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Apple App Store Scraper

Pricing

from $1.60 / 1,000 scraped apps

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Apple App Store Scraper

Apple App Store Scraper

Scrape public Apple App Store app data and reviews. Search apps by keyword, look up app IDs or URLs, collect top charts, and export ratings, prices, developers, genres, versions, and review text.

Pricing

from $1.60 / 1,000 scraped apps

Rating

0.0

(0)

Developer

Maxime Dupré

Maxime Dupré

Maintained by Community

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1

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a day ago

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🍎 Apple App Store scraper for apps, charts, and reviews

Apple App Store Scraper collects public iOS app data from the Apple App Store. Search by keyword, look up apps by App Store URL or numeric app ID, pull top chart apps, or export public App Store reviews for product research, ASO work, competitor monitoring, and reporting.

Use this Apple App Store scraper when you need app names, developers, bundle IDs, genres, prices, ratings, versions, source URLs, storefronts, and public review text in one clean Apify dataset. You can export the results as JSON, CSV, Excel, XML, RSS, or HTML, run the Actor through the Apify API, schedule repeat checks, or connect the data to webhooks and integrations.

You do not need an Apple Developer account, App Store Connect access, cookies, or an API key. For a small first run, keep the prefilled Spotify App Store URL and run App details mode to preview the app row shape before adding more app IDs, URLs, search terms, or chart settings.

✅ What this Actor does

  • Looks up public App Store app details from app URLs or numeric app IDs.
  • Searches Apple App Store apps by keyword.
  • Collects apps from Apple top chart feeds.
  • Scrapes public App Store reviews for one or more apps.
  • Can add public review rows alongside app rows in app details, search, and top chart modes.
  • Supports country storefront settings such as United States, Canada, United Kingdom, Germany, France, Japan, India, and more.
  • Saves one dataset item per app or review.
  • Adds source target, target type, source URL, source rank, storefront country, and scrape time.
  • Runs without user-provided Apple credentials.

This Actor is focused on public Apple App Store data. It does not scrape private App Store Connect analytics, paid campaign data, TestFlight builds, in-app purchase reports, subscriber data, private developer dashboards, or historical archives beyond what Apple exposes publicly.

📦 Data you can extract

🍏 App rows

App rows can include:

  • rowType - app
  • target and targetType
  • sourceUrl and sourceRank
  • appId and bundleId
  • appName
  • developer and developerUrl
  • primaryGenre and primaryGenreId
  • price, currency, and formattedPrice
  • rating and ratingCount
  • version
  • country
  • scrapedAt

Some fields can be empty when Apple does not expose them for a specific app, country storefront, chart, or search result.

⭐ Review rows

Review rows can include:

  • rowType - review
  • target, targetType, sourceUrl, and sourceRank
  • appId
  • reviewId
  • reviewTitle and reviewText
  • reviewRating
  • reviewAuthor
  • country
  • scrapedAt

Apple review availability can vary by storefront and app. If a selected app has no public reviews in the chosen country, the Actor completes the run and reports that no public reviews were found for that app.

🚀 Common use cases

  • Find iOS apps for App Store keywords such as photo editor, habit tracker, or budget planner.
  • Build Apple App Store datasets for ASO research, category research, or app market maps.
  • Track competitor app metadata, ratings, pricing, versions, and storefront availability.
  • Collect public App Store reviews for product feedback, support triage, sentiment analysis, or feature request research.
  • Pull top free, top paid, top grossing, and new app chart data for market monitoring.
  • Schedule repeat App Store checks and send results to spreadsheets, BI tools, APIs, webhooks, or internal workflows.

▶️ How to run it

  1. Choose a Mode: app details, search apps, app reviews, or top charts.
  2. Add App Store targets when the mode needs them.
  3. Pick the App Store Country storefront.
  4. Keep the app and review limits low for a preview run.
  5. Start the Actor and open the dataset.

Use App Store URLs or numeric app IDs for app details and reviews:

{
"mode": "lookup",
"targets": [
"https://apps.apple.com/us/app/spotify-music-and-podcasts/id324684580",
"570060128"
],
"country": "us",
"maxAppsPerTarget": 10,
"includeReviews": false,
"reviewLimit": 25,
"reviewSort": "mostRecent",
"chartCollection": "top-free"
}

Use keywords for search mode:

{
"mode": "search",
"targets": ["photo editor", "fitness tracker"],
"country": "us",
"maxAppsPerTarget": 25,
"includeReviews": true,
"reviewLimit": 10,
"reviewSort": "mostRecent",
"chartCollection": "top-free"
}

Use top charts mode when you want Apple chart feeds. In this mode, the Actor uses the selected chart and country; the targets field is ignored.

⚙️ Input options

FieldWhat it does
modeSelects app lookup, app search, app reviews, or top charts.
targetsApp Store URLs or numeric app IDs for lookup and reviews; keyword strings for search. Ignored in top charts mode.
maxAppsPerTargetCaps app rows for each lookup target, search term, or chart run.
reviewLimitCaps public review rows per app, up to Apple's RSS review limit.
includeReviewsAdds public review rows when running app details, search, or top charts.
reviewSortRequests most recent or most helpful public reviews from Apple.
countryChooses the two-letter Apple storefront country.
chartCollectionChooses the Apple top chart feed for top charts mode.
categoryIdsOptional App Store genre IDs. Search uses the first ID; top charts filter fetched app details after lookup.

🧾 Output example

{
"rowType": "app",
"target": "photo editor",
"targetType": "search",
"sourceUrl": "https://apps.apple.com/us/app/example/id123456789",
"sourceRank": 1,
"appId": "123456789",
"appName": "Example Photo Editor",
"bundleId": "com.example.photo",
"developer": "Example Developer",
"developerUrl": "https://apps.apple.com/us/developer/example/id987654321",
"primaryGenre": "Photo & Video",
"primaryGenreId": "6008",
"price": 0,
"currency": "USD",
"formattedPrice": "Free",
"rating": 4.7,
"ratingCount": 12345,
"version": "1.2.3",
"country": "us",
"scrapedAt": "2026-05-28T12:00:00.000Z"
}

💳 Pricing

This Actor uses pay-per-event pricing. App rows and review rows are charged as separate scraped results, so a run with Include reviews with app rows turned on can create both app charges and review charges.

Keep the default limits for a small preview, then raise maxAppsPerTarget or reviewLimit when the output matches your workflow.

⚠️ Limits and caveats

  • Apple data can vary by country storefront.
  • App search and top chart order follow the public Apple source for the selected storefront and settings.
  • Public review availability depends on the app, country, and Apple RSS feed.
  • Top chart category filtering is applied after app details are fetched, so a filtered chart can return fewer rows than the requested app limit.
  • The Actor only returns data Apple exposes publicly. It does not access private developer, user, or analytics data.

❓ FAQ

Do I need an Apple account?

No. The Actor uses public Apple App Store surfaces and does not require an Apple Developer account, App Store Connect access, cookies, or an API key.

Can I scrape App Store reviews?

Yes. Use App reviews mode for review-only runs, or turn on Include reviews with app rows when running app details, search, or top charts.

Can I use this as an Apple App Store API?

Yes, for public App Store data returned by this Actor. You can run it through the Apify API, schedule it, export datasets, or connect it to webhooks and integrations.

Why did a run return fewer apps than my limit?

Apple may return fewer public results for a keyword, country, chart, or category filter than the limit you requested. Top chart category filtering can also reduce the final row count after app details are checked.

📝 Changelog

  • 0.0: Initial release.

🆘 Support

For issues, questions, or feature requests, file a ticket and I'll fix or implement it in less than 24h 🫡

🔗 Other actors

Made with ❤️ by Maxime Dupré