Case Study: meliz boosts app installs by 5% with Airbridge MMM

How meliz Measures and Optimizes Marketing Performance with Airbridge’s Privacy-Preserving MMM Solution

meliz, a Korea-based fashion meta-search platform operated by ABLY Black, wanted a better way to understand the true impact of its marketing channels as privacy changes like Apple’s ATT made last-touch attribution less reliable. To support growth while protecting user privacy, the company worked with Airbridge and its Marketing Mix Modeling (MMM) solution.

Airbridge built a frequentist MMM using six months of historical channel spend data and calibrated it with incrementality results to improve accuracy. The model showed 33% less organic contribution than last-touch attribution, 39% more installs credited to display ads, and a budget plan that could drive 5% more installs while lowering average CPI by 4%. Airbridge’s MMM also delivered an average prediction MAPE of 7% during the analysis period.

meliz

Jongsoo Shin

Marketing Manager