MANY in digital advertisements are talking about their cookieless strategies for targeting in the post cookie-era.
In IAB’s fifth State of Data report, the deprecation of third-party cookies or IDs and cross-media addressability constraints are already impacting advertising measurements. The main concern is that a new privacy-centric solution that can replace historical measurement practices has yet to emerge.
For advertisers, costs to maintain campaign Return on Advertising Spend could increase as much as 200%. In Malaysia, the cookieless inventory is almost 30% and growing. Meanwhile, the shares of cookieless inventory are already 50% or higher in Singapore, Hong Kong and Taiwan.
As the impacts of 3rd party cookie depreciation becomes imminent, advertisers and agencies will need to invest on implementing new targeting and measurement tools that are technically ready and are sustainable.
The five must-haves are:
> Unique ID
Unique IDs such as The Trade Desk’s Unified ID 2.0 are popular, because they offer a solution that fully restores the functions that 3rd party cookies offer today. They also are privacy compliant as users need to provide consent to be targeted.
Unique IDs allow targeting of all audience types, including offline data, shopper data or income related data.
However, users need to be logged-in for this approach and as publishers face severe challenges to get users to sign-up, this solution is not likely to cover your targeting needs at scale.
In addition, the publisher 1P cookies., on UIDs rely, may also face depreciation in the future, which pose some risk for this approach.
> Publisher first-party data
Publishers’ first-party cookies are not impacted from browser cookie removal. They allow continued identification of users and can serve measurement functions such as Frequency.
While publisher 1st party data is an important ingredient in contrast to UIDs, publisher data cannot identify user behaviour offline and is relatively siloed. In addition, smaller publishers find it challenging to cover all legal and technical prerequisites to collect user consent.
> Predictive targeting
This approach is real time prediction targeting. For every online session, an AI predicts which audiences a user fits best. If the user fits into your campaign, targeting the online bidding can proceed.
Predictions are based on online behaviour through analysis of cookieless data signals such as IP address, device, website, time, and context.
However, for AI to carry out real-time profiling accurately, much data needs to be analysed, giving AdTech players on the supply side an advantage. Based on IP addresses AdTech companies can also create user IDs. However, this process called fingerprinting is rapidly becoming extinct due to privacy concerns and restriction to IP address information.