Recently, Google announced they would not invest in building alternative methods of identification once third-party cookies are no more. Once we finally wave goodbye to the cookie, Google will instead lean on their "FloC" solution (Federated Learning of Cohorts), which will essentially group similar behaviours and attributes in a cohort group, to be used for targeting.
Removing the use of identifiers within their advertising ecosystem means we will experience a shift from ‘one to one’ targeting capabilities to a ‘one to many’ approach to targeting. Whilst this may seem counterproductive, the investment Google have made into their machine learning capabilities over recent years has placed them in a favourable position to maintain advertising effectiveness, without the need for personal identifiers.
Their accelerated investment into product development, notably the evolution of their automated campaign and optimisation types, has given Google's entities the edge over their competitors from a future proofing perspective. Their algorithms are now so advanced they will be able to maintain advertising effectiveness, despite less granular means of user identification.
Similarly, Facebook is investing in product development such as their Aggregated Event Management (AEM), which works to group behaviours and attributes for targeting effectiveness by solving smaller pool sizes, improving the number of available signals to the machine for optimisation purposes.
What about the advertising scale?
The walled garden approach is favourable for the tech giants like Google, where ingesting first-party data to their clean room "Google Ads Data Hub" works to centralise data, including mobile app data sets, in a "privacy-centric" way.
This means that although you cannot surface the original data sets, users gain an overarching view of campaign performance across the Google ecosystem and can activate against them, therefore creating a strong case for ongoing investment into the Google tech stack as a whole.
Outside of the walled gardens, the outliers, such as open web inventory, are also working to resolve the diminishing cookies. They are creating more universal open-web solutions, which assign a proxy ID to a user across a group of relevant placements, aiming to maintain scale and efficiency through the strength in numbers approach.
Resolution Digital's PoV
Is this the end of retargeting?
Use of First-party data from your Customer Relationship Management (CRM) system will still be available in the future. However, we see platform optimisation tools pivot to futureproofing their own advertising products against the diminishing audience signals we anticipate due to increasing privacy restrictions across both web and app inventory.
The reduction in advertising identifiers means this is primarily focussed on developing goal-based bidding methods, as opposed to reaching individuals in a traditional retargeting way.
Goal-based bidding capabilities have become a key focus within the digital advertising space over recent years, not just with Google but will all major platforms.
The impact of this is that advertisers are now shifting their attitude. Their campaigns are targeted towards an objective rather than an audience to drive efficiencies.
It's evident in the recent years that, while prospecting and retargeting lines have become blurred, best practices are skewing towards broader targeting pools, underpinned by automated bidding solutions focussed on driving the overarching campaign objective. Increasingly automated campaign types will continue to be more and more prevalent in the future, across all major platforms – to future proof your own strategy, it is essential to remain agile and adapt to the changing digital climate.
Press coverage: Adnews