---
title: "Dating subscription app Case Study | Lemon AI"
description: "Dating subscription app case study: how Lemon AI addressed retention and ltv had stopped growing and measured -37% inefficient budget allocation reduced."
canonical: "https://lemon-ai.com/cases/dating-subscription-app"
markdown_url: "https://lemon-ai.com/cases/dating-subscription-app.md"
language: "en"
image: "https://lemon-ai.com/og/case-dating-subscription-app.png"
image_alt: "Rising retention and ad-revenue outcomes for an anonymized dating subscription app."
schema_types: ["BreadcrumbList","Organization","WebApplication","WebPage","WebSite"]
---

# Dating subscription app

lifestyle · Customer outcome

The starting point, work, and retained outcome record from an anonymized Lemon AI engagement. 

**Android, iOS, WEB**

MENA, Europe

Google Ads, Meta Ads, TikTok Ads

$380K+ 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

55M+ monthly visits 

2.4M+ MAU 

## Starting point

- Retention and LTV had stopped growing
- Competitors were running large campaigns

## Goal

- Raise retention and revenue

## What Lemon AI did

1. Integrated data from Appsflyer and proprietary solution in 6 days
2. Found direct correlation between chat message frequency and LTV, improved accuracy of revenue prediction
3. Targeted users with Top 30% LTV on Day 90, and users with top 20% Ad Revenue on Day 30
4. Standardized A/B testing across channels and predicted campaign revenue on Day 90

## Measured results

| Outcome                                  | Result                  |
| ---------------------------------------- | ----------------------- |
| inefficient budget allocation reduced    | \-37%                   |
| hours saved per week on analytical tasks | 140                     |
| Retention                                | Android +34% · iOS +24% |
| Ad Revenue on Day 30                     | Android +37% · iOS +22% |

## 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](https://lemon-ai.com/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.

[Book a demo](https://calendly.com/robert-lemon-ai) 

[← All case studies](https://lemon-ai.com/cases)

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```