# App Review Intelligence — Bugs & Churn Signals (`matiaslencina/app-review-intelligence`) Actor

Analyze Google Play and Apple App Store reviews for recurring bugs, feature requests, churn signals, release regressions, competitor mentions, app health, and prioritized product actions—without an external AI key.

- **URL**: https://apify.com/matiaslencina/app-review-intelligence.md
- **Developed by:** [Matias Lencina](https://apify.com/matiaslencina) (community)
- **Categories:** Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $50.00 / 1,000 app intelligence reports

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## App Review Intelligence — Bugs & Churn Signals

Turn public **Google Play and Apple App Store reviews** into product intelligence.

Instead of exporting hundreds of reviews and reading them manually, get one app-level report that surfaces **recurring bugs, feature requests, churn risk, release regressions, competitor mentions, app health, and prioritized product actions**.

### What you get

- recurring bug / pain-point clusters
- severity and review evidence
- feature-request themes
- churn / switching signals
- rating trend
- latest-version regression risk
- competitor keywords you choose to monitor
- custom watch keywords
- rating distribution
- 0–100 app health score
- prioritized recommended actions

### Why this is different from a review scraper

A review scraper answers:

> What did users write?

This Actor is built for **app review analysis, bug detection, churn analysis, feature-request analysis, mobile product research, and release triage**.

It answers:

> What is repeatedly going wrong, how serious does it look, and what should the product team investigate next?

The analysis is deterministic and evidence-backed. No external AI key is required.

### Supported stores

- Google Play
- Apple App Store

Each app × country storefront produces one intelligence report.

### Example input

```json
{
  "targets": [
    "com.spotify.music",
    "https://apps.apple.com/us/app/notion/id1232780281"
  ],
  "countries": ["us"],
  "maxReviewsPerApp": 200,
  "lookbackDays": 90,
  "minIssueMentions": 2,
  "competitorKeywords": ["YouTube Music", "Apple Music"],
  "watchKeywords": ["offline", "subscription", "crash"],
  "includeEvidence": true
}
```

### Best for

Product managers, mobile developers, QA teams, ASO / reputation monitoring, agencies, founders, investors, and scheduled app-health monitoring.

### Limits

Store feeds expose recent public review windows rather than guaranteed full historical archives. Keyword classifications can miss sarcasm, synonyms, or language variants, so use evidence snippets when validating important product decisions.

# Actor input Schema

## `targets` (type: `array`):

Google Play package IDs or URLs, Apple App Store URLs, or numeric Apple app IDs. Prefixes google: and ios: are also supported.

## `countries` (type: `array`):

Two-letter storefront country codes. Each app-country pair becomes one analysis row.

## `googlePlayLanguage` (type: `string`):

Two-letter language code used when reading Google Play reviews.

## `maxReviewsPerApp` (type: `integer`):

Maximum number of recent reviews analyzed for each app and storefront. Apple public feeds cap at roughly 500 per country.

## `lookbackDays` (type: `integer`):

Only reviews inside this age window are used for the main intelligence analysis. Use 0 to disable the date filter.

## `minIssueMentions` (type: `integer`):

Minimum number of matching low-rated reviews required for an issue cluster to appear in topIssues.

## `competitorKeywords` (type: `array`):

Optional competitor names or product keywords to detect inside review text.

## `watchKeywords` (type: `array`):

Optional product-specific words or features whose review mentions you want counted.

## `includeEvidence` (type: `boolean`):

Include a few short review snippets behind issue, churn, feature, and keyword findings.

## Actor input object example

```json
{
  "targets": [
    "com.spotify.music",
    "https://apps.apple.com/us/app/notion/id1232780281"
  ],
  "countries": [
    "us"
  ],
  "googlePlayLanguage": "en",
  "maxReviewsPerApp": 200,
  "lookbackDays": 90,
  "minIssueMentions": 2,
  "competitorKeywords": [],
  "watchKeywords": [],
  "includeEvidence": true
}
```

# Actor output Schema

## `results` (type: `string`):

Bug clusters, feature requests, churn signals, release risk, keyword mentions and health score.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("matiaslencina/app-review-intelligence").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("matiaslencina/app-review-intelligence").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call matiaslencina/app-review-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,matiaslencina/app-review-intelligence"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/NvBjlS2KU2R002gOY/builds/jcu0j6TALgrjj2BFR/openapi.json