Case Study: Unruly - Uses Lotame Audience Optimizer To Scale Campaigns And Increase Purchase Intent
Unruly uses emotional data to deliver video advertising on brand-safe, premium sites, driving the most revenue for premium publishers. At its core, Unruly is focused on ad distribution, and ensuring brands get the most out of their campaigns. Unruly believe that ads should not just reach people, but move them. With a unique set of emotional intelligence products, they are able to gauge which videos will resonate best with certain audiences, leading to increased engagement for advertisers and better placement for publishers. However, while they understand the emotional attributes of a particular target audience, the challenge they face is in scaling these audiences effectively to meet client campaign parameters.
Lotame Platform for Data Collection: Unruly works with Lotame’s Data Management Platform to identify and collect data from their millions of video campaign interactions, gathering emotional and psychographic data.
Audience Profiles: All of this data is combined into segments for audience targeting. Unruly also uses these profiles to build content roadmaps based on past engagement from surveys over their sample of 20,000 viewers.
Audience Optimizer for Lookalike Modeling: Unruly then used their powerful first-party data to build lookalike models via Audience Optimizer to extend the scale of their data and reach more potential customers for their clients.
Data Validation: With the support of Lotame’s Data Science team, Unruly took these AI audiences one step further and validated the lookalike audiences. Over many iterations and learnings, audiences proved to show statistical significance with their input data.