gaming · Customer outcome
The starting point, work, and retained outcome record from an anonymized Lemon AI engagement.
Android, iOS
Europe, MENA, APAC
Google Ads, Meta Ads
$100k+ monthly
Evidence note: The customer identity is withheld. The operating context, actions, and outcome figures are retained from Lemon AI’s previously published case record and were approved for this migration. Results describe this engagement and are not a promise of identical performance for another app or market.
Operating context
5M+ installs
725K+ MAU
Starting point
- Revenue varied by market, and the team needed to protect player experience and engagement
Goal
- Increase ROAS and ad revenue for a game with hybrid monetization (80% ad revenue, 20% in-app purchases)
What Lemon AI did
- Trained and integrated a model in 8 days
- Predicted Top 10%, 20%, and 30% players by revenue
- Created custom event for players who reached "level 10" and spent 200 "diamonds"
Measured results
| Outcome | Result |
|---|---|
| campaign efficiency during the Lemon trial | +25% |
| ROAS | Android +42% · iOS +37% |
| Ad revenue | Android +28% · iOS +16,5% |
How to interpret the result
The outcome should be read in the scope shown above: its platforms, region, acquisition sources, budget band, objectives, and measurement period. The result does not isolate a universal causal effect and should not be compared with another case without aligning its metric definition and time horizon.
Read the measurement and forecasting methodology for source, attribution, aggregation, reconstruction, and prediction limitations.
Next step
See the same workflow with your data
Bring one app and its acquisition questions to a product walkthrough.