Apple App Store Reviews Scraper

Export public Apple App Store reviews by app, country, and sort order, including ratings, review text, dates, versions, author names, and app metadata.

Apple App Store Reviews Scraper saves one public review per dataset row. Use it for ASO, product feedback mining, release monitoring, support triage, competitor review analysis, and mobile app intelligence.

At a glance

• Input: Apple App Store URLs or numeric app IDs in appUrlsOrIds.
• Output: review title, text, rating, version, date, author display name, review URL, app name, developer, app ID, and source feed URL.
• Controls: country, sort order, review cap per app, and optional app metadata lookup.
• Exports: download JSON, CSV, Excel, XML, RSS, or HTML, or read results through API/MCP.
• Best for: ASO analysis, post-release monitoring, competitor review mining, and support issue triage.

What can it do?

• Export public app reviews: Save one row per public Apple App Store review for one or more apps.
• Filter by country and sort: Use localized review feeds and choose recent or helpful review ordering.
• Track ratings and versions: Capture star ratings, review text, dates, version labels, and public author display names.
• Add app metadata: Include app name, developer name, canonical app URL, and app ID when available.
• Use as an App Store reviews API workflow: Run from API, schedules, webhooks, or MCP-compatible agents and export CSV/Excel/JSON.

Input example

{
  "appUrlsOrIds": ["https://apps.apple.com/us/app/whatsapp-messenger/id310633997"],
  "country": "us",
  "sortBy": "mostrecent",
  "maxReviewsPerApp": 20,
  "includeAppMetadata": true
}

Output example

{
  "appId": "310633997",
  "appUrl": "https://apps.apple.com/us/app/whatsapp-messenger/id310633997",
  "country": "us",
  "appName": "WhatsApp Messenger",
  "developerName": "WhatsApp Inc.",
  "reviewId": "14177411298",
  "reviewUrl": "https://itunes.apple.com/us/review?id=310633997&type=Purple%20Software",
  "authorName": "Example reviewer",
  "authorUri": "https://itunes.apple.com/us/reviews/id123456789",
  "rating": 4,
  "version": "25.12.0",
  "title": "Example review title",
  "content": "Example public review text...",
  "updatedAt": "2026-06-13T04:03:53-07:00",
  "sourceFeedUrl": "https://itunes.apple.com/us/rss/customerreviews/page=1/id=310633997/sortby=mostrecent/json",
  "scrapedAt": "2026-07-03T00:00:00.000Z"
}

Common workflows

• Release monitoring: schedule mostrecent reviews after each app update and compare version, rating, and content.
• ASO review mining: export review text by country to identify feature language, complaints, and competitor positioning.
• Support triage: collect low-star review text and route common issues to support or engineering.
• Competitor analysis: run several app IDs with the same country and cap, then compare themes and ratings.
• Downstream AI analysis: send title, content, rating, version, and updatedAt into tagging or summarization workflows.

Tips for best results

• Use numeric IDs when possible: App Store URLs work, but IDs are easiest to reuse in scheduled tasks.
• Run one country at a time: review availability and language vary by country.
• Keep first runs small: start with 20-50 reviews per app before increasing to 500.
• Use sort intentionally: mostrecent is best for monitoring; mosthelpful is useful for evergreen review samples.
• Expect optional fields: author URI, review URL, version, and app metadata can be missing for some rows.

Limits and caveats

• Public reviews only: the actor does not log in and does not collect private Apple account data.
• Feed limits: Apple review feeds may expose fewer rows than your requested cap, often up to about 500 per country/sort combination.
• Metadata is optional: review rows can still be saved if app metadata lookup is unavailable.
• No ratings aggregate history: the actor exports review rows, not complete historical rating curves.

API usage

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/apple-app-store-reviews-scraper').call({
  appUrlsOrIds: ['https://apps.apple.com/us/app/whatsapp-messenger/id310633997'],
  country: 'us',
  sortBy: 'mostrecent',
  maxReviewsPerApp: 20,
  includeAppMetadata: true
});
console.log(run.defaultDatasetId);

MCP and AI agents

Focused Apify MCP server URL:

https://mcp.apify.com?tools=fetch_cat/apple-app-store-reviews-scraper

Example agent prompt: "Collect the 20 newest US App Store reviews for this app, then group complaints by app version and rating."

Support

Open an issue with the run ID, app ID or URL, country, and field that looks wrong so feed changes can be reproduced.