From sharing data in clean rooms and within publishers' associations to contextual advertising and AI- powered solutions, Tim Conley , IPONWEB's Director of Customer Service Europe, talks about what awaits us in a cookie-free world.
The news that Google will end support for third-party cookies in its popular browser Chrome made a lot of noise. This news comes as no surprise to those who are well versed in the matter and know that cookies are poorly suited for long-term tracking and targeting of user activity. And yet there is still debate about what awaits us next.
So what will the cookie-free future be like?
PPC solutions
In the early days of the digital age, content played a key role - along with context. Advertisers bought ad space based on the publisher's audience, which in turn was dependent on the content posted on the site. That is, advertising was related to the direct interests of the user, and not to his past activity tracked using cookies.
Over time, with the development of cookie-based retargeting and its higher performance, the audience has come to the fore. It became not so important where to place the advertisement - the main thing is that it is seen by the very user whom the advertiser wanted to attract.
Now that the end of cookies is imminent, the targeting pendulum has swung back towards contextual advertising. It seems that advertisers are willing to (re) recognize that relevance is important and that there is some point in putting their content in the right places. Instead of trying to sell a user a running shoe while he is researching his pedigree on a genealogy site, it’s much more effective to show him the same ad when he is looking at running trails.
Contextual targeting hasn't stood still either. Here it was possible to achieve, in particular, a faster and more detailed content classification. This allows advertisers to leverage news cycles and popular content, for example.
There is still a lot to be done to learn how to complement the context with the right emotions and provide a more differentiated approach that takes into account different nuances. For example, so that advertisers who want to associate with basketball-themed content without appearing in news stories about Kobe Bryant's recent tragic death can adjust this placement automatically and with scalability.
Publisher and Advertiser Initiatives
Without third-party cookies, the value and importance of the data received directly by the publisher will increase. If now advertisers determine which publisher users are suitable for their audience, then in the future publishers will be engaged in this task: on the basis of their data, they will compare their users with the target audience of the advertiser.
This will lead to the following trends:
Redefining audience segments .For scaling, the publisher will need to agree on the designations of the currently defined target audiences. One option is to improve on the existing IAB industry category list. At the same time, it is likely that third-party companies will, together with publishers and advertisers, look for other ways to target audiences.
Consolidate your own data. Publishers will work with advertisers and technology partners to create a consistent, consistent audience, tracked across all networks, based on their own (currently underused) cookies as well as any other user-supplied data.
Validation of identifiers without using cookies.Today's non-cookie identifiers often lose validity very quickly. However, when used in conjunction with the publishers' protected proprietary data, it increases their usefulness for creating a targeted user profile - a kind of "nicotine patch" for advertisers who cannot live without attribution.
Data exchange using "clean rooms"
The concept of "clean rooms" for data processing is not new. In such “premises,” in a secure environment, advertisers' own data can be combined with other datasets, usually from closed ecosystems, to gain insight and measure ad performance. Neither party has the right to use the raw data of the other party outside of this space.
Publishers (or their associations) and advertisers could use clean rooms in a similar way to gain insights and insights from user data. This could potentially enhance individual targeting, cross-brand and publisher attribution, and insights from aggregated information across multiple devices - all without compromising data security.
In the future, it will be possible to solve current problems, for example, related to privacy, due to which advertisers are unable to exchange detailed transaction data. Thus, the top priorities in cleanroom projects are data management and creating constraints on who can access what data.
AI and machine learning algorithms
There is a lot of room for theory and speculation in this topic, but it is clear that a constantly refined self-learning model that analyzes anonymous signaling data, such as the frequency of visits to the site or the devices used, allows us to learn a lot about users. The processing of large arrays of such data makes it possible to form user cohorts and, on the basis of this, make general forecasts.
For example, people in a specific area of a city with an Apple device with iOS 13 or higher and visiting Forbes.com are five times more likely than average to get and receive credit cards. That is, instead of targeting advertising to specific users based on cookies, it is possible to create ad purchase models that are targeted and optimized to reach the audiences identified in this way.
There are obvious questions about attribution, especially related to how publishers will profit from this approach. But in the cookie-free world that awaits us, this is one promising approach to audience targeting. Therefore, to prevent the last-click attribution model from becoming the norm, there will be a new way to measure ad performance.
The future is based on identifiers
For a while, this header was relevant for third-party cookies, but this does not mean at all that it will be possible to find alternatives quickly and easily. One thing is clear: the interest of players in the advertising market in trading on digital platforms will stimulate the search for non-personalized solutions based on identifiers.
Such projects can appear in different parts of the AdTech ecosystem. They will strive to satisfy equally important needs: ensuring return on investment for advertisers, profit for publishers, and data privacy for users.
I can already imagine how, a few years later, when meeting with colleagues in the shop, I will ask: “Remember when we thought we needed cookies?”.