The ad tech business is experiencing an identity crisis as a result of the elimination of the third-party cookie. Universal identifiers are one of the emerging options for the post-cookie era, but their effectiveness is yet to be established.
Although the IAB Tech Lab’s Seller-Defined Audience is another way to bring addressability to a cookie-free future. It may very well leverage the open web to securely scale the monetization of first-party data.
How Does Seller-Defined Audience Work?
The IAB’s proposal aims to make it possible for publishers to label their audiences and provide those labels to bidders. These labels can be used to segment audiences based on demographics, interests, and purchasing intent. Contextual signals will also be possible to convey. Without third-party cookies, bidders will be able to find the correct audience, and the entire process is expected to be privacy-friendly and law-abiding.
Why SDA?
According to the IAB Tech Lab, this strategy has the following benefits:
- Both the demand and supply sides can define and transmit audience data on the same platform.
- As a publisher, you’ll have hundreds of options for naming your audience, and the buyer will have to decide whether or not to trust the vendor (by analyzing the DTS info). It gives you a lot of options when it comes to segmentation.
- The transparency standards can be used to classify a single piece of traffic not just by you, but also by other data-providing partners. As a result, the segmentation process is not solely reliant on publishers.
- Buyers will be able to make informed judgments before spending money on Seller Defined Audiences because of DataLabel.org’s transparency.
- The IAB’s compliance program will ensure that data labels can be trusted by customers. It’s critical to have a reliable protocol in place.
Future of SDA
As a marketer, we expect to see a lot more of these options in the future. To cover the gap left by the third-party cookie, we almost certainly need multiple tools. We must assess them in order to determine their optimal application. While the approach appears promising on the surface, its full efficiency will be apparent only once the adoption process has progressed.
