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.

       Predictive Audience targeting ticks not only the very important box for scale but offers a good balance in terms of accuracy and scale for crucial audience types like Age & Gender as well as Interest categories with considerable granularity.

       Just as data provides use to model their data segments, predictive targeting can be fine-tuned to meet accuracy and scale demands.

       > Google chrome privacy sandbox

       Google Chrome is the world’s largest browser and powers digital advertisement. The scale alone makes the solution must have. Google’s approach promises scalable and privacy-compliant targeting, based on a user’s reading behaviour in the browsers across multiple domains. Google’s change from the envisioned FLOC cohort approach to the latest Topics API can be described as less ambitious on the one hand, but also more achievable on the other.

       A main caveat is individual user data will remain in the browser adding to the black box of Google’s digital ecosystem.

       > Contextual targeting

       Contextual targeting whether based on simple keywords, advanced semantic analysis or image analysis, does not rely on user IDs at all. It is an elegant way to reach users in the moment when they are most receptive to marketing messages.

       Good contextual targeting needs to overcome three challenges – accuracy, scale, effectiveness. Accuracy can be achieved by analysing the importance of keywords for contextual interest topics and curating keyword groups.

       While scale is inherently more limited than audience targeting, a hierarchically organised contextual catalogue will allow control accuracy and scale as needed.

       Stronger media effectiveness and ad memorisation often depends on the environment. An ad unit embedded in professional editorial content has distinct advantages over user generated contents or banners at the top of a page.

       Users slowly reading an engaging article will be more likely to respond positively to a non-intrusive creative aligned with their interests.

       > About Teads

       Teads analysis of online content consumption is at the core of Teads unique knowledge to deliver best-in-class semantic algorithms.

       In 2021, Teads delivered over 50% of all ad dollars spent on the platform with cookieless solutions, by making cookieless solutions accessible for clients through a new ‘Cookieless Mode’ in our buying interface.

       Our data solutions are seamlessly integrated into Teads Ad Manager and make it easy to set up A/B tests with sustainable audiences or advanced contextual targeting as well as our latest release the Teads Cookieless Translator.

       For more on Teads Ad Manager and our cookieless solutions, contact danial.smurthwaite@teads.tv

       Teads was the Tech Trooper sponsor of Star Media Group’s #digitalXdata MarCom Tech conference. To rewatch Teads’ session at the Data & Analytics track, visit bit.ly/marcom-teads.