# Apple App Store Reviews Scraper (`neuton/apple-app-store-reviews-scraper`) Actor

Scrape Apple App Store reviews, app metadata, and search result rows for ASO research, review sentiment, mobile app competitor monitoring, and product intelligence.

- **URL**: https://apify.com/neuton/apple-app-store-reviews-scraper.md
- **Developed by:** [Ashwin Prasad](https://apify.com/neuton) (community)
- **Categories:** Business, AI, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

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

## 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

## Apple App Store Reviews Scraper

Scrape public Apple App Store reviews, app details, ratings, developer metadata, and search result rows for ASO research, mobile app competitor monitoring, review sentiment, product feedback analysis, and app market intelligence.

This actor is designed for searches such as Apple App Store reviews scraper, App Store scraper, iOS app reviews API, App Store competitor monitoring, app review sentiment, and mobile ASO data export.

### What You Can Extract

- App Store review title, text, rating, author, version, and date
- App name, developer, category, average rating, rating count, price, and supported devices
- App Store search result rows by keyword and country
- Country-specific review feeds for market-by-market monitoring
- Source URLs and raw Apple/iTunes records for auditability

### Example Input

```json
{
  "mode": "reviews",
  "appIds": ["284882215"],
  "country": "us",
  "maxResultsPerApp": 100
}
```

### Modes

- `reviews`: fetches public RSS review feed pages for each app ID.
- `details`: fetches app metadata from the public iTunes lookup endpoint.
- `search`: searches the App Store by keyword and exports app result rows.

### Common Use Cases

- Monitor competitor app reviews and ratings
- Build review sentiment and product feedback datasets
- Track ASO keywords and app search competitors by country
- Enrich mobile app market maps with developer, category, and rating data
- Feed app review data into BI dashboards, LLM pipelines, or alerting workflows

### Output

Every result is saved to the default Apify dataset. Review rows can include `appId`, `country`, `reviewId`, `title`, `text`, `rating`, `author`, `version`, `updatedAt`, and `reviewUrl`. App detail/search rows can include app name, developer, category, rating count, average rating, price, supported devices, artwork URLs, App Store URL, source mode, and scrape timestamp.

### Launch Pricing Recommendation

Use pay-per-event pricing after payout billing is configured:

- $0.0010 per review row if split pricing is available
- $0.0030 per app detail/search row if split pricing is available
- $0.0020 per dataset row if only one default dataset-item event is practical

The actor is built around low-cost public Apple/iTunes endpoints and should remain at 256 MB memory unless smoke tests show otherwise.

### Responsible Use

This actor extracts public App Store reviews, app metadata, and search results. It does not access private developer analytics, user accounts, personal contact data, or paid App Store Connect data. Follow Apple's terms and use review text responsibly, especially when sharing sentiment outputs externally.

### Automation Ideas

Schedule daily or weekly country-specific review monitors for your app and competitors. AI agents can summarize recurring complaints, classify feature requests, detect review-rating drops, compare ASO keywords, route negative reviews to product teams, and update mobile market-intelligence dashboards.

# Actor input Schema

## `mode` (type: `string`):

Choose whether to fetch reviews, app details, or App Store search results.

## `appIds` (type: `array`):

Numeric Apple app IDs or App Store URLs. Required for reviews/details mode unless search terms are used.

## `searchTerms` (type: `array`):

App Store search keywords such as fitness tracker, budget app, meditation.

## `country` (type: `string`):

Two-letter App Store country code such as us, gb, in, de, jp.

## `maxResultsPerApp` (type: `integer`):

Maximum review rows to fetch per app in reviews mode.

## `maxSearchResultsPerTerm` (type: `integer`):

Maximum app search results per keyword in search mode.

## Actor input object example

```json
{
  "mode": "reviews",
  "appIds": [],
  "searchTerms": [],
  "country": "us",
  "maxResultsPerApp": 100,
  "maxSearchResultsPerTerm": 50
}
```

# Actor output Schema

## `results` (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 = {
    "country": "us"
};

// Run the Actor and wait for it to finish
const run = await client.actor("neuton/apple-app-store-reviews-scraper").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 = { "country": "us" }

# Run the Actor and wait for it to finish
run = client.actor("neuton/apple-app-store-reviews-scraper").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "country": "us"
}' |
apify call neuton/apple-app-store-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=neuton/apple-app-store-reviews-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Na7nSXJ6efn0mPI2N/builds/Z55lrhQHlSIFNiiK3/openapi.json