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It’s no secret that words like artificial intelligence (AI) and machine learning (ML) carry a lot of weight these days. No doubt, these technologies have changed industries for the better with the ability to process high volumes of data rapidly and accurately, providing analysis and actionable insights that can be leveraged in myriad strategic business decisions.
Perhaps not surprisingly, ML is especially relevant to digital advertising. With its ability to not only compile consumer data, but analyze and predict future consumer behavior, the technology has significantly transformed the space and will continue to open up new doors for the industry going forward. Yet few people really understanding its specific role and its vast potential for advertisers.
First, we’ll distinguish between AI and ML.
Artificial Intelligence (AI) is essentially a computer system that can perform tasks that would normally require human intelligence, such as making decisions or understanding speech language. AI has applications to a wide variety of industries, including advertising.
Machine Learning (ML) is a type of AI that uses statistical techniques to learn from data. When an AI computer system is set to perform a specific task, machine learning allows it to learn from new information as it comes in. It can then make changes to improve performance at a task without being programmed to do so.
In advertising, AI and ML elevate the ability to make buying decisions that emulate human decision making. However, with the right AI technologies and data insights, it’s actually possible to significantly improve decision-making processes beyond human capabilities.
The digital footprint consumers leave is huge, and it’s only continuing to grow. On Google alone, 40,000 search queries are performed per second. To put that in perspective, that's 3.46 million searches per day.
In order to create the most relevant advertising message and deliver it at the right time to the right audience, marketers need as many data insights as they can get. But, in light of the enormous amount of consumer data generated on a daily basis, advertisers are struggling to analyze and act on the information available to them. By the time they manage to derive insights and adjust their campaign strategy accordingly, a new, more relevant data set emerges. Only the largest and most competitive global corporations could hope to build an advertising team with enough data specialists to effectively tackle this kind of undertaking.
While many advertisers don’t yet realize it, ML is the only viable solution to this growing problem. Among other things, the technology makes it possible to analyze and gain insights from vastly more data than a human ever could ever process in their lifetimes. What’s more, it also automates advertising decisions based on these insights, making ads more efficient and effective, and driving business revenue in the process.
Among other things, ML has the capacity to draw on data from a wide variety of sources, including search engines, social media, and other third-party platforms. It can then draw connections and make sense of it in a way that a normal human brain isn’t equipped to do.
Consider social media, for example, where individuals discuss their interests and pain points, follow topics that interest them, and check in at various locations. In what’s known as cognitive intelligence, ML can use this information to build complex personality profiles. In addition to better understanding customer demographic information, marketers can then leverage these comprehensive profiles for insights into users’ thinking, behavior and even their next probable move.
Thus, building better audience profiles makes it possible to create more relevant and targeted ads for potential customers -- a capability that has become increasingly critical in recent years as ads have become more irrelevant to, and thus ignored by, consumers. Having a deeper understanding of the needs, pain points, and even your audience’s train of thought makes it possible to develop truly meaningful and relevant ads aimed at addressing their toughest challenges.
The same processes that make it possible to build better audience profiles can also help advertisers discover new audiences that they never before thought to target. ML can help uncover unlikely but valuable correlations between consumer demographics, interests, and online behavior that reveal new potential target audiences.
For example, an AI system has the ability to analyze a large set of Facebook data and discover that older women who are interested in green living and like horror movies are more likely to buy a certain category of digital products. The data might not explain why this unlikely correlation exists, but advertisers can test out the opportunity by showing ads to them and accurately gauging their response.
AI also makes it possible to develop a template of target audience characteristics that you can search for, identify and cross-reference across the web. As with Google’s similar audiences or Facebook’s lookalike audiences, you can discover new leads to target across the entirety of the internet, as opposed to just one platform. Using vast amounts of third-party intent data, ML can process this consumer information and make sense of it in new ways that lend themselves to better and more strategic decisions for your business.
Historically, most advertisers have relied on spreadsheets and basic analytics software to track their data and generate insights to optimize their campaigns. All too often, this becomes a tedious, error-prone, and laborious strategy that generates only marginally valuable insights.
Artificial intelligence and ML, on the other hand, can automate this process, freeing advertisers to focus on discovery, growth, and other initiatives to improve the media-buying process. Because ML does this more rapidly and accurately than humans, it also results in more valuable insights. Depending on what kind of AI technology is being leveraged, it’s possible to improve insights even more by incorporating your own previous ad performance, as well as that of other advertisers, into your analysis.
ML is also a worthwhile investment because it vastly broadens your dataset and analysis capabilities beyond that of advertisers. What’s more, it continues to grow in value over time as it learns from the performance of its own choices and uses this information to improve future campaigns. In short, the longer you use machine learning technologies, the smarter it becomes, thus increasingly emerging an essential tool for obtaining more ambitious advertising goals and metrics.
Employees tend to get nervous when their employer starts implementing AI and ML technologies -- largely because they assume AI will supplant their jobs and minimize their value to the business.
But in reality, the best way to use AI and ML is by allowing them to support internal teams, not replace them. In fact, using ML effectively can make advertising teams more competitive and relevant in the industry, which can actually increase their overall value to the organization. Also, because ML has the ability to predict the outcomes of campaigns, media buyers can leverage the technology as a check to help them avoid mistakes before they occur. If, for example, they accidentally clicked the wrong campaign setting or forgot to adjust their budget to match seasonal bid costs, these outcomes could easily be displayed in the predicted results, enabling the business to course-correct before a bad decision is officially executed.
As previously mentioned, ML frees media buyers of tedious tasks and saves them time, providing more opportunities to focus on strategy and development. Applying ML to routine, administrative tasks means that advertising teams spend less time doing busy work, and more time working on creative, innovative projects within their department.
While some businesses might envision a future in which advertising is 100 percent automated by machines, it’s more likely that ML will become an essential tool that advertisers will regularly rely on to support their internal teams and streamline workflows.
ML can derive and help businesses act on new data insights faster than a human, or even a team of humans. At the same time, it can use advanced statistical algorithms to identify trends and predict future outcomes. That means it can help advertisers see around corners and make necessary bid adjustments to maximize their return on ad spend.
Its ability to make changes quickly also helps businesses cut costs and reduce wasted ad spend, as it can identify unnecessary spending quickly that will enable you to lower your bids accordingly. Leveraging ML for more accurate and timely insights mean better ad targeting, making it possible to reach advertising goals with a significantly lower budget.
The right advertising software will utilize an advanced decision engine to predict the best ad investments. By using important buying signals, data, and quick bidding options, these solutions can ensure you always effectively leverage your advertising budget to increase ROI.
ML is transforming the digital advertising industry on a daily basis, and as such, has the ability to dramatically improve the direction -- and ROI -- of your campaigns. Currently, AI has the ability to discover new audiences, build comprehensive user profiles, save time, reduces ad spend, and supports advertising teams in countless ways.
That said, it’s only effective as the solution in which it's being used. Advertising software can pay for itself and then some by improving the efficiency and effectiveness of your campaigns. And looking ahead, ML will become an increasingly necessary tool to add to the advertising arsenal, further accelerating the evolution of the digital advertising industry, as businesses find new and innovative ways to realize its true potential.
Few can deny that big data is the engine powering numerous industries -- and that includes digital marketing. From phones and tablets to social networks and even digital assistants, consumers have more channels than ever from which to access brands' products and services.
While for marketers that means even more ways to reach niche audiences, it also means exponentially more data at their disposal -- which they are now required to parse and analyze in order to make smarter and more strategic decisions regarding the future of their digital campaigns.
Consequently, the role of the digital marketer has evolved significantly to one that can also make sense of copious consumer data -- numbers, statistics, and trends -- to optimize their campaigns, increase ROI, and bolster conversions. While this sounds like an enormous and daunting endeavor, big data also provides a path to detailed, nuanced, and previously unattainable insights that have served to strengthen their SEM and other digital marketing efforts.
Here are five ways that big data has turned digital marketing on its head, opening up new opportunities for marketers and their customers.
Improving the customer experience should always be a top priority for brands. After all, the experience customers have buying products and services from you will often have a direct bearing on the type of review they leave, whether they return to the site or patron your competitor.
Big data gives you a reliable way to effectively measure and assess where customer engagement is strong and where it lags, what resonates with your customers, and where they lose interest. For example, different aspects of your campaign as they relate to customer satisfaction can be tracked and adjusted accordingly, providing you a means of connecting the dots between the components of your campaigns that resonate with consumers and the resulting behavior that elicits the highest returns. This information can include the time they spend on a site looking at your ad, the number of pages visited once they’re on your site, return visits, or comments and feedback, which can then be compiled in aggregate to make the customer experience -- including the conversion process -- simpler, and more efficient.
Without a doubt, big data insights garnered from analytics tools have given brands a better ability to accurately respond to customer needs and wants, as well as fluctuations in their consumer habits and behavior, lifestyles, incomes, and other variables.
If anything, the availability of these insights equips digital marketing teams with the ability to be flexible and pivot, if necessary, for the customer. The result? Better ways to engage with consumers and more effective strategies, which in turn makes for more satisfied and ultimately loyal customers.
It’s well established that much of digital marketing -- PPC advertising in particular -- is about the art of locating and targeting new and desirable audiences that have a strong potential to become customers. Big data is the fuel that drives these campaigns.
Among other things, big data can help you take full advantage of all your digital marketing channels by vectoring in on new demographics and groups of consumers that have an interest in your product, as well as distinguish which audiences are more likely to actually become buyers.
To that end, big data enables us to drill down even further to understand and analyze buyer intent -- whether consumers are casually perusing, looking for something else, or are on a mission to find a specific product or service. Once it’s understood what groups are actually looking for, marketers can tailor their content and campaigns accordingly to further reach untapped audiences and drive ROI.
Big data is critical in determining how users got to your site in the first place -- and that includes the keywords they’re consistently using to find you. Big data gives you the ability to find those keywords that provide the most value, as well as explore related keywords that might also be profitable. It also allows you to detect correlations between the keywords that have driven website traffic or led to conversions. And when potential customers do land on your website, big data can also be crucial in optimization efforts that allow them to immediately see the products they want most right away. You can further refine and optimize this kind of targeting by showcasing different groups of products at the top of your site, based on the differing needs of various groups and demographics of site visitors. This capability allows you to maximize ROI with a better understanding of what your audience is looking for and how they’re looking for it -- often resulting in a big boost to conversions.
A McKinsey report found that 30% of the thousands of pricing decisions a company makes every year fail to deliver the best price. For many organizations, this represents wasted effort and a lot of money left on the table that could otherwise have been channeled into your bottom line. Meanwhile, according to the consulting firm, a 1% price increase can result in an 8.7 % increase in operating profits, underscoring that incremental price adjustments based on nuanced insights around consumer behavior, can elicit strong returns and often lead to significant increases in ROI. These adjustments can be determined by the wealth of market and customer data you have at your fingertips, which includes everything from social media engagements and interactions to website traffic and specific PPC campaign data -- because finding the sweet spot for pricing can be vital to the success of your marketing endeavors.
As digital marketers, we are constantly perfecting our campaigns. But we often don’t know what we need to improve upon unless we have insights into the success -- and especially failures -- of previous campaigns.
Big data provides a clear and accurate picture of what went wrong and what went right during your last campaign, where you beat your metrics, and where you missed the mark. This kind of data-driven approach provides a wealth of context for analysis so marketers can make more informed and strategic decisions going forward. With insights garnered from prior customer data, marketers can see where strategies fell short or failed altogether, and can subsequently leverage that data to validate tweaking or even significantly adjusting their digital marketing strategy to ensure a better customer experience going forward. For example, retail clothing stores can leverage insights from previous campaigns to determine when to hold sales, what items to promote or how to adjust prices for the items that will likely be popular. In short, big data is often the only window that gives them the ability to confidently lay the groundwork for even stronger, and more effective campaigns in the future.
Big data can represent a monumental task for marketers, adding copious more layers to marketing goals and campaign analysis that can be complex, time-consuming, and labor-intensive.
But it can also be a digital marketers’ best friend. The insights contained in big data hold the key to greater customer engagement, discovering new and untapped audiences, creating more accurate pricing to maximize ROI and profits, refining the right keywords, and measuring against past successes and failures.
Big data has changed the game for marketers, and as such, the best marketers also have the ability to access its insights. That said, finding the nuggets of truth in a vast sea of data is something that even the best digital marketers can’t do alone. For digital marketers, leveraging dedicated platforms designed to drill down to the most valuable insights will be critical going forward -- especially as they continue to navigate through a vast and growing barrage of data to make their campaigns more targeted, relevant, and profitable than ever before.
You’ve probably seen the headlines calling ad blockers the “death of online advertising," and anyone who works in PPC advertising knows a thing or two about them.
But while ad blockers gained popularity back in 2016, three years later, advertising revenue is as strong as ever. Still, some worry that the rise of ad blockers in popularity and adoption will continue to grow, affecting long-term advertising growth potential.
It’s true, ad blockers can have an impact on your PPC growth potential, but only if you allow them to. In fact, pragmatic advertisers see ad blocking as an opportunity more than a hindrance. And once you understand the real scope and impact of ad blocking features, you’ll also gain clarity on your path of growth.
The first step to overcoming the challenge of ad blockers is understanding why people use them. After all, at least some portion of your target market is using ad blockers.
As of 2017, roughly 40% of laptops and 15% of mobile devices in the US used ad blockers. Globally, more than 600 million devices were using ad blocking software in 2016 -- and all industry predictions expect they will grow.
More than any generation, millennials are the driving force behind ad blocker use, as they’re the most disenchanted with intrusive online ads. This represents a significant and accelerating problem for advertisers, as millennials have already overtaken Baby Boomers as the largest generation. And perhaps not surprisingly, their buying power is also expected to more than double over the next four years. Perhaps ironically, the generation with the greatest potential to drive ad revenue is also the generation paying the least attention to ads.
That said, millenials (and others adopters) actually have very good reasons for why they use ad blockers. According to PageFair’s recent ad blocker report, the number one and number two motivations behind ad blocker usage represent about 60% : (1) Exposure to viruses and malware, (2) Interruption. The biggest takeaway? Nobody’s saying they hate advertising. They simply don’t want to be exposed to malicious ads or be exposed to ads that detract from their web experience.
As a PPC marketer, you know that not all ads on the web are spammy, intrusive, or irrelevant. But, unfortunately, a high percentage of them are.
While it seems ad blocker adoption is an attack on low-quality advertising, the ad blockers themselves are indiscriminate. While you might have a highly targeted, relevant PPC campaign that helps your audience convert, it won’t reach anyone who uses ad blockers.
Ad blockers may seem like bad news for advertisers, but really they’re a response to a problem. Even if your ads are unintrusive and highly relevant to your audience, would you want them to appear alongside spam ads and clickbait? Low-quality advertisements give the whole industry a bad name, discrediting honest, customer-centric PPC advertisers.
If nothing else, ad blockers are a way for consumers to fight back against spam adverts. And they’re more prevalent than you might think. According to a recent AdGuard survey: 57% of web users were attacked by scammers through online ads representing a major intrusion in the advertising market -- a fact not lost on the advertisers.
Even Google, which makes 90% of its money from advertising revenue, created an ad blocker people can use with Chrome in response to research released by the Coalition for Better Ads, detailing the types of ads that make it difficult for people to browse and use websites.
While its ad blocker doesn’t impact Google PPC or social media ads, it does block ads that create a poor browsing experience. The tech giant launched their own ad blocker iAd blockers that may help cut down on bad ads and spam ads. But there’s no getting around the fact that they can negatively impact ad visibility and returns for quality marketers in the process. So what’s the solution?
The short answer is: a change in strategy.
Instead of viewing ad blockers as a hindrance to growth, it’s better for PPC advertisers to perceive them as an opportunity.
There’s a certain group of people who are always going to ignore advertisements, ad blocker or not. So why bother serving ads to people who are only going to ignore them? You shouldn’t. Instead, it makes more sense to invest your time and advertising spend reaching people who are receptive to your marketing message -- people who are actually paying attention.
Also, the idea that one day in the future nearly every consumer will use an ad blocker (like nearly every person with a computer now using antivirus software) is unlikely. Advertising isn’t inherently malicious (like malware), and consumers understand this.
According to Hubspot research:
Consumers are open to the idea of viewing advertisements as long as they’re quality ads that don’t take away from their user experience on the web. So why not make efforts to meet this need with your advertising strategy? If you create quality, relevant, unintrusive ads, you'll show your audience there’s no need to use an ad blocker.
Of course there’s the issue that even if advertisers make these changes, the people using ad blockers are never going to know about it. But that’s not necessarily true either. Ad blocking software is predominantly used on desktops and laptops. In fact, only 22% of people who use ad blockers use them on their mobile devices.
So the same people who have tuned out advertisements on their computers can still be reached with targeted ads on their phones. There’s still an opportunity to reach them with targeted PPC ads, which can be even more relevant when you use advanced mobile targeting features such as location-based targeting.
Marketers who actually understand and appreciate the reasons people use ad blockers are much better positioned to develop an advertising strategy that doesn’t annoy them. Not only will this make them more receptive to viewing ads, but they’ll also be much more likely to convert.
That said, even if advertisers can’t recapture the attention of people who use ad blockers, there’s still everyone else. Ad blocker penetration is still extremely low. At the same time, the number of new internet users is always growing. If the advertising market can eliminate intrusive, spammy ads while providing a more relevant message, new users will be much more willing to see ads than old-time internet users. And the more advertisers can do to prevent their audience from considering using ad blockers, the better.
The truth is, the rapid growth in desktop ad blocking is nothing more than a tough lesson from which advertisers can learn. There are still plenty of opportunities to create better marketing messages for your target audience that address the problem -- particularly for PPC search advertisers. Hubspot’s survey also asked which mobile ad formats people find most valuable or useful, and search ads were the top result.
Consumers have multifaceted needs when it comes to online advertising, but there’s a clear path to success. Focus on the right key areas and it’s possible to grow your PPC revenue despite the rise of ad blockers.
Start with consumer data
If you want to deliver relevant, helpful ads to your target audience, your most important tool is data. The more you understand the interests, needs, and intentions of consumers, the better you’ll be able to target them.
There are many different sources of behavioral data advertisers can mine to gain insights:
First-Party Behavioral Data
This is information your business collects about your audience through tracking cookies and site form fills. Most marketers collect this using their website analytics tools and CRM platforms. First-party data is the most common kind of data marketers use and is often considered the most valuable. But there are other important sources that can broaden your understanding of your target audience and their needs.
Second-Party Behavioral Data
Second-party data is behavioral information collected by other businesses. Form a partnership with another business that targets a similar audience to yours, then you can share behavioral data and insights to get a deeper understanding of the interests and needs of your audience.
Third-Party Behavior Data
Third-party behavioral data comes from publishing networks and data aggregators. They collect information about people’s behavior on other sites around the web. Third-party data is a great way to learn more about consumer demographics and what kind of information they’re consuming on the web. You can use this to optimize your marketing message. Third-party intent data can also help you uncover qualified leads who haven’t yet interacted with your business directly.
You can use these sources of information to flesh out your buyer personas and inform major marketing strategy decisions. Understanding buyer intent can help you better target warm leads, increasing your conversion rates in the process.
Businesses that are customer-centric consider the needs and desires of their audience over their own agenda: getting clicks, driving revenue, etc. And when you really do prioritize your audience, it will help drive your advertising goals in the process.
Consider these top reasons people click on advertisements, according to HubSpot: Two of the top reasons are negative: (1) It was a mistake, (2) The ad tricked me into clicking. Using deceptive strategies to get people to click doesn’t prioritize the needs of the user. And while it may be a great way to improve click-through rates, it likely does little to convince these leads to become paying customers.
What’s the main reason someone would click on an ad by mistake? Likely because it’s intruding into the content they’re consuming. People don’t visit a web page to look at ads, they want to consume the content without interruption.
Advertising networks have made some efforts to make ads less intrusive. Google, for example, now penalizes sites that display interstitial ads on mobile. But unfortunately, this issue is still very common (You’ve probably seen ads that don’t fully block the page but still prevent you from reading the content.)
Serving ads that block or distract from the content experience isn’t a customer-centric marketing strategy. Making your ads less intrusive to maintain a good user experience is. And it’s the job of both advertisers and the platforms serving these ads to ensure audience needs are the main priority. Then the only reason people will click on an ad is because they want to.
Remember, most consumers are open to seeing ads that are relevant to them. To achieve this, it’s not just about targeting people with products or services that interest them. You need to also serve these ads at the right point in the consideration process.
Take for example a woman who purchases a pair of leather boots online. Then the next day she visits another webpage and sees an ad for leather boots. Since she’s already made the purchase, the ad is completely irrelevant. Even if she likes the style and color of the boots in the ad, it’s unlikely she will buy two pairs of boots in two days.
The goal here is to get your ads to appear in that small window of opportunity when someone’s suggested they have purchase intent but haven’t yet made a purchase. Your intent data can help you identify this key timeframe.
In the PPC world, the best way to tackle this challenge is to optimize your reach and frequency. It’s possible to use intent data to set frequency caps, make bid adjustments and optimize your audience targeting to ensure your ads show up when they’re most helpful to searchers.
Most advertisers don’t even attempt to do this because the sheer volume of actionable intent data out there is too large to begin to derive actionable insights. By the time they’ve made the necessary adjustments, the window of opportunity has passed.
The solution that will help you deliver timely, relevant ads to your audience is technology. Use a bid adjustment tool to derive key insights and automate changes in your PPC accounts. Without some amount of automation, it’s virtually impossible to serve the right ads at the right time to the right people.
There are also key advantages when you engage in predictive advertising. Use a technology that incorporates AI and machine learning to understand major market trends before they happen. This way, you can be proactive in your advertising strategy, making necessary changes to gain future ad visibility during these key points of relevance. Because the more relevant and timely your PPC ads, the more your audience will appreciate and respond to your advertising message.
Ad blockers aren’t just an impediment to be overcome by advertisers -- they’re indications of a greater problem with digital advertising. If people are going so far as to install software to prevent seeing ads, then you know there’s something is likely wrong with the digital advertising strategy and approach.
Customer-centric businesses want to serve ads that inform, help and ultimately convert their audience into customers. And customers often appreciate these ads. The reason? They provide relevant products and services when they need them the most, providing a crucial stepping stone in their own buying journey. The good news is that the public is ready to see these ads whenever marketers are ready to serve them.
At the end of the day, it’s about making their customers want to click. Advertisers will start succeeding in their battle against ad blockers when they get to the root of the problem, embracing it not as an obstacle, but as a new opportunity to help meet their customers’ needs.
At Centro, we know that keeping up with the trade pubs and latest trends can be tough and time consuming—so we made it easier for you, and compiled all the articles, reports, and other bits of awesomeness you may have missed, but should definitely read. Bundle up, and enjoy the latest list below!
New York Times passes 3 million mark in paid digital subscribers [2-minute read]
Backed by a large marketing push and it’s new slogan, "The truth is worth it." The New York Times is up to over four million total subscribers, with one million subscribers to its print circulation. And its ad revenues are up compared to last year.
The Battles Programmatic Is Yet To Win in 2019 [4-minute read]
As programmatic continues to grow, its hold on the industry is being held back by three main things: transparency, viewability, and brand safety issues. According to experts, there is still a lot of work to be done in terms of transparency. However, there has been a noticeable shift in the industry, where advertisers are asking for more meaningful measurement and data.
What Advertisers Want to Know About Programmatic [3-minute read]
With an expected $46 billion dollars dedicated to programmatic buying, more marketers are seeking answers on top concerns regarding the space. AdWeek pulled together a list of top questions and answers to marketers’ most pressing curiosities, including how media can be measured, how supply strategy can be improved, and how programmatic ad spend will or should be split between RTB vs PMP deals.
First-Price Auctions Are Driving Up Ad Prices [2-minute read]
Many publishers have now shifted to a first-price auction model which has caused the price of the inventory to go up. In an agency-side test, CPMs were 59% higher in first-price than second-price auctions. From a buyer’s perspective, this price bump suggests that in first-price auctions, buyers are paying more than they should.
5 Things Marketers Must Know About Mobile In Programmatic To Survive in 2019 [3-minute read]
There are many ways you can use mobile in the programmatic world. In order to survive in 2019, this article lists the top 5 things you should know from evaluating ad formats to audience-specific considerations.
Six-Second Ads: It's All About The Context [2-minute read]
Short-form ads are increasingly making a presence as prime video placements for advertisers, driven by the new age of dwindling attention spans. However, the increase in popularity has also required advertisers to rethink video ad spots that they historically cut down from 30 seconds. While advertisers work to retool the length of these ads, they may also struggle with the fact that the efficacy of this shortened format can’t be compared to their traditional predecessors.
Ad-Supported OTT Viewers Incremental To TV [1-minute read]
The IAB released a report, Ad Receptivity and the Ad-Supported OTT Video Viewer, illustrating the demographics of OTT video viewers, the regularity with which viewers consume OTT content and how AS-OTT viewers are incremental to traditional TV consumers. The report notably distinguishes free, ad-supported OTT viewers from subscription-based viewers who don’t see ads.
Facebook: Coming To A TV Near You? [1-minute read]
Facebook is rumored to be working on a project that will include a connected TV (CTV) device. This will include a camera, be similar to Roku or an Amazon Fire Stick, and could potentially stream content from Facebook Watch.
Amazon’s Alexa Finds Its Business Model: In-Skill Purchases [1-minute read]
Amazon has revealed a business model for Alexa developers: in-skill purchases or what they are calling a “consumable.” Developers can now start selling these unlocked features/functionality, premium content, or even virtual games within skills—all of which can be purchased, used and then purchased again.
Domino’s in-house technology push has helped increase online orders [4-minute read]
But does it sell more pizza? The answer is yes! The company saw sales grow 8.3% in their third quarter when they made the decision to bring technology in-house—which got rid of silos and allowed their teams to work closely together by establishing cross-functional groups with their online, offline, research, and IT teams.
Netflix: Engineering to Improve Marketing Effectiveness [19-minute read]
A peek behind the crimson logo, this multi-part blog series by Netflix’s AdTech team shares their methods to effectively working across-departments to create, localize, manage, distribute, measure, and optimize their digital marketing and a growing library of creative assets. It's an impressive read about how they approach promoting their content through testing and personalization to drive new subscriptions and increased viewership. Part 2 is here.
Optimizing your ROI is a challenging, seemingly endless, process in the highly competitive world of search engine marketing (SEM). In order to stay ahead of the curve, digital marketers must continuously anticipate and execute solid strategies aimed at uncovering new opportunities for growth through testing and experimentation. That of course includes implementing best practices around keywords, as well as staying on top of any unanticipated PPC roadblocks - like keyword cannibalization.
With modern technology solutions now empowering SEM professionals to observe, collect, store, and leverage increasingly large clusters of data, there is a growing -- and pressing -- need to embrace new ways of understanding the power of big data and how to leverage it to extract actionable insights.
This inconsumable amount of information has led many of today’s marketing teams to suffer from what Debra Bass, president of Global Marketing Services at JNJ, has termed as Infobesity. The emergence and rapid rise of accessible data has not been balanced by opportunities to support and properly analyze it, making it near impossible from a time and resource perspective to successfully manage thousands (or millions) of keywords in a given portfolio. A costly, oftentimes unrecognized, consequence of this can be keyword cannibalization across entire PPC programs.
Keyword Cannibalization is called such because, in effect, digital marketers are taking a “bite” out of their own results and margins, splitting CTR percentages, links, content, and those all-important conversions between two (sometimes more) pages that should be consolidated into one, while driving up CPC numbers in the process.
In a scenario in which you have the same keywords targeting the same audiences all competing against each other, Google will automatically show the ad that it deems more relevant based upon the ad rank assigned to that specific keyword (ad rank calculated by multiplying your maximum CPC bid by your Quality Score). When a search query pairs with multiple keyword match types, and there are various ads supporting these keywords, the flow of regular traffic for the original search term will markedly diminish as your control over matched keyword behavior becomes severely hampered.
Over time, you’ll begin noticing how select keywords will direct traffic to page x one week and then page y the following week. These unrelated and unexplained fluctuations will lead to inadvertent spikes throughout your program that can prevent you from reaching your PPC campaign goals. If ignored or incorrectly managed, keyword cannibalization will entail a slew of negative outcomes, from diminishing page authority to rising CPC costs and decreasing conversions.
Just how you deal with this headache depends on where the problem has its roots. Once that is determined, there are four possible ways to resolve this issue.
Create One Authoritative Page
The most straightforward solution is simply to convert your most authoritative webpage into a one-stop landing page that links to a series of variations that all fall within the same field of your target keywords. A highly effective, high converting landing page can become the foundation for creating a successful lead generation strategy.
Employ 301s Liberally
If you’re splitting your CTR between a collection of moderately relevant pages, essentially you’ve turned them into competitors. Not ideal. To counteract the problem, digital marketers can use 301 redirects to link the pages of lesser importance to a single definitive version that is no longer fighting for views and SERP ranks.
Build New Landing Pages
Creating multiple landing pages with only slight keyword variations might, at first, appear to be thinning content. While this may be true, ultimately the more landing pages you have on your site, the more opportunities there are for visitors to turn into leads. A recent study by HubSpot revealed that upon increasing their number of LPs from 1 - 10 to 11 - 15, companies reported a massive 55% lift in leads. Go the extra mile and develop 40+ LPs, and you could be looking at a 300% uptick. Those are compelling numbers.
Get Creative With New Keywords
This is where SEO comes in. Content-rich pages should be utilizing a highly diverse set of keywords that can broaden your reach, with particular attention paid to the long-tail. Naturally, you will draw less traffic with a long-tail keyword, but the audiences you do capture will be extremely valuable: more focused, more committed, more targeted.
With companies today trying to dominate SERP real-estate in their respective fields, keyword cannibalization is more common now than ever before. In an ironic twist, it is the savvy marketers attempting to harness the potential of optimized SEO campaigns who are falling victim to its traps, unable to comprehend Google’s myriad technical languages.
Through a combination of implementing the right technological systems and exercising best practices, keyword cannibalization can be eliminated, though, and you can ensure your ads are reaching your desired audiences. Google is very smart when it comes to identifying, deciphering, and then appropriately ranking content on its pages, so if you’re not on top of your keywords, your business could be suffering - missing out on leads and wasting valuable marketing spend. While it might seem negligible, finding tricks to avoid keyword cannibalization will likely ensure that you see higher ROI, lower CPC costs and more conversions -- and continue to benefit from all of the tangible rewards of your PPC efforts.
These days "big data" isn’t just a buzzword — it’s an integral part of the sales and marketing narrative. Data is what creates context, meaning and value for PPC advertising campaigns, while enabling marketers to generate metrics that can be measured against monthly, quarterly and annual goals. Thus, every good marketer knows the potential value of big data and its power to help achieve comprehensive business objectives. But only great marketers will know how to break it down to truly take advantage of the vast array of customer insights it offers. And one of the most important types of data for driving sales and marketing insights is intent data.
According to DemandGen’s 2018 State of B2B Intent Data Report, 35 percent of B2B companies say they plan to start using intent data insights within the next 12 months. Despite it's enormous value, intent data isn’t leveraged as often as you might think, although its use is increasing year after year as more marketers continue to realize its potential. However, few marketers completely understand the wealth of available intent data at their fingertips that can be leveraged for business insights and more intelligent marketing decisions. And as such, even fewer are equipped to harness insights from it that will increase ROI and boost conversions.
We break down how you can make intent data work for you and your campaigns.
At its core, buyer intent data is information about your prospect’s behavior before they even enter your sales funnel. When prospects click on your ad, visit your site, read your blog, or fill out a form, you consider these as signs that they have some degree of purchase intent. But in reality, the process begins before prospects ever interact with your business.
Buyer intent data is information that incorporates what research prospects are conducting online, with a focus on determining interest in certain topic areas. For example, when a consumer reads a news article online, they’re considered interested in that topic. Sales and marketing teams can then use that data to better reach out to prospects and deliver a targeted marketing message. And marketers who know how to harness intent data are in a position to significantly improve conversions and revenue.
Buyer intent data is collected through IP addresses and browser cookies, which can be parsed into two categories: first and third party.
First party intent data is normal engagement data that can be accessed by most marketers. Using your marketing automation platform, it’s possible to collect important information that illustrates a lead’s point in the sales funnel. This includes information like site pages visited, time on page, links clicked and forms filled -- all of which illustrate a prospect’s level of purchase intent.
First party intent data can come from known leads you’re tracking or from anonymous visitors who haven’t filled out a form on your site. Regardless of type, marketers use this information to understand what content and touch points are most important to their sales cycle. You can also use buyer intent data to create lead scoring models to illustrate which of your prospects are ready to buy.
Third Party intent data comes from sources other than your website, such as publisher networks. Most marketers who use third party intent data get it from a data aggregators such as Bomborda, 6sense, or Leadspace. These data aggregators also use IP addresses, tracking cookies and form fills to collect consumer behavior data from places across the web, such as product review sites, popular online magazines and blogs.
They then categorize this data into thousands of distinct topic areas that marketers can choose based on its applicability to their target audience. They then have access to information like the types of articles people are reading, site searches, and content they download, among other behavioral information. While third party intent data is used less frequently among marketers, it contains a lot of potential to drive insights so you can work toward your sales and marketing goals.
Businesses that use a combination of first and third party intent data can drive insights to improve a wide range of initiatives that particularly benefit marketing and sales teams. Specifically, marketers can leverage both internal and external data insights to create more relevant content for their audience. Meanwhile sales teams who understand what certain accounts or prospects are researching beforehand can use this information to help drive them down the sales funnel.
Some common uses for and benefits of intent data include:
It’s well established that intent data is already widely used to improve content marketing and other lead nurturing initiatives. But its benefits for advertising are often overlooked or underutilized. Each action a person takes online is a data point that advertisers can potentially leverage to create a more relevant and precise targeting strategy.
Here are just a few of the many ways advertisers can harness intent data to boost performance:
Long-tail keywords have long been an important asset for search engine marketers to target because of their relevance. Among other things, they’re more descriptive, so they do a better job of implying buyer intent. But traditionally it’s been difficult for advertisers to target long tail keywords because they tend to have a much lower search volume. In order to achieve the same ad visibility as they would with high volume keywords, brands would need to target and optimize for an exponential number of long tail keywords.
That said, automated bidding technologies have become the perfect solution to the problem, so use your third party intent data to understand what kind of long tail keywords your audience is searching for. At the same time, first party intent data is an often overlooked source of relevant information. As such, dig into your own website analytics to find relevant, fresh information for keyword research.
From there, use this information to target keywords and create more relevant ads. Automated bidding makes it possible to target large numbers of long tail keywords and make minute adjustments to improve campaign performance at scale. The right technology will also offer flexibility to help you automate changes based on your preferred PPC benchmarks — revenue, conversions, or other relevant metrics.
Marketers can use intent data to create more relevant ads for their audience, whether they’re known leads or anonymous prospects. Intent data aggregators make it possible to identify qualified leads based on things like device ID and domain, among other factors. You can then use this information to place the right kind of ads on user devices, for example.
Advertising can also benefit from the same automation processes mentioned above. When you use intent data coupled with AI technology, it’s possible to both better understand your audience for targeted advertising and automatically trigger relevant advertising campaigns to reach them.
For example, if your intent data shows an account is researching a specific keyword, you can automatically customize an advertising campaign related to that topic. While it is possible to make these kinds of adjustments manually, automation gives you the benefit of speed and precision, delivering your relevant advertising message before competitors can do the same.
Intent data carries a lot of power to help boost ecommerce performance when leveraged properly.
That said, the ecommerce customer journey isn’t what it used to be. Instead of centralized shopping, consumers are turning to resources across multiple channels and platforms to make the best buying decisions for themselves. And while the journey is fragmented, it’s full of data points that businesses can harness to optimize their strategy. Intent data used with the right technologies can help improve advertisements, retail efficiency, and profits overall.
Intent data has a lot of potential to help improve different areas of marketing. But to take full advantage of it, marketers need to approach it with the right perspective.
Most marketers today already have access and utilize some of their first party intent data. So when they decide to harness third party data, it’s common to start ignoring these internal insights. But information you gain from your own site visitors are just as important and relevant as from other sources. Thus, the key to success in your SEM strategy will be to combine first and third party intent data to drive more informed insights. This will help improve your targeting of individual accounts as well as your overall marketing strategy.
There’s only so much you can do within account based marketing to personalize your targeting strategy. As a template, it already needs to be highly targeted. So focus on using intent data insights to flesh out and better understand your target personas in general. If you focus all your energy on targeting the accounts you can see, then you might miss out on prospects that don’t show up in your data stream.
In the same vein, harnessing intent data isn’t just about targeting low hanging fruit. Sure, it can help you identify new qualified leads that are warm to your products and ready to convert. Giving them the final push across the finish line is an easy way to drive revenue for your business that you attribute back to your intent data insights. But don’t let that be the main focus of strategy.
The last challenge that stops marketers from taking full advantage of intent data is scalability. Yes, it’s possible to use intent data to better understand individual accounts, review the insights, and then make choice marketing decisions by hand. But that’s rarely a scalable strategy.
That’s what makes the applications of intent data to advertising so compelling compared to its other use cases. With the help of automation, it’s possible to create rule-based changes to your advertising initiatives based on intent data insights in real time. Not only can you create more targeted ads, you can also make bid adjustments based on data insights. This can help increase your ad visibility while reducing wasted ad spend in the process.
Ultimately, the keys to getting the most out of intent data insights include:
Tools that use data science and machine learning to automate actions based on deep funnel insights are uniquely positioned to help businesses fully utilize all of the advantages that intent data has to offer.
Of all of the benefits intent data offers to your PPC program, it likely goes without saying that you’ll have access to a host of new opportunities and insights about customer behavior -- all of which you can leverage to create more focused, targeted campaigns that produce higher ROI. Capturing new insights has copious advantages that you likely haven’t even realized -- and many of them will give you a big leg up over competitors.
When used correctly, intent data can open up a wealth of insights into new leads, better personalization, improved content marketing, better lead prioritization and myriad other benefits that will only make your campaigns stronger, more profitable and sustainable going forward. The rewards for accessing intent data are numerous and undeniable. And like a hidden treasure, finding out how to dig them up and keep them at your fingertips so that they can work best for your PPC campaigns will be your next step.
One of the best ways to widen your audience, increase your perceived expertise or generate profits for your business is to advertise on Amazon. The eCommerce giant is is now the third largest advertising platform in terms of ad revenue, placing it squarely behind tech behemoths Google and Facebook. For brands, this development is a powerful signal that they’ll have little room to ignore Amazon as a viable revenue generator going forward. That means brands will need to hone and refine their Amazon ad tactics to stay relevant and competitive.
What will you need to make your Amazon ads stand out? A lot. And chances are strong that you’re doing it all wrong. Most companies who sign up to market products on Amazon soon discover that they don’t know how to create ads, write copy or bid effectively. This is true even for businesses that have large budgets and knowledgeable teams on the case. So, it’s time to fix that.
Before anything else, you’ll need to reevaluate the very foundation of your Amazon ad tactics marketing plan. Among other things, you should be thinking about are the size of your keyword list, the range of your ad types, how to optimize your copy, the in-copy sales words you should be using, and how to analyze your ads. You should also be thinking about how to use Google AdWords outside the Amazon ad tactics marketing platform to drive people to your company's products or services.
And in addition to a thorough understanding of how to effectively leverage Amazon ad tactics in your marketing – as well as AdWords and other useful marketing tools off-platform -- you’ll also need a solid grasp of the mistakes you’re making in your Amazon marketing approach, and how to fix them.
Copywriting is far more difficult than many people assume. Lots of folks can write well. Many others can write decently, while others can string an effective sentence together – enough to impress in the boardroom or breakroom.
But to write well and to create compelling copy are entirely two different things.
Chances are you already have a copywriter or two on staff, but if they're not used to writing Amazon descriptions, it's time for a refresher. The truth is, writing website copy or long-from content optimized for search engines is not the same as writing a good description. Similarly, even if your ad staff knows how to write great PPC creative, that doesn't mean they're well versed in descriptions that sell. In the end, both PPC and SEO have the same goal as Amazon – using words to create an emotional experience and get readers to click – so you should be able to parlay those skills into writing descriptions. This, however, doesn’t happen without practice.
The goal of an Amazon description (and all copy) is simply to move the reader from one line to the next. This is the powerful advice offered by Joseph Sugarman, one of the top copywriters in the world, in his esteemed Adweek Copywriting Handbook, a veritable Bible for the copywriting world.
Among other things, Sugarman offers actionable tips on tweaking words so that they create an emotional experience within the prospective reader -- an experience that takes them from one line to another. It’s the type of experience that creates closeness between you (the copywriter/author) and them (the browser/consumer), one that will eventually lead to moving the reader down the funnel, and eventually, a sale.
If you’re still not sure how to make this happen, that’s okay. Try this formula for writing good descriptions on Amazon, and consider a course on selling ads, such as Mark Dawson’s Self Publishing Formula. And practice, of course.
On a final note regarding your description copy, it’s important you don’t go on too long. Around 500 words is the max for good Amazon description copy. That’s because, even if you manage to pull a prospective reader through that many words, you probably can’t keep them on the page for much longer. Eventually, it’s time to make the sale. Check out that description formula for the best way to do so.
If your company wants to sell products on Amazon, you need to use the right words. Your marketing department ideally has experience writing short, punchy ads, which will translate well to Amazon's restrictive ad environment.
That said, you still need to turn that browser/surfer into a reader. So how do you do that? You use the right keywords in your ad copy.
Again, copy makes a big difference overall, but sometimes all it takes is a single word to hook that person. Some of the most effective include:
Now, don’t feel as though your ad copy has to contain all of these. Choose two or three to use strategically. Also, remember that you have much more space in your description (unlimited, basically), so you can always use them in there.
Most likely you already know that succeeding with ads is a volume game. If you don’t run enough ads, you don’t gather enough data. If you don’t gather enough data, you can’t tell which approaches are working and which aren’t. And if you can’t tell what’s working, you can’t replicate the successes and ditch the failures.
Plainly put, when you run a few ads here and a few there and “hope for the best,” you’re likely crippling yourself. You may as well not try, because your company will not see the bottom-line increases you're looking for, and will not reach the wider audience you need to build your brand.
Here’s what you need to do instead: Make proper use of, all of Amazon’s marketing tools then give your sales a boost by driving external as well as internal traffic to your books.
Amazon has three types of ads:
We explain each of these ads in more depth here, and each has its own set of benefits. Sponsored product ads allow you to create massive keyword lists, then bid on them, targeted up to a thousand in a single ad.
Product display interest and product display product ads, on the other hand, let you add a significant number of categories or products, respectively, so you can always target a wide swath of shopper interests.
Each of these ads has countless different combinations of factors, so it’s important to run enough of them so you can test those factors effectively. Like any other marketing platform, Amazon’s marketing service is impossible to game from the get-go. Your only hope is to run ad after ad, tweaking and adjusting as you go along until you find an approach that works best.
Make sure when you adjust your ads and re-run them that you’re not changing too many variables at once. Any researcher will tell you that you can only change one variable at a time without confusing your results.
One example: If you have a successful ad and want to make it more successful, you should run it again in tandem with ads that adjust the price both up and down, to see if you can maximize your ROI. You could also adjust the copy on the assumption that the keywords are bringing the benefits, to see if you can get even greater sales volumes.
What you should not do is change price, copy, headline, interests, and everything else all at once.
Keep in mind that Amazon ads aren’t the only type. Many people use Facebook and AdWords marketing to drive readers to their Amazon sites, on the assumption that lots of potential readers live on the web and on social but aren't on Amazon regularly. This is absolutely true, and once you’re good at running Amazon ads, you can branch out to those as well. Alternatively, if you're already well-versed in PPC and social ads, you can translate those skills to Amazon.
Either way, focus right now on mastering your Amazon game. You need to use enough ads, enough of a variety of ads, in enough different formations, that you can make serious sales and justify continuing to spend company dollars this way. If you're a publishing company already spending lots of ad dollars on Amazon, prepare for a bit of a hit in your ROI while you figure this out, but don't shy away: As long as you put in the time, Amazon works.
Sponsored product ads depend heavily on using the right keywords. Some people leave it there, though, bidding on 10 great keywords and hoping for the best. The problem is that those 10 words should more accurately be called 10 “really really popular words for which you’ll never win the bid against other, bigger companies.”
Instead of trying to win bids on the most popular keywords, it’s smarter to build huge keyword lists that contain lots of longtail search terms. Naturally, you’ll never be able to come up with so many on your own, which is where Publisher Rocket comes in.
This impressive piece of software costs only about $100 and delivers enormous keyword-scraping power right to your fingertips. It interfaces with Amazon’s search engine to find the most popular words and phrases people are already searching right on Amazon. It will then organize them, categorize them and deliver the relevant data to you when you search for it. To use KDP Rocket effectively, you need only:
You can do all of the above correctly, however, and still not get very far if you don’t know what to make of your ad results. Analysis is imperative, because it tells you what’s working and what isn’t – in other words, where you should spend more money and where you’re simply wasting it.
At the end of the day, though, lots of businesses simply don’t have the bandwidth or headspace to do copious in-depth analysis. Instead, they struggle through half-hearted advertising campaigns, trying and failing to run the numbers in such a way as to come up with meaningful metrics on which to base new campaigns.
Sound familiar? If so, you’re in good company. Many businesses have at some point tried their hand at PPC marketing, only to find they can’t make head nor tail of it. Even large companies with considerable marketing departments struggle to make their ads elicit sustainable ROI.
The problem is twofold: 1) You immediately drown in data, and become so overwhelmed you don’t know how to proceed, and 2) Because you don’t know how to proceed, you often end up just throwing ads at the system and hope something sells. As with most endeavors, this approach rarely works, and the exacting nature of Amazon marketing ads is no exception -- which is why so many people give up altogether.
Creating a sustainable Amazon ad tactics strategy takes a lot of honing and refining, as well as copious trial and error. But few tactics are as effective as powerful ad copy. Whether it’s reaching users with efficient, streamlined descriptions, strong calls to action, or well-placed keywords, your ad content is an extension of your voice that will be key to either connecting with customers or losing an opportunity. By learning to effectively use the right words to amplify your message, you will not only help spark consumer interest but be able to keep it throughout the entire customer journey.
From connected cars and household appliances to what we wear, the Internet of Things (IoT) has fundamentally changed the way we live. These days, it’s expected that connected devices and technologies will unobtrusively, and sometimes stealthily, collect data on our vital functions, what we do, where we go, what we share, what we believe, what we buy, who we know, how we move and even what we eat. It may come as no surprise, then, that the majority of industries and market segments have found and are continuing to find ways to leverage that data to their advantage - into conversions, higher ROI, and ultimately profit.
The advertising industry is no exception. Undoubtedly, IoT has that same predictable but revolutionary impact on advertising as it has had on manufacturing, automotive, and healthcare. For digital marketing and advertising, IoT can clearly help create new customer opportunities. But its potential runs much deeper, providing data and insights into new, unexplored markets and demographics, as well as how businesses research their target markets, the ways they reach them, and how they analyze and assess their efforts.
The Internet of Things (IoT) is a concept that refers to how devices can store, analyze and share information over a network without the help of people or other computers - all made possible with a wide variety of devices that have computational and networking capabilities, including mobile phones, wearable and medical devices, vehicles and home appliances.
The Internet of Things - that is, internet-connected - devices essentially serve as sensors that can send data through a network using the internet, Bluetooth, or other connected technologies. Thus they have the ability to collect, send and receive information that people can act on. And that list of devices is almost endless - and continually growing.
A few real-world examples of IoT include:
While connectivity is nothing new, it’s become so ubiquitous that it has created new opportunities for building applications and services. That means, as with regular devices, the host of real world applications for IoT devices open up a plethora of new doors for digital advertising.
IoT has already penetrated a lot of industries - including online advertising. That said, up until now, IoT has often been overlooked by most marketers. But that’s been changing as digital advertisers have started uncovering marketing opportunities around IoT.
For example, Johnnie Walker has a Blue Label bottle with built-in electronic sensors that can tell if the bottle has been opened and where it is in the supply chain. Malibu, another drinks company, takes it a step further, using their “connected” bottles as a digital touchpoint to promote exclusive content.
While these types of IoT applications to advertising are definitely impressive, what’s the practical direction for marketers to follow if they want to start taking advantage of IoT for their business?
The truth is you don’t need to turn your products into IoT devices to benefit. While they might not make it to the front page of TechCrunch, there are actually plenty of real ways marketers can start using IoT for better online advertising.
As previously mentioned, IoT makes it possible to track and access much more data about individuals. When approaching them as consumers, advertisers can consider each data point a touchpoint in the customer journey.
The sheer volume of actionable data that can come from IoT devices is enormous - to the tune of five quintillion bytes of data every day. And the potential applications and uses of IoT data are endless for advertisers that know how to harness it. IoT data can reveal to advertisers who bought a product, where they bought it, and potentially what they did with it after purchase. Among other things, this information can be used for customer relationship management, as well as informing new product development. It can also be used to optimize ad marketing messages while potentially delivering them through new channels.
Specifically, deep funnel insights derived from IoT data can tell businesses who has buying intent for certain products and when. IoT devices themselves can also tell advertisers a lot about the people that use them - someone who wears a fitness watch, for example, could be targeted with advertising for sportswear clothing. Someone who owns an irrigation controller could be targeted with advertising for a garden maintenance service. The possibilities are almost limitless.
Suffice to say, people who carry and regularly use IoT devices are easily differentiated from the crowd - which in turn can generate significant opportunities to better target marketing messages to individuals both online and off. The reason? IoT devices provide important personal details that advertisers can use to better personalize their messages. One of the most basic examples is location-based ads, from data leveraged from users’ mobile phones and other devices.
Google’s local search ads, for example, are already a widely used application of IoT in advertising, making it possible to target specific audiences within certain areas of a country or within a radius of a certain location. When people make local searches using their mobile devices, they’ll be subjected to relevant ads based on their current location. PPC advertisers can then target their ads to specific locations (usually their local store), and even optimize their ads by targeting keywords that illustrate user intent.
But real-time, contextualized personalization doesn’t have to end there. Why not factor in information like time of day, or the person’s physical condition? The possibilities are endless.
The key difference between personalization using IoT devices and other strategies is contextualization. It’s true that marketers don’t need to tap into someone’s fitness monitor to know that they’re health conscious - the fact that they purchased it in the first place could tell them that. Marketers can also tap into third party intent data from publishing networks to learn more about the specific health interests of a lead.
So why rely on devices themselves to collect this information? The answer is better, individualized contextualization. Take these examples:
None of those targeting strategies are possible with even the most advanced prospect research, online or off. But they can be when marketers harness the power of IoT.
How these marketing messages are delivered is another important aspect of the potential for real-time, contextualized personalization. The advertising space changed when it became possible for online advertisers to market to people on their mobile devices instead of just their computers. Now it’s happening again with other IoT devices.
Now, it’s possible for marketing messages to come from the IoT devices themselves. Your washing machine will tell you when you’re out of detergent and add it to your shopping list for you. Your car can suggest a nearby auto center when you’re due for an oil change. Amazon is already taking advantage of this as well, using smart home devices to suggest more of their products to consumers.
IoT has other benefits for advertising, beyond better targeting opportunities. The wealth of data the IoT ecosystem provides also makes it possible to learn more about the impact of your advertising on consumer purchase behavior.
This is especially important for businesses that advertise online to drive conversions offline. Businesses that sell exclusively online can rely heavily on metrics like click-through rate and onsite behavior to measure performance. But businesses that use local search ads (for example) to encourage in-store visits have a serious gap in sales funnel visibility. That’s where IoT can come in.
What if you could deliver an ad to someone’s mobile device, and they go on to use contactless payment when they purchase in your store? This data would make it possible for advertisers to understand important behavior points like:
And it’s not just location-based businesses that can benefit from offline data. Even an e-commerce store will want to better understand when, where, how frequently, and potentially why people choose to make purchases from retail stores instead of online. IoT also makes it possible to know when people research a product offline then ultimately purchase it online - all parts of an advertiser’s sales funnel that have significant blind spots without the help of IoT devices.
Advertising performance today often relies too heavily on online behavior, mostly because they lack a scalable way to monitor performance outside of this digital space. IoT makes it possible to expand the web of understanding beyond this.
As the number and kind of IoT devices continue to grow, so will this web of information. Devices that were previously never connected to the internet (fridges, TVs, thermostats, etc.) are now coming online, providing unique opportunities for different types of businesses to benefit. Advertisers can better track the impact of their TV commercials on online purchase behavior, for example. Or grocery stores can better understand their customers’ shopping needs using information from their smart fridge.
It’s true that the practical applications for advertisers are still being discovered. But interconnectivity is expanding every year. And once a business can track performance of all their marketing touchpoints simultaneously, they’ll have full funnel performance insights to help improve critical components such as advertising messages, targeting strategies, customer retention and customer service, as well as many more benefits at their fingertips.
As discussed earlier, IoT provides an enormous amount of new data that advertisers can use to better understand their complete sales funnel. But this data is only useful if you can follow four key steps:
And it’s all easier said than done. The more data that comes in about your audience, the less likely you’ll have the capacity to handle it. But if you use the right technologies, it’s possible to fully harness the data IoT offers for better strategy optimization.
It’s possible to use machine learning algorithms with big data to generate predictive analytics. Businesses do this all the time with third-party intent data, using these insights to drive automated changes to optimize their advertising campaigns. It’s possible to incorporate IoT data into this strategy as well, seriously impacting the scope of possibilities with predictive analytics.
Predictive analytics use a combination of data mining, statistical modeling, machine learning and artificial intelligence to make predictions about future events. And real-time reporting makes it possible to identify actionable trends in data, allowing marketers to make decisions to optimize their strategies beforehand.
Bid optimization capabilities are a key benefit of this technology for advertisers. By leveraging data insights provided by IoT devices and other big data sources, it’s possible to make small, ongoing PPC bid adjustments to optimize advertising campaigns. And because it’s automated, it will ensure you’re only bidding the necessary amount to get the ad visibility you need and drive the highest ROI. That means not wasting ad spend because you can’t drive the right insights at scale.
These are things that are already possible with IoT data and the right technologies. But the future is bound to bring even more optimization capabilities as both predictive analytics and IoT grow. Consider the possibilities if predictive algorithms could add individual location data to their mix. Then advertisers can automate targeted ads toward individuals at a time and place that’s most relevant to them.
It’s well established that IoT has the potential to make advertising much more intrusive. But given consumer sentiment around ads today, it’s probably not the best way to be utilizing the technology. Nobody wants their Amazon Echo to start blurting out product suggestions based on conversations overheard in their living room.
The real benefit of IoT for advertising is more and higher quality data, enabling advertisers to create granular insights and more relevant and better targeted ads that are more aligned with their customers’ needs. That said, those insights and unique personalization can only be realized if marketers have the time and resources to harness this data to its full potential - which means applying intelligent technologies that have the ability to separate, analyze, and create value from it that can be applied strategically to your short and long-term PPC strategies to maximize ROI, boost profits and create value for your campaigns.
New IoT technologies are constantly generating raw, untapped data that can be leveraged in almost limitless ways. The data is already there. All you have to do is find the right technology to unlock its true potential.
If you’ve glanced at the headlines recently, you likely know that Amazon has far exceeded expectations when it comes to its digital ad business, and is set to be the world's third largest digital advertising platform, according to market research firm eMarketer.
After revising its previous estimates, eMarketer now predicts Amazon will gross $4.61 billion in ad revenues in 2018 -- a vast increase from previous projections that had it $2.89 billion, attributed in part to a spike in growth from a reclassification of revenue. According to eMarketer’s revised estimates, the online retail giant will surpass Verizon Communications Inc.’s Oath and Microsoft Corp, firmly placing it in the No. 3 spot in the world for digital advertising revenue behind Google and Facebook.
That said, it still has a ways to go before reaching the league of either of its archrivals. But while the online retail giant still comprises only about 4.15 percent of total U.S. digital ad revenue, it is experiencing a steadily growing upward trajectory, while Facebook and Google revenues are simultaneously in decline.
That means it will also be actively be taking share from its two major competitors for the foreseeable future. By 2020, eMarketer predicts that Amazon’s growing digital ad business will continue to increase by more than 50 percent annually through 2020, ultimately totaling 7 percent of all US digital ad spending, while Facebook’s and Google’s share will decrease to 20.8 percent and 35.1 percent respectively. While Amazon isn't yet considered a serious threat to the Facebook-Google digital ad duopoly, it appears that the global retailer is nipping at their heels, and is on track to becoming a serious contender in this space.
eMarketer cites strong “organic growth” as one of the most significant reasons for Amazon’s rising digital ad revenues -- which aren’t destined for a slowdown anytime soon. In short, companies are increasingly buying ads on Amazon. And they’re clearly reaching the right audiences.
And over time, merchants will be under increasing pressure to buy up even more advertising space to compete with other merchants, lest they lose visibility in the search results to sponsored listings. As such, Amazon is now taking advantage of this wide open playing field as every merchant on the platform could potentially be an advertising customer as well. Looking ahead, that untapped potential will continue to be a powerful driver for growth in its ad business as merchants look to capitalize on Amazon’s copious search traffic.
So, what can Amazon’s bullish strides in its digital ad business be attributed to? As with almost anything, it turns out, there’s no one simple answer. But its continued digital ad success can be sourced to the right mix of a rapidly evolving digital advertising environment, some astute accounting changes and a clear, holistic understanding of their customers’ buying behaviors and relationship to technology.
It’s Easier Than Ever to Buy Ads on Amazon
It wasn’t that long ago when consumers regularly labeled Amazon’s ad buying process as confusing, frustrating and difficult. That all changed in September, when Amazon announced that all of its ad buying and reporting would fall under the new, fully consolidated umbrella dubbed “Amazon Advertising.”
The comprehensive Amazon Advertising moniker now entails Amazon Marketing Services, Amazon’s suite of CPC ad formats; Amazon Media Group, which sells display advertising on Amazon properties, and Amazon Advertising Platform. In addition, Amazon has recategorized its former Headline Search ads -- a CPC format that serves up multiple products on search result pages -- to Sponsored Brands.
Many of Amazon’s accounting changes reclassify several advertising services from cost-of-sales to revenue, and, according to eMarketer, were the primary drivers for eMarketer’s adjusted projections. But the net-net is that Amazon has streamlined and simplified its entire digital advertising portfolio for its customers, making ads more efficient, accessible and targeted, increasing their value and giving a big boost to advertisers’ ROI.
Users Start - and End -- Their Product Searches on Amazon
Once upon a time, Amazon was a place that would-be consumers landed after extensive and exhaustive product searches. Not so anymore. Now more than ever, users are skipping over Google, which might eventually be perceived as a sort of digital middleman. Instead, they’re going right to the source -- Amazon -- to begin their product journey -- which bodes well for advertisers looking to target specific demographics and other types of dedicated shoppers. And because Amazon is first and foremost an online retailer, consumers are ending that journey there too with a purchase.
Amazon Expanded Its Mobile Advertising Business
With the explosive reliance on smartphones as consumer buying tools, retailers need to be heavily investing in their mobile advertising strategy. This hasn’t been lost on Amazon, which has bulked up its mobile ad business to accommodate an anticipated groundswell of users. Thus, in its report, eMarketer also projects that Amazon will increase its mobile ad revenues 242 percent to $1.61 billion in 2018, which will give it 2.1 percent market share of the mobile ad market. Naturally, its mobile ad play will only serve to build out its expansive digital ad business.
Amazon Offers Increased Consumer Insights
No one can argue that better data means stronger insights -- and that includes Amazon’s. Another reason Amazon is increasingly attractive to advertisers is because it provides access to consumer purchase data. And advertisers looking for insight into the impact of their ad buys on purchases have that information right at their fingertips. Google and Facebook, on the other hand, don’t offer the same type of granular insights. And in an increasingly data-driven environment, advertisers need every ounce of insight to refine their digital advertising strategy, better target their consumers and gain an edge on their competitors -- or risk being left behind.
The Power of Voice
All this growth is great for advertisers. But there’s yet another factor that might contribute to Amazon’s rise in the digital ad space -- voice. It’s no secret that Alexa-powered devices like the Amazon Echo are becoming increasingly common household items, and as such, the eCommerce giant has a strong potential to lead the charge in delivering voice ads to users.
Currently, Alexa directs inquisitive users to products that are well-reviewed on its site, as well as available on Prime. But taking that a step further, Alexa’s “expert” guidance could potentially direct users to well-placed programmatic voice ads, according to a recent report from CB Insights, opening up even more opportunities for advertisers to more acutely target desired audiences.
So, What Does All This Mean For PPC?
Ultimately, Amazon’s steady upward growth trajectory opens up a host of new opportunities for PPC advertisers. The biggest reason? PPC advertising isn’t just about targeting more consumers or bigger audiences -- although that often contributes to the success of a campaign. But at the end of the day, it’s about optimizing marketing efforts to target the right consumers -- the ones that will not only click, but convert.
And if there’s anything that Amazon can do well, it’s gathering dedicated audiences. In general, people don’t go to Amazon just to surf or browse. Many -- perhaps the majority -- go to the site with a mission. They basically know what they want, without perhaps knowing the right brand, style, size or color that would specifically suit their tastes. Thus, Amazon turns up an array of products that it deems are a close fit to the users’ description. As more users leverage organic search to narrow down their choices, their attention will be increasingly drawn to paid search opportunities as well. What’s more, Amazon is paying attention to the way today’s consumers shop, and is doubling down on creating new and unique channels through which advertisers can reach those highly targeted -- yet untapped -- audiences.
Amazon’s comprehensive advertising business and means of gathering the right audiences aligns well with the principles of PPC that include increased efficiency and ROI. With a streamlined organization, as well new platforms, technologies, and data insights with which to keenly vector in on both advertisers and buyers, the online retail giant will likely be making noticeable dents in this space in the near future.
And PPC advertisers will be watching its path with interest.