Remember 1994? Forrest Gump topped the box office, Green Day were the new punks on the charts. And the first digital banner ad appeared.
It didn’t take long for cookies to come along as a way to track banner performance, followed shortly by ad servers and true programmatic advertising. And if you think about that time, the programmatic landscape was littered with various players all racing to stay ahead as the technology rapidly developed. Their differentiated solutions would eventually fade as the industry consolidated, resulting in a few competitors with near-identical capabilities.
For a short time, programmatic and ad networks were the wildest party in town. Now, over 25 years later, party time seems to be here again as digital advertising technology takes a cookieless spin.
What should we expect in 2022?
Personalization will continue to be a top priority as the journey for instantaneous feedback and privacy-centric—and accurate—data will be big trends this year.
Probabilistic models can help drive relevant experiences that lead to conversions, but they’re only as good as the methods behind them. Marketers and data science experts will need to apply AI to drive machine learning so that models are able to scale properly and generate desired outcomes.
These models are also only as good as the data they use. Any new data coming into the model must be instantaneous, accurate and easily digested. That’s easier said than done as good data gets harder to obtain.
With cookies going away and walled gardens continuing to pop up, advertisers, brands, publishers and tech providers are scrambling to capture as much first-party data as possible across the ecosystem and figure out how to expand audiences beyond what is known. Zero-party data—which is explicitly provided by consumers, usually in regard to how they want you to communicate with them—can be helpful, but it’s also limited in its ability to be collected and scaled.
So, how will buyers and sellers operate in these new cookieless environments?
Something new in the cookie jar
Cookies won’t just disappear; they’re going to be replaced. You can’t serve a relevant ad if you can’t identify the user, if not on a personal level, then at least with an understanding of their behaviors, desires and preferences.
In a post-cookie world (we’re going to need a new buzzword for this era, aren’t we?) marketers and data science experts must figure out how to track users across platforms while respecting privacy. More than likely, this will lead to a rise in the use of identity (ID) graphs to recognize individuals across channels and devices.
There are currently myriad options in the ID graphing space: RampID, Google FloC, Unified ID 2.0 and more. These technologies are making big promises to deliver greater accuracy and personalization than cookies while providing more control, transparency and privacy for users.
But the variety of available technologies creates challenges. When brands, advertisers and publishers are all using different solutions, it’s possible (and likely) that they will be unable to share relevant data with each other.
Simply put, everybody will try to talk to each other about peoples’ behaviors in different languages and most of them will be unable to understand.
This plethora of options and technologies harkens back to the beginning of programmatic advertising. Eventually, brands and advertisers came to understand which solutions could yield the results they wanted. The larger companies bought up the smaller companies, leading to consolidation and more simplicity across the industry.
Though it’s still anybody’s guess as to which of these new technologies will become the industry standard, marketers should expect that—as before—the many will become the few and those few will become very powerful.
What should marketers do right now?
The winners in the programmatic era were those who were clear about what they needed from the technology early on. Specifically, these marketers sought more control over how they bought media, increased efficiency, and achieved greater precision and deeper insights into their ability to reach their intended audiences. After activation, they also needed to understand the performance of those campaigns so they could adjust accordingly.
Sound familiar? To prepare for this new era (and maybe get a head start on the competition), marketers should strive for that same clarity about goals and challenges in the new landscape.
A good first step is optimizing your first-party data. As these data sets become increasingly important, ensure that solutions are in place that help you effectively collect, analyze and activate on first-party data so you can enrich relationships with existing customers and find net new audiences.
Also, understand that there are likely gaps in your first-party data that you may be unable to see. For this reason, find partners in the ecosystem that can help fill those gaps to create a complete view of your customer and how they interact with the world.
Finally, brand marketers must maintain focus on their current needs while being unafraid to try new tactics. This could mean adopting new technologies, working with new partners or perhaps even targeting new potential audiences that are identified by AI-driven insights.
Savvy brands will also prepare for the future by investing in privacy-friendly identity technologies such as data clean rooms that support user-level matching without the need to share raw data.
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Kelly Nash is the head product architect for IBM Watson Advertising’s next generation of advertising data solutions. In her role, Kelly oversees go-to-market product strategy, development and implementation across The Weather Channel data offerings.
