Case Study: meliz boosts privacy-first installs with Airbridge MMM

meliz boosts installs by 5% with Airbridge MMM

meliz, a one-stop fashion search platform, faced the challenge of accurately measuring marketing channel contributions in the post-privacy era due to policies like Apple's ATT, which rendered last-touch attribution unreliable. To examine the true contribution of its marketing channels while protecting user privacy, meliz turned to Airbridge and used its Marketing Mix Modeling (MMM) solution.

Airbridge implemented its proprietary MMM model to analyze performance and optimize budget allocation. The solution provided crucial insights, crediting Display Ads with 39% more installs and showing 33% less organic contribution compared to last-touch attribution. The optimized budget plan suggested by Airbridge's MMM model projected a potential 5% increase in installs and a 4% decrease in the average cost-per-install for meliz.

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