No cookies? No problem

By Misha Sulpovar

In the months since Apple’s declaration about IDFA policies and Google’s announcement to phase out third-party cookies, players in the AdTech ecosystem have been searching for new strategies to either work around or stay just ahead of regulatory headwinds to meet the market’s demand for personalized targeting.

Some are looking for clever ways to utilize emails, graphs, probabilistic fingerprinting and so on to support targeting and personalization instead of relying on cookies or IDFA. Like bailing water on a sinking ship, these approaches could buy some time but aren’t sustainable long-term solutions. As regulatory changes continue, users will demand more privacy and “opted in” consumers will be an ever smaller group.

But maybe the loss of cookies and other personally identifiable information isn’t such a bad thing. In fact, it might be the best change that could happen to modern advertising—and not just because privacy is the right thing to do for consumers.

Who said cookies were so great anyway?

The efficiency of using third-party consumer data has been overestimated for too long, creating a false sense of security for effective personalization and targeting. Often the information upon which we activate campaigns is faulty, incomplete or just best guesses. Sometimes we don’t even know how the data was derived. As publishers, we’re overdue for a better solution.

This isn’t to say that PII isn’t valuable if gained through a trusted, transparent process. As much as possible, we should monetize consumers by moving them toward targeted services like subscriptions that help us align user value with value capture. If not subscriptions, the next best thing may be encouraging users to at least register so we can improve their experience while connecting them with better or more relevant personalized advertising.

This requires a sophisticated approach to clearly and concisely articulating the value exchange, providing high quality, free resources in return for user data. While this may sound like the status quo, it supports the level of transparency that the market now expects, improving experiences for both consumers and advertisers.

But what about the consumers not currently using your service and whom you know nothing about? To grow and survive, our industry must discover a different path for maximizing the value of those potential users.

An old school recipe with new ingredients

Contextual marketing is about as traditional as it gets. You see it every time you gaze at a strategically placed billboard during your commute or pull meal service coupons out of your mailbox. These efforts are often based on, for example, what your zip code suggests about your lifestyle, where you likely work, your family makeup and your spending propensity. Despite its manual and limited nature, contextual marketing endures because it continues to prove effective.

But the next level of contextual marketing is understanding not only where our consumers are, but how’re they moving and behaving. We like to think of this as advanced contextual.

Imagine you’re in a grocery store. You push your cart to the aisle with flour and sugar, then you hit the refrigerated section for a carton of eggs. What if—based on these movements—the grocery store could rearrange itself in the moment by understanding that you’re likely baking a cake? Suddenly you’re presented with milk and butter. Maybe you’re alerted to a sale on a specific brand of icing.

Keep in mind that in this scenario, the grocery store doesn’t necessarily know anything about you or your personal history. Instead, it’s making an educated decision about your preferences and intentions based on what you’re doing. Once the store has recognized your intended path, you can benefit from the convenience of this adapted, targeted experience.

While this isn’t possible in physical stores, it’s certainly achievable in virtual environments. By tracking user navigation through a site—or a series of connected sites—the experience can be adjusted to optimize advertising and content. We can also utilize machine learning in advertising to evaluate user sentiment and the context of the interaction to better understand what the person wants and curate an enhanced experience and more relevant advertisements.

The best part is that, rather than relying on third-party data with questionable validity, these decisions are based on user actions as they actually happen. If executed correctly, this technologically driven contextual approach could be a significant improvement to the consumer and brand experience.

Regardless of the path, the marketing industry must determine how to create better transparency, privacy and certainty around the data exchange.

The vendors that succeed will recognize the new normal as an opportunity for healthy transformation while the rest search for the crumbs left behind.

Learn more about AI in advertising and cookieless solutions. Want to learn more about how advanced contextual marketing can drive growth for your business? Check out this infographic and this video.