Using Permutive, Ranker created high-intent audiences based on first-party data, collected from a variety of unique visitor data. This includes site votes, surveys, behaviour, and context. Ranker also has the ability to create lookalike audiences. The seeds are broken out by content category through IAB segmentation combined with Ranker’s contextual taxonomy. This enabled them to increase scale across various direct, private marketplace, and programmatic guarantee campaigns, and optimize all these in their partnership with one of the top four streaming services.
Testing contextual versus first-party cohorts
Ranker ran tests for the streaming service campaign, starting with contextual targeting across all the client’s audience interests in week one. While those ran, Ranker built cohorts from its higher intent audiences via Permutive, which were applied in week two and resulted in lift across the board.
Reactive to proactive insights
Ranker uses pre-sale audience affinities to craft proposals and post-sale analysis, helping position campaign success and insights back to their advertisers. Ranker previously relied on being reactive to cohorts that they built. The team can now identify affinities and intent based on a combination of different activities, such as voting data, page view data and affiliate link data for each campaign, all in real-time using Permutive’s edge technology. This provides a view on what impacts campaigns from a scale and performance perspective.
Deeper audience understanding
The insights Ranker provides help advertisers understand more about the audience that’s clicking on their display ads and viewing their video ads; Ranker can tell advertisers what their users are doing and their other interests and likes, demonstrating the value of their unique first-party data cohorts. These insights include pre-, mid- and post-campaign data designed to inform planning, mid-flight optimization and future targeting.