Impact on Wagawin’s LivingAds

While the whole industry is negatively affected by reduced user identification, Wagawin’s ability to build unique 1P audiences based on user engagement will suffer as well. Wagawin’s LivingAds can run on any mobile Display & Video placement worldwide and support all kinds of alternative IDs. Group-based approaches like Google’s privacy sandbox will also be supported. Furthermore, publishers will take care of privacy and support these IDs to increase the value of their inventory. So, you still can build audiences by making users engage with your ads. However, there will be big publishers that don’t pass user IDs to the programmatic value chain. So you won’t be able to build a unique audience in these closed environments. Instead, you can use data clean rooms to activate your existing audience there. As already described, collecting 1P data on your website will become even more important.

In contrast to audience building, Wagawin’s non-PII approach of building unique audience insights is not affected. In fact, no personalized data is processed and Wagawin’s engagement data generated by LivingAds is enriched by bid stream data and meta data like age, gender, and context. Wagawin offers a wide-ranging database on conversational data that can be used for cross-channel campaign optimization. We expect our unique insight data base to have a higher impact on performance than audience remarketing.

No matter if you consider working with personalized data or non-personalized insights, our fully optimized and responsive LivingAd formats process 5x more user feedback than traditional static ad formats.

Balance of power

While nobody can really predict the future of user identification in online advertising, there are few conclusions that can be drawn. First, big publishers and marketers with much 1P data will get even more power as they can keep their data secure. Second, small players are weakened due to a lack of scale and resources. While small advertisers might double down on Walled Gardens to get measurement and attribution at a small scale, data privacy, brand safety, visibility, control, and content quality are still disadvantages that must be taken into account.

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