delivery · Customer outcome
Food delivery apps
The starting point, work, and retained outcome record from an anonymized Lemon AI engagement.
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
Starting point
- The apps had strong service quality but struggled to gain market share
Goal
- Raise retention and AOV
What Lemon AI did
- Trained and integrated model in 9 days
- Focused campaigns on the top 10%, 25%, and 50% of users by D30 LTV
- Added predicted product recommendations to encourage repeat purchases
- Adjusted the marketing mix in each country
Measured results
| Outcome | Result |
|---|---|
| hours saved monthly for product and analytics teams | 140 |
| LTV on Day 30 | Android +34.2% · iOS +22% |
| Retention on Day 14 | Android +22.5% · iOS +14.1% |
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.