Case Study: AzurGames boosts data monitoring efficiency with AppsFlyer’s AI-powered alerts

Boosting data monitoring efficiency with AI-powered detailed alerts

AzurGames, a mobile game developer in EMEA, needed a better way to monitor and optimize its user acquisition campaigns across hundreds of campaigns and platforms. Its in-house rule-based alerting system had limited data coverage, produced too many false positives, and often delayed key performance insights, making it hard to act quickly on issues and opportunities. AppsFlyer’s Measurement Suite and Marketing Analytics were used to address these monitoring challenges.

AppsFlyer implemented oolo, its AI-powered alerting solution, to provide full data coverage, noise-filtered alerts, and detailed root-cause insights across cost, revenue, retention, and share-of-voice metrics. The result was faster decision-making, a drop in false positives from 10–20% to under 5%, and more than 30 hours saved each month in monitoring time. AzurGames also cut weekly monitoring from 10 hours to 2–3 hours and resolved complex investigations in 1–2 hours instead of 3–5.

AzurGames

Diana Agrba

UA Manager