But despite the wealth of cookieless alternatives already available, a recent study revealed that 41% of advertisers are only moderately, if not at all, familiar with non-cookie-based targeting methods. From unified IDs to contextual or cohort-based targeting, many brands don’t know where to turn and are struggling to find the best path forward to continue engaging their customers in this new paradigm.

A plethora of unified IDs solutions have been developed in recent years. However, these initiatives lack the scalability cookies provided. They are siloed and can’t be interoperable, while also requiring consent - which is increasingly more difficult to get as users reject tracking en masse.

In addition, such solutions depend on a specific network of publishers, who are not inclined to share their users’ data either, making their reach extremely limited. That is without even mentioning Apple’s Private Relay setting on its devices and Safari browser, which hides users’ IP addresses and browsing data, making it impossible to reconcile IP addresses with unique IDs.

Another path many advertisers have explored is contextual and semantic targeting. But this approach does not allow brands to fully understand, nor engage, their audiences as it can only predict who is looking at a page or app based on the context instead of specific user interests. For example, a user browsing the Sports page of a general news website will be considered a sports fan, triggering sports-related ads. That could indeed be the case, but what about their other interests, which could also provide rich insights? What if that user has a dog, but never visits pet-focused websites? These “hidden enthusiasts” can be missed by only considering a small number of people gleaned from only focusing on very specific topics.

Lately, cohort-based advertising, like Google Topics, has proven superior to contextual and semantic targeting. By collecting users’ browsing history, this technique studies user behaviour to segment general topics at an aggregate level. But using cohorts still implies gathering user information, without users being fully aware of it.

In contrast, personified advertising does not rely on users’ browsing history. While cohort-based targeting depends on tracking users’ digital behaviour, personified advertising looks at the destinations where personas are likely to access their content, asking consenting users a number of questions to determine their interests in a transparent way.

For instance, marketers can use opt-in surveys to ask sports fans questions like “How many times a week do you work out?” to define if they are into casual or heavy fitness, investigating far beyond sports websites only. These questionnaires also determine users’ interests besides sports, shifting from a user-centric to a placement-centric approach, and accumulating dozens of millions of data points to define thousands of personas.

As cookie-based advertising approaches its decline, alternatives like unified IDs, or contextual, semantic and cohort-based targeting fall short in meeting expectations. In light of this, advertisers should turn to personified advertising for a solution that is truly privacy-first, future-proof and scalable.