# App Store & Google Play AI  reviews scraper (1$/1.000 reviews) (`lofomachines/mobile-app-review-intelligence`) Actor

Scrape Apple App Store and Google Play reviews in one run and get AI-classified sentiment, themes, bugs, feature requests, churn signals, and executive insight reports.

- **URL**: https://apify.com/lofomachines/mobile-app-review-intelligence.md
- **Developed by:** [Lofomachines](https://apify.com/lofomachines) (community)
- **Categories:** AI, MCP servers, Social media
- **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 reviews

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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 Reviews Scraper + AI Insights — App Store & Google Play in One Run 📱🤖

**Scrape Apple App Store reviews and Google Play reviews together, and get every review automatically classified by AI** — sentiment, theme, severity, churn risk — plus an executive insight report with top complaints, top feature requests, emerging issues, and concrete recommendations for every app you analyze.

Stop exporting raw CSVs and reading thousands of reviews by hand. Paste an app link (or just the app name), click **Start**, and get an analysis that would normally take a product team days — in minutes.

### What does App Review Intelligence do?

- ⭐ **Scrapes app reviews from both stores** — Apple App Store (iOS) and Google Play (Android) — in a single run, normalized into one consistent format
- 🌍 **Multi-country support** — collect reviews from the US, UK, Germany, Italy, France, Spain, Brazil, India, Japan, and dozens of other storefronts
- 🤖 **AI review classification** — every review is enriched with `sentiment` (positive / neutral / negative / mixed), `category` (bug, feature request, UX, performance, pricing, ads, account access, support, content, praise), up to 3 concrete `topics`, a problem `severity`, and a `churnSignal` flag for users threatening to leave
- 📊 **Per-app insight report** — average rating, rating distribution, sentiment breakdown, top topics, 12-month rating trend, developer response rate, churn signals, and a 0–100 **App Health Score**
- 🧠 **AI executive summary** — strengths, top complaints, top feature requests, emerging issues, and prioritized recommendations, written like a senior product analyst would
- ⚔️ **Competitor comparison** — add two or more apps and get an automatic side-by-side ranking with key differentiators and opportunities
- 🔎 **Zero setup** — no API keys, no login, no cookies. Works with URLs, app IDs, package names, or just app names ("Duolingo")

### Who is this for?

- **Product managers** mining feature requests, bug reports, and churn reasons from real user feedback
- **App developers & indie hackers** monitoring releases — see instantly if a new version triggers a wave of complaints
- **ASO specialists & mobile marketing agencies** running review audits and reputation reports for clients
- **Founders & investors** validating a market — analyze competitor apps' weaknesses before building
- **UX researchers & data scientists** who need clean, labeled voice-of-customer datasets
- **Customer support teams** spotting emerging issues before they hit ticket queues
- **AI agents & LLM pipelines** that need structured, pre-classified review data (works great via API, MCP, Make, Zapier, n8n)

### Use cases

#### 1. Competitor app analysis

Add your app and 2–3 competitors. Get a side-by-side comparison of health scores, sentiment, top complaints, and the exact features users beg competitors for — your roadmap shortcut.

#### 2. Find bugs & technical issues fast

Set **Analysis focus** to *Find bugs & technical issues*. Crashes, login failures, payment errors, and performance problems are extracted, tagged, and ranked by severity.

#### 3. Discover feature requests & product ideas

Set the focus to *Feature requests*. The report distills hundreds of "I wish this app could…" reviews into a clean, prioritized list of product opportunities.

#### 4. Understand churn & cancellations

The *churn* focus highlights why users uninstall, cancel subscriptions, or switch to alternatives — with churn-risk flags on individual reviews so you can quantify it.

#### 5. Release monitoring & reputation management

Run it on a schedule after each release (newest reviews first) and watch the monthly trend, sentiment breakdown, and emerging issues. Pipe results to Slack, Sheets, or your BI tool.

#### 6. Market research & app due diligence

Evaluating a niche or an acquisition target? Analyze the leading apps in the category and instantly see what users love, hate, and still miss.

### Input

Designed for non-technical users — just three things really matter:

| Field | Description |
|---|---|
| **Apps to analyze** | App Store / Google Play URLs, Apple app IDs, Android package names, or plain app names (matched on both stores automatically) — see the accepted formats below |
| **Max reviews per app** | 10–5,000 reviews per app (default 250) |
| **Countries** | Storefront country codes, e.g. `us`, `gb`, `de`, `it` (default `us`). These are countries, not languages — `en` is not a valid storefront |
| Language | Preferred review language (default `en`) |
| Sort reviews by | Newest first or most helpful first |
| AI insights | Toggle AI classification and reports on/off |
| Analysis focus | Balanced, bugs, feature requests, churn, or competitor research |

#### How to reference an app

| Store | Accepted formats | Example |
|---|---|---|
| **App Store (iOS)** | Numeric app ID, the same ID with its `id` prefix, or the store URL | `458023433`, `id458023433`, `https://apps.apple.com/it/app/splitwise/id458023433` |
| **Google Play (Android)** | Package name or the store URL | `com.whatsapp`, `https://play.google.com/store/apps/details?id=com.whatsapp` |
| **Both stores** | Plain app name — the best match on each store is used | `Duolingo` |

The iOS app ID is the number after `/id` in the App Store URL; the Android package name is the `id=` parameter in the Google Play URL. Numeric values are always treated as App Store IDs and dotted values such as `com.company.app` as Google Play packages, so list both if you want the same product from both stores. When a plain name has no confident match on a store, that store is skipped and the log tells you which exact ID to use instead.

Example input:

```json
{
    "apps": [
        "458023433",
        "com.Splitwise.SplitwiseMobile",
        "https://apps.apple.com/us/app/whatsapp-messenger/id310633997",
        "Duolingo"
    ],
    "maxReviewsPerApp": 500,
    "countries": ["us", "gb"],
    "analysisGoal": "competitor"
}
```

### Output

You get three kinds of records in the dataset (filter by the `type` field), exportable as **JSON, CSV, Excel, or via API**.

#### Enriched review (`type: "review"`)

```json
{
    "type": "review",
    "appName": "Duolingo - Language Lessons",
    "platform": "ios",
    "country": "us",
    "rating": 2,
    "title": "New update ruined it",
    "text": "Ever since the last update the app crashes every time I open a lesson...",
    "date": "2026-06-02T09:14:33.000Z",
    "appVersion": "7.92.1",
    "helpfulCount": 41,
    "developerReply": null,
    "sentiment": "negative",
    "category": "bug",
    "topics": ["crashes on startup", "lesson loading"],
    "severity": "high",
    "churnSignal": true
}
```

#### App insight report (`type: "app_insights"`)

Average rating, rating distribution, sentiment & category breakdowns, top topics with counts, 12-month trend, developer response rate, churn signals, **App Health Score (0–100)**, store metadata (developer, category, installs, store rating), and the AI report:

```json
{
    "aiReport": {
        "summary": "Users love the gamified learning experience, but the latest release introduced...",
        "strengths": ["Engaging streak and gamification system", "..."],
        "topComplaints": ["Crashes when opening lessons after the latest update", "..."],
        "topFeatureRequests": ["Offline mode for lessons", "..."],
        "emergingIssues": ["Spike in login failures starting May 2026", "..."],
        "recommendations": ["Hotfix the lesson-opening crash affecting iOS users", "..."]
    }
}
```

#### Cross-app comparison (`type: "comparison"`)

A ranked comparison of all analyzed apps with reasons, key differentiators, and opportunities. A consolidated JSON report (`INSIGHTS`) is also saved to the run's key-value store — perfect for feeding dashboards or LLM workflows with a single request.

### Why teams choose this Actor

- **Two stores, one dataset** — no more stitching together separate iOS and Android scrapers
- **Insights, not just rows** — AI does the reading, tagging, and summarizing for you
- **Fast and affordable** — built for scale, priced for everyday use
- **No authentication required** — no store accounts, tokens, or developer access needed
- **Automation-ready** — REST API, webhooks, scheduled runs, and native integrations with Make, Zapier, n8n, Google Sheets, Slack, and the Apify MCP server for AI agents

### FAQ

**Do I need an Apple or Google account?**
No. The Actor needs zero credentials from you.

**Can I analyze any app?**
Yes — any publicly listed app on the Apple App Store or Google Play, in any supported country storefront.

**How many reviews can I get?**
Up to 5,000 per app per run. Apple storefronts expose the most recent reviews per country, so adding more countries increases iOS coverage.

**What languages are supported?**
Reviews are collected in any language; AI topic tags are normalized to English so cross-country data stays consistent and filterable.

**Can I use it without AI?**
Yes — switch off **AI insights** to get clean, normalized raw reviews from both stores.

**Is this legal?**
The Actor only collects publicly available review data that anyone can see in the app stores. No personal accounts are accessed.

**Can I run it on a schedule?**
Yes — use Apify Schedules to monitor your app (or competitors) daily or weekly, and connect webhooks to get alerts.

***

*app store reviews scraper · google play reviews scraper · app review analysis · review sentiment analysis · ASO tools · app store optimization · competitor app analysis · voice of customer · mobile app market research · app reviews API · ios reviews export · android reviews export*

# Actor input Schema

## `apps` (type: `array`):

One entry per app. <b>iOS / App Store</b>: the numeric app ID (e.g. <code>458023433</code>), the ID with its <code>id</code> prefix (<code>id458023433</code>), or the full store URL (<code>https://apps.apple.com/it/app/splitwise/id458023433</code>) — the number after <code>/id</code> in the URL is the app ID. <b>Android / Google Play</b>: the package name (e.g. <code>com.whatsapp</code>, <code>com.Splitwise.SplitwiseMobile</code>) or the full store URL (<code>https://play.google.com/store/apps/details?id=com.whatsapp</code>) — the package name is the <code>id=</code> parameter in the URL. <b>App name</b>: plain text (e.g. <code>Duolingo</code>) is searched on both stores and the best match on each is used. Numeric values are always treated as App Store IDs and values like <code>com.company.app</code> as Google Play packages, so add both if you want the same product from both stores. Add competitors here too to get a side-by-side comparison.

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

Maximum number of reviews to collect per app. Reviews are collected country by country until this number is reached, so the actual total depends on how many reviews each store actually publishes for that app in the countries you selected (a small app may have only a few dozen per country). More reviews = deeper insights.

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

Two-letter <b>ISO country codes</b> of the app stores to collect reviews from — e.g. <code>us</code>, <code>gb</code>, <code>it</code>, <code>de</code>, <code>fr</code>, <code>es</code>, <code>br</code>, <code>in</code>, <code>jp</code>. These are countries, not languages: <code>en</code> is not a country code (use <code>us</code> or <code>gb</code>) and invalid codes are ignored. Reviews are collected country by country until the maximum is reached, so add more countries to collect more reviews.

## `language` (type: `string`):

Preferred language code for review collection (e.g. <code>en</code>, <code>de</code>, <code>it</code>, <code>es</code>, <code>pt</code>). It sets the Google Play language and the App Store review locale — it does <b>not</b> replace the country list above.

## `sortBy` (type: `string`):

Collect the newest reviews first (best for monitoring) or the most helpful ones first (best for research). Applies to Google Play; the App Store only publishes reviews newest-first.

## `aiInsights` (type: `boolean`):

When enabled, every review is enriched with sentiment, theme, topic tags, severity, and churn-risk signals, and each app gets an executive insight report (top complaints, top feature requests, emerging issues, recommendations). Disable to get clean raw reviews only.

## `analysisGoal` (type: `string`):

Tell the AI what matters most to you. This shapes the insight reports and recommendations.

## `proxyConfiguration` (type: `object`):

Apify Proxy is used for the store requests. The App Store limits how many reviews a single IP can pull, so rotating proxy sessions is what keeps large runs complete — leave this on unless you have a reason not to. Turning it off makes all requests come from one IP, which usually means fewer reviews per app.

## Actor input object example

```json
{
  "apps": [
    "458023433",
    "com.Splitwise.SplitwiseMobile",
    "https://apps.apple.com/us/app/whatsapp-messenger/id310633997"
  ],
  "maxReviewsPerApp": 100,
  "countries": [
    "us"
  ],
  "language": "en",
  "sortBy": "newest",
  "aiInsights": true,
  "analysisGoal": "balanced",
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

# 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 = {
    "apps": [
        "458023433",
        "com.Splitwise.SplitwiseMobile",
        "https://apps.apple.com/us/app/whatsapp-messenger/id310633997"
    ],
    "countries": [
        "us"
    ],
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("lofomachines/mobile-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 = {
    "apps": [
        "458023433",
        "com.Splitwise.SplitwiseMobile",
        "https://apps.apple.com/us/app/whatsapp-messenger/id310633997",
    ],
    "countries": ["us"],
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("lofomachines/mobile-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 '{
  "apps": [
    "458023433",
    "com.Splitwise.SplitwiseMobile",
    "https://apps.apple.com/us/app/whatsapp-messenger/id310633997"
  ],
  "countries": [
    "us"
  ],
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call lofomachines/mobile-app-review-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,lofomachines/mobile-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/q5ufg9DaHXmeyMAcr/builds/wWJ5mh9Mz96O1cG48/openapi.json