⭐ App Store Reviews Scraper - iOS & macOS Reviews avatar

⭐ App Store Reviews Scraper - iOS & macOS Reviews

Pricing

from $2.00 / 1,000 results

Go to Apify Store
⭐ App Store Reviews Scraper - iOS & macOS Reviews

⭐ App Store Reviews Scraper - iOS & macOS Reviews

Scrape customer reviews from any iOS/macOS app on the Apple App Store. Extract ratings (1-5 stars), review titles, full text, author names, app versions, vote counts, and dates. Perfect for App Store Optimization (ASO), sentiment analysis, competitor research, and market intelligence

Pricing

from $2.00 / 1,000 results

Rating

4.2

(2)

Developer

ben

ben

Maintained by Community

Actor stats

4

Bookmarked

124

Total users

9

Monthly active users

4 days ago

Last modified

Share

⭐ App Store Reviews Scraper — iOS & macOS App Ratings, Reviews & Feedback

Extract customer reviews from any app on the Apple App Store — star ratings, review titles, full review text, author, app version, vote counts and country — as clean, structured data for one app or a whole list of competitors. It runs on Apple's official iTunes RSS API across 50+ country storefronts, so there's no browser, no login, and no API key. Export to JSON/CSV/Excel, run on a schedule, call via API, or connect to Make, Zapier or n8n.

📱 What is the App Store Reviews Scraper?

It turns any iOS or macOS app into a structured reviews dataset. Give it App Store app IDs or full App Store URLs (the app ID is auto-extracted) plus the country storefronts you care about, and it returns every matching review with rating, text, author, version and helpfulness votes — so product, marketing and research teams can analyze sentiment without copy-pasting from the store.

What data does it extract?

  • rating — the 1–5 star score for each review
  • title and content — the review headline and full body text
  • author_name and author_uri — reviewer name and profile link
  • version — the app version the review was written for
  • vote_count and vote_sum — how many users voted and the net helpfulness
  • country — the storefront the review came from (50+ supported)
  • app_id, app_name and app_url — the app the review belongs to
  • review_id and updated_date — stable review ID and last-updated timestamp

⬇️ Input

Target apps by ID or URL, choose your storefronts, and set the cap:

FieldDescription
appIdsApp Store app IDs, e.g. ["333903271"] (X/Twitter)
appUrlsFull App Store URLs (app ID auto-extracted) — alternative to appIds
countriesCountry codes to pull from, e.g. ["us", "gb", "de", "jp"] (50+ supported)
maxReviewsMax reviews per app per country (0 = unlimited; ~500 cap from Apple's API)
sortBymostRecent or mostHelpful
delaySecondsDelay between requests (0.3–5, default 0.5)

Example input

{
"appIds": ["333903271", "389801252"],
"countries": ["us", "gb", "ca"],
"maxReviews": 300,
"sortBy": "mostRecent"
}

⬆️ Output

Every review is one clean row (view as a table, or export JSON / CSV / Excel):

{
"review_id": "10456789123",
"app_id": "333903271",
"app_name": "X",
"author_name": "JohnDoe123",
"author_uri": "https://itunes.apple.com/us/reviews/id12345678",
"rating": 4,
"title": "Great app but needs improvements",
"content": "The app works well for basic usage. However, I wish they would add dark mode and better notification controls...",
"version": "10.15.2",
"vote_count": 42,
"vote_sum": 38,
"country": "US",
"updated_date": "2026-06-15T10:30:00-07:00",
"app_url": "https://apps.apple.com/us/app/x/id333903271"
}

💡 Use cases

  • 🔍 App Store Optimization (ASO): track rating trends, surface complaints and feature requests for your apps.
  • 🧠 Sentiment analysis & ML: build labeled review datasets for NLP and brand-perception monitoring.
  • 🥊 Competitor research: compare review volume, ratings and weaknesses across rival apps.
  • 🐞 Product & QA insights: spot version-specific bugs by filtering reviews by app version.

❓ FAQ

How do I scrape App Store reviews? Give the actor one or more app IDs (or App Store URLs) and country codes, then run. It pulls ratings, titles, full review text, author, app version and vote counts via Apple's official iTunes RSS API — no browser.

Do I need an Apple developer account or API key? No. It uses public iTunes RSS endpoints, so no credentials are required.

How do I find an app's ID? It's the number after /id in the App Store URL — e.g. https://apps.apple.com/us/app/x/id333903271 has ID 333903271. You can also paste the full URL into appUrls and the ID is extracted for you.

Can I get reviews from multiple countries? Yes — pass a list of country codes (50+ supported including US, GB, CA, AU, DE, FR, JP). Reviews vary significantly by region, so multiple storefronts give wider coverage.

Can I scrape macOS app reviews too? Yes — any iOS or macOS app on the App Store works the same way.

How many reviews can I get per app? Up to ~500 per app per country. Apple's RSS API caps at ~10 pages of about 50 reviews each; use multiple countries to gather more.

Which sort order should I use? mostHelpful surfaces the highest-signal feedback for ASO; mostRecent is best for tracking the latest issues and bug reports.

Can I scrape several apps at once? Yes — pass multiple IDs/URLs to compare competitors side by side in a single dataset.

Can I run it on a schedule or via API? Yes — schedule recurring runs in Apify, call it via the API/SDK, or connect it to Make, Zapier or n8n.

Is scraping App Store reviews legal? It retrieves publicly available review data via Apple's official RSS feeds. Use it responsibly and respect Apple's Terms of Service and applicable laws.

🔗 You might also like


Keywords: App Store reviews scraper, iOS app reviews API, Apple App Store reviews, scrape app ratings, ASO tool, app review sentiment, customer review data, app store data, competitor review analysis, macOS app reviews, iTunes RSS reviews, app feedback scraper, app rating tracker, mobile app reviews.