those guys. It's like there is a lot of complexity and just understanding the ecosystem of players. That's another area where we're having to educate a lot.
NN: A question I get most frequently from people on the agency side and the brand side, anybody who's responsible for buying is the classic measurement question. So to go back to something you mentioned earlier, Shiv, it's that how do we convert this rating point system into one that is equitable and that my client can respect when it seems like this dust still hasn't settled on what's going to be standardized in the CTV world?
How do you start to have that conversation with media buyers?
SG: My perspective is that I don't think we will standardize it. I don't think we will.
And there's a few reasons for that. Linear TV was a very clear cut advertising medium in terms of what it is trying to achieve, which is more upper funnel type of outcomes for whom. And there were a few kind of publishers that controlled a lot of that inventory and sold it in a very specific way. And so it's easy for us to agree all on like a general kind of way to measure this. Digital is a whole other ballgame. When you think about like the way you can target people, the calls to action and the things that people can do after seeing an ad on TV now with QR codes and things like that. And so all of a sudden now you are selling advertising to people in more targeted ways with different desired outcomes up and down the funnel through all sorts of different tech. And that then just, it opens up the box that is digital advertising. And so if you think about the way we measure and digital advertising, there's 15 gazillion different ways to do it. There's brand lift studies, there's conversion tracking and attribution, there's MMM, there's MTA. You know, there's tons and tons and tons of different ways to measure with different types of data. And that's where we're going with TV. Like I think brands and advertisers have to actually get comfortable with that idea, learn about all the different ways to measure. I understand why it feels like a curse. It's actually a blessing, right? Because the reason we were doing linear TV in this very uniform way is because the only way we could buy and sell TV and the only thing we could achieve was a very basic thing. So that's my kind of viewpoint on like, we're not gonna have standardization in CTV. And that's actually a good thing because it helps advertisers figure out like, how do I actually measure what I am trying to achieve.
NN: I want to shift over into another topic. I think you mentioned two big ones. I think the other one was AI. And I'd love if you could frame the AI side of things, thinking about it from the perspective of like a media buyer or somebody who's responsible for programmatic campaigns.
And I'll just like set the table a little bit as far as where we're hearing a lot of energy is, of course, AI has a myriad of applications. But specifically, when we've been talking about it for programmatic, it's like, oh, we have all these AI solutions. But what we actually mean is that we already had stuff in place. And it's not actually new type of AI. And a lot of these solutions are smoke and mirror solutions. I can't imagine you get any shortage of questions around how much of this is legit? How do I even understand what like AI means pertaining to me, because I think what people are looking for is advancement, they're looking for some sort of new emerging opportunity to level up and solve for challenges that they're currently facing. And people are trying to distract them with a new title on an old thing, so wanted to get your thoughts and how you've been addressing AI for media buyers.
SG: Yeah, 100%. So I think there's a few answers to that. So first of all, machine learning has always been around, right? It's been around forever. And so, hey, everybody, let's be cautious about when we use the term AI, are we talking about machine learning, which is totally fine to do, right? Because machine learning, if the machine is actually learning and getting smarter and taking data and, and getting better and better and better, that's literally the definition of AI. But machine learning is very different than what AI, let's say, has become in the last couple of years since ChatGPT launched. And now, you know, we kind of talk about AI as being synonymous with LLMs or NLP, natural language processing. And so, first of all, let's figure out, which one is it? Is it that? Or is it machine learning? And machine learning, we've been doing for a long time? Is it a new thing? Or is it a branding exercise? Is it a marketing exercise, that, you know, somebody's coming and pitching to me just like a rebranded version? It's actually just machine learning, and they slap a new logo on it, or a new, you know, label on it.
So there's that. The other thing I'd say is like, it's really important, I think, to talk about AI, starting from the use cases, right? So like, again, classic industry and technology problem, we talk about the technology and how cool it is, and what it might be able to do. We don't actually talk about the business problem we're trying to solve first. That's where we should always start, right? Like start from the use case, start from the business problem, and then go backwards from there and figure out like, oh, okay, well, maybe AI is a solution to this thing that I'm trying to achieve.
When we are training marketers and buyers on AI, we're literally breaking down all the things that marketers have to do. So that's planning. That's execution. That's optimization. That's measurement and analytics. Let's go through each of these tasks that we have to do as buyers, and think about now, okay, here are the problems. And then are there ways in which AI, whether that's machine learning, or LLMs, or natural language processing, or some other form of AI that I'm not even talking about, right now, can solve those things. And if there are, let's talk through how those things work, which tools exist out there. And that way, we make it tangible, right? We're actually solving a business problem, right? And that's like, frankly, how we like to educate. It's about actually learning in a way that's applicable to what you do.
One more thing to add, I'd say is like, AI, like any tool, people are more likely to understand it and want to use it when they actually start using it for their own life. That's what creates behavioral change. Hey, I actually like, I bought the Google Home. And so now I understand voice a little bit better, right? Or I have a smart TV. So now I understand like, the tile ads on my smart TV better, right?
A lot of what we're seeing with AI right now, which is bonkers to me, we're two years into this, and it's going to revolutionize everything. A lot of people still aren't comfortable going to ChatGPT, and so like, help me write an email, right? Or like, dissect this report, or here's a PDF. Can I ask you a few questions about what's in here in this 30 page PDF, right? Instead of me going through manual and reading all of it.
And so we're trying to get people to apply it to their regular life a little bit to start creating the behavioral change where they will start opening their mind by themselves organically to how it can be applied in other areas in their work, potentially, right? So that's another aspect of what we're trying to do with the AI training is like, just create behavioral change by getting people in there, getting them using it, even for simple things.
NN: I know we went through two topics, and I want to backpedal a little bit correlated with some things that you said about TV. And the fact is that the standardization of the past is not something that's going to apply to the future.
It's something that me and my team have been talking about constantly across this year. People have misconceptions, people who have been in the advertising space for a long time. So I'm curious to ask you, not just specifically related to CTV, but are there a couple of areas where people can't abandon the past that they're so addicted to? And how do you try to help people get to a place where they can accept that? This is a misconception. And we need to start thinking about this, whatever that thing is, they need to get educated on.
SG: Yeah, it's a great question. My mind just goes to one place, and it's kind of full circle here, like it's measurement. It's measurement, measurement, measurement. Measurement is what validates or disproves the value of everything we do in this space in terms of marketing and advertising. If we measure it, and the measurement tells us it didn't work, then we're not going to do it anymore. If we measure it, and it says it worked, we're going to do more of it, right? And we're going to keep doing it and doing it and doing it. And so measurement, fundamentally, in our industry is broken because of inertia, because of the old ways of doing things, right?
So, you know, just some examples, last click attribution, I think is a broken way of measuring. I don't blame marketers for being hooked to it. There's a lot of good reasons why they're hooked to it. It is not actually telling us what is good and what is bad. Even last view attribution, you can make the argument for that. GRPs and TRPs, a lot of these things are broken. And you know, when we talk about some of the problems downstream in our industry, content issues, brand safety issues, fraud issues, all of these problems that we have downstream in our industry can all be traced back to problems with how we measure. Because when we say something is good, and we buy more of it, when it's not actually good, and it can be gained, then that's where we get, you know, nefarious activity and fraud, and you know, bad content, etc.
If I serve an ad, and it drove a last click conversion or a last view conversion, but it was served on a garbage MFA website, we're basically supporting that website. We're basically saying, hey, good job, pat on the back, keep doing what you're doing. And so that's the thing that is hardest. I'll go back to what I was saying a minute ago, which is like, people are hooked to some of these antiquated ways of measuring. Because listen, at the end of the day, you have to be able to explain to your CFO why you're doing what you're doing. And the CFOs don't understand, there's a big education gap there. And they're like, well, last year, you drove, you know, X many click conversions for me, I want to see what you're doing this year. And I don't want to hear a story about how click conversions are broken.
That's what I understand on the CFO, right? So we have to answer to our CFO, we have to look good on spreadsheets. And in order to look good on spreadsheets, you have to show year over year, month over month, apples to apples comparisons, you can't just say, hey, I'm completely changing how I measure things. Like, that's hard to do. That's got to come from the CMO down, or even the CEO or the CFO down. And changing that is hard. Those people in the leadership suite don't understand some of this stuff. They need the knowledge and the education, so they can change. And so that's why we're stuck to it. That's why we're addicted to it. But it needs to change if our industry is going to improve and get better.
NN: It's making me think of what these needs are for a lot of people who report to people in the C-suite or the executive suite, wherever their organization is. Maybe they're in charge of media buying or just overarching campaigns and they're struggling with exactly what you described. And they're also struggling with the sources from which they gather information. So even if I seek knowledge from whomever it is that I seek it from, I ultimately need to sit down with partners and evaluate and see if what they're offering is in fact going to meet my needs.
And let's say it's from the spectrum of measurement. Measurement's been another space where there's been no shortage of smoke and mirror type of players. Attribution is a space where there's like maybe the vast majority of smoke and mirrors. I'm sure some people will not like to hear me saying that. It's just so very true. Like people build these glass houses and they can be knocked down easily, but sometimes you don't know until you test and learn. So I think that's where people really are seeking a lot of education. How do I know that I know enough so that I'm not wasting my time signing up for something that's going to be a waste of my client or whoever that their needs are being met? So if you were to address a question like that, how do you make sure somebody knows enough so that they're not getting scammed? Seems like a strong word, but like essentially so that they're not getting tied up in something that they don't want to be associated with.
SG: Like, I think that that's tricky, right? Because on one hand, yeah, you want to be able to kind of say, No, listen, this is how I do things. And this is how I've set it up. And I believe in that.
On the other hand, you want to have a mentality of like, always be learning and keep your mind open. And maybe you're not doing it the right way. And so always be scoping out what's out there and keep an open mind. I think with measurement in particular, right now, we're a really interesting moment where there's a lot of stuff going on, there's signal loss, right? So we're losing a lot of our tracking mechanisms, there's new types of signal coming in, that makes things, you know, more difficult, walled gardens are putting up their walls, it's hard to get data out, etc. fragmentation of partners and channels, we talked about channels earlier, like CTV is different from streaming audio is different from display from social. And so measurement is getting harder and harder and harder.
And I think in this moment, you have to be open minded, you have to do a few things. One is like, you have to always be questioning what is your source of truth, you always have to be gut checking your source of truth. I actually think the idea of a source of truth is almost becoming antiquated in a way, because there is actually no right answer anymore. To measurement, you have to constantly be triangulating multiple different methodologies and approaches to measurement to constantly be gut checking what's actually real and what's not. And so I think almost like taking that mentality is the right approach of like, no, I have to keep gut checking everything I I'm going to keep questioning, you know, the source of truth or the measurement that I have in place. Because at the end of the day, with everything in flux, everything changing, like, if I get set in my ways, you know, I'm gonna extrapolate a little bit, but like, you're just like playing out the next version of last click attribution, right? Like, in a microcosm of like this current environment, I think it's almost like, hey, don't say you know enough, always be questioning and get your organization and the people around you to have that same mentality. And that's what's going to help you drive outcomes and drive your business for them, right? Because at the end of the day, right? Marketing is not about the number of conversions you got in your spreadsheet. Marketing is about, hey, did my business grow from last year to this year? And if you're keeping that lens, and then questioning all the measurement underneath it, to get to that result and get to that outcome, I think that's when you know you're doing a good job.
NN: I want to ask you a specific question about the tech stack. You mentioned many different elements that are associated with it, and that there's tangential learning that needs to take place.
So I have my specific role, but then there's this halo effect or ripple effect where I need to learn about these other things. And I'm just framing the question to ask, how much does a non technical professional need to learn about some of these different elements in the tech stack, especially when they don't have the opportunity to really like dive in on a day to day basis.
SG: I love that question. I mean, most of our learners nor our non-technical audiences, right? We're training a lot of business people, right? Sales people, account people, media buyers, strategy people, marketing people, et cetera, right? So we deal with these folks a lot.
And frankly, like there's too much to learn. There's too many subject matters. There's too many domains. There's too much technology to expect yourself to go a mile deep on everything. You don't need to. What you need to be able to do is understand the strategic big picture. You need to understand where all of the things kind of fit and what purposes they serve, what use cases they serve, why they exist. You need to be somewhat of a thought leader and you need to be opinionated about some of these things. Not all of them. You don't need to always have an opinion, but you need to have some thoughtful opinions about the things that are relevant to, let's say, your partners or your customers or your key constituents or to your business.
Those are the things you need to know, right? It's like what matters to the people I work with, what matters to the outcome I'm trying to drive out of my role. I think that's where people fall down a lot because they don't think that certain things matter when they do. It's just kind of expanding your aperture, opening your mind to like, oh, okay, I sell a DSP. In the last five meetings I've had with customers, the term data clean rooms has come up and I didn't know it. I didn't understand. I don't understand why it exists. I don't understand what purpose it serves or maybe even I did, but I didn't have thoughtful opinions about it. Okay, that's an area where I need to go get more conversant.
I don't need to get technical. I don't need to access a UI and actually set up a data integration. I don't need to do that, but I need to know what it is. I need to know what use cases it serves so I can talk to it about my customers. That's how I'm going to do a good job, right? By no means do I encourage everyone to go out and learn everything and go a mile deep. That's unreasonable. I can't do that. You can't do that. Nobody can do that. There's too much, but what you need to think about is what job do you do? What outcome are you trying to achieve? And where are your blind spots or knowledge gaps that are preventing you from doing that? And I guarantee you, everyone has those. There's not a single person that is like, oh, I know all the things I need to know in order to do my job as effectively as possible.
NN: What do you think about, I'm going to call it AdTech Twitter, and just social spaces in general, because we talked about some other sources that there is sales collateral. There is obviously educational resources that have been developed, like you have digital amongst some other players out there. There's articles from the trades, which those people they have a beat, but they're not speaking of non-technical people, typically people who are writing about it are also non-technical. And then there are these thought leaders online that are speaking about it extensively. And a lot of people use that as a proxy for, I guess, education as well.
This is kind of a question that's going a little bit of an outlier question. How often are you seeing something where you feel unaligned or you think, oh, the baseline of this person's understanding of this topic, it's not quite there. How do you internalize that? Because you're in the business of really knowing these things, because there's so much accountability that you need to take on in order to be an educator in this space. But when you see something that's not quite right and it's being publicly solicited for consumption by people in the AdTech world, what do you do?
SG: I'll be the first one to say, you mentioned accountability. Yes, I have accountability, especially when I'm formally in a learning environment. I don't feel that level of accountability on social media, for better or for worse.
I'm out there just trying to talk to people and learn and hear what's going on. Honestly, sometimes have fun with it because sometimes I think we take ourselves too seriously in the industry, so I think it's a nice outlet. But I think the key thing with social media is taking it for what it is. People go to social media to be whimsical, to get a break, to get entertained, to listen to thought leaders and hear opinions. Social media is all about opinions and not necessarily facts and reality. I think if you go into social media with that mindset, you'll do well and you'll take away valuable stuff from it, but you have to have that grain of salt with everything you get. Also, a lot of times on social media, people are using social media as a marketing channel, whether that's to propagate their own opinions or their company's viewpoints or what have you. That's what social media is. It's a marketing channel. There's a lot of value there, 100%. Also, just the speed of social media. Oh, this company just bought this other company. What does it mean? I'm getting that from Twitter and LinkedIn. I'm not getting that from a press release. I'm not getting that from a blog post from the companies. There's a lot of value there in terms of speed and quick hit information. But again, everything I think on social media should be taken with that grain of salt of people are going there with an angle. People are going there to be whimsical. People are going there to share their opinions. People are going there to be entertained. If you can take that mindset into it, I think there's a lot of value to be had.
NN: Do you think the AdTech slash digital media programmatic industry has failed to resonate with audiences as far as actually educating them? And I'll give a little bit more context around that question.
So often you'll go to a conference and people to go back to the agenda piece, people have their talking points, they've worked with their marketing team. Now they have their best executives up on stage saying something as like, this is objectively true. It is something where people are trying to like determine like, am I learning something new? Is this true? Is this just true with your technology? Is this an actual opportunity for me to learn? Just again, curious for your opinions and in these types of other spaces, which also I left it out when I shared earlier, like places of learning, in theory, you would go to a conference as a space for learning, but everything is sponsored. So it is another space where you take things with a grain of salt. Just again, curious for your thoughts in that space as well.
SG: 100% listen, I think like and this goes back to what we were talking about with like the academies, right? There's a lot of value in all of these forums, whether that's conferences, social media, you know, vendor provided academies, there's a lot of rich content, you definitely shouldn't dismiss it, you just have to go in eyes wide open of like, who is telling me this? What is their angle? And if I can remember that, and kind of caveat everything I'm hearing, then I can get a lot of value out of this.
And I just feel I feel the same way about conferences, you shouldn't ever go into like a sponsored panel, expecting to come away with the objective truth and nothing but the truth, like, you should come in expecting to hear opinions and angles. And like, you know, a lot of times, it's very valuable to know the angles of these companies, as long as you go in with the eyes wide open of like, this is not just going to be objective truths, this is going to be, you know, an angle, and that's okay. And I can still benefit from that. I think you're fine, right? And I think you're fine in most forums. Very rarely do I go into like, I mean, sure, there's like webinars that are just garbage, and it's just like fluff and nothing material there. Sure, there's plenty of panels like that, too, where they just say like the words and the jargon, there's a lot of garbage. So sure, obviously, like have that filter. But there's also plenty of those situations where it's very valuable, even though there's an angle.
NN: Yeah, the opportunity is to observe how people choose to position and then like make a note of it. Very much agree with that. And that's important, right?
Like the, you mentioned of the LUMAscape earlier, it feels like an infinite volume of micro LUMAscapes out there, not micro actually, they're big LUMAscapes out there. And despite M&A activity, there's new actors popping up all the time, new spaces, sometimes it feels like there's overlap. So maybe that can be one of these final questions I'm moving towards probably should have asked this earlier, sometimes it just feels so overwhelming. And you had said earlier that you can't know everything, nobody can know everything, but you want to know enough. Do you ever advise on how often you should be leaning into educating yourself? Because you have a lot of other responsibilities. How do you set aside enough time to feel like you're chipping away enough to be knowledgeable?
SG: Great question. Couple of thoughts. First of all, being okay and being comfortable with the idea that I'm never going to know enough and I'm not going to know everything is the first step. Knowing that you're not always going to know is good. That's step one.
Step two is I don't think I'm a fair comparison for folks that are actually working at companies and building products and things like that because I'm in a very fortunate position of my job is to teach, my company's job is to teach and educate. Because I don't know if you've heard this saying, but the best way to learn is to teach. When you teach somebody, you’re learning. You have accountability to the information. We're in this fortunate position where we have to be learning all the time in order to teach. For me, that's my job. It's constantly learning, constantly reading, constantly asking questions. If I was to say to other people, it goes back to the question you asked earlier, you have to feel confident. Being confident is important that you know the things you need to know to do your job effectively and also knowing that there's always going to be more. I know I'm talking on both sides of my mouth. I'm saying both sides of it, but that is reality. That's the reality of our situation is on one side, have that confidence. If you don't, go out and get there and learn the things you need to know in order to do your job effectively. Also, be confident in knowing that you're not always going to know and you're always going to need to be learning more. That's my very wishy-washy abstract answer.
NN: No, I think that framing is something that I have encountered, maybe more so in the past. And it's because I used to ask more binary questions in front of audiences where I say, do you know about X? And then people I think felt pressure to say, yes. But yes, to what? What is it that you know? So now I'll ask many more, you know, qualitative questions, tell me what it is that you know, and let's go from there, as far as really understanding where there's opportunity to like fill a gap and or find where are there potentially misconceptions?
Where do we have differing opinions? How can we get more aligned? And that that scenario that has application for every single person that not only works in the AdTech space that works for everybody who works on anything ever. And it's, it's just AdTech happens to be so incredibly complex. So from there, I wanted to ask you one or two last questions to round us out, one of them being to just learn about a little bit more about you and your process, what does Shiv Gupta do to stay informed? Are there foundational or fundamental things, just topics that people really should educate themselves on so that when they do read the trades, when they do get exposed to all these things you describe, they can feel more comfortable knowing that you're not going to know everything, but there are actually some things you absolutely need to know.
SG: I could say a bunch of things that are true for different types of people and personas. So it's hard to give one answer.
But my one answer right now in this moment, March 2025, is go learn about AI, please go learn about AI. Everyone's talking about AI, every article has something to do with AI, every company's rebranding itself as AI, learn about AI, our whole world is going to be very different in a few years. It's like the internet, like how the world changed from 95 to 2005. That's going to happen in a condensed period of time over the next few years. And you want to be ahead of that curve, right? If there's one thing I would encourage you all to listen to or learn about right now, it's AI.
NN: if there were some other topics like in my mind, there is the never ending challenge of understanding addressability slash targetability. And to your point measurements, are there things about any one of those more foundational topics? Because to your point, you could say a million things, right? You could say every emerging platform, every emerging technology, every part of the tech stack, that would all be seemingly valid as a foundation.
If you are a programmatic buyer, or you're responsible for campaigns, since that that's like a classic angle for us, I feel like things pertaining to identity measurement and attribution, they’re table stakes in that everybody wants to know about them, but they don't know as much about them as they would like. How would you advise someone if that was their baseline? What should they be doing to learn more about those types of topics?
SG: I mean, listen, the word data is nebulous. I'm going to say like all things data to your point, right? Like understand what kind of data exists out there, how it can be used, how it can be tracked, how it can be used for different parts of, let's say, a campaign process and the planning process, the execution process, activation, optimization, measurement, analytics, like data, data, data, right? If you don't understand something about where data is coming from, how it is being used, the output, then that's an area to get smarter.
And I even think like tying it back to AI. In the world of AI, UIs are going to become defunct, right? We're always, we're going to start talking to things. We're going to have agents doing things for us. Gone are going to be the days of I log into a thing and I click some buttons and it does tasks for me. Those days are going to go away pretty soon.
And so I think you have to think about like what underpins what we're trying to do and where there's differentiation and it's going to come from data. And so I think all things data.
NN: I love that answer. I love landing the plane there.
I know there's so much that you can say about what's happening in the AdTech and programmatic and digital marketing and digital media world. We'll have to have you back another time to talk about something additional. And I just want to thank you for the time today, Shiv.
SG: Yeah, thanks Noor for having me on. This was a really fun conversation and I'm excited to maybe do it again one day. Thank you.
NN: Thanks to Shiv Gupta, founder of UofDigital, for sharing how at-tech pros can level up through education and training. Staying ahead has become more complex and labyrinthine than ever before, making continuous learning essential.
If you want to learn more, a good place to start is UofDigital's newsletter, which you can sign up for at the letters U of, that's the letter U-O-F dot digital forward slash newsletter. And while you're there, you can learn more about their other programming. You can also check out Basis' website's resource center to find more education resources and insights. You can also check out AdTech Academy, which offers free courses, learning paths, and certifications. That's it for now, another AdTech Unfiltered episode coming up soon.
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