# App Store Reviews Scraper | No Personal Data (`datamill.top/app-store-reviews-scraper`) Actor Scrape Apple App Store reviews, ratings and app metadata. Review text, titles, scores, dates and app versions. No author names or profile links — GDPR-safe output. Apple caps its public feed at 500 reviews per app per country; collect across storefronts for more. - **URL**: https://apify.com/datamill.top/app-store-reviews-scraper.md - **Developed by:** [Alexandr Gobozov](https://apify.com/datamill.top) (community) - **Categories:** - **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/actors/running/actors-in-store.md#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 ## App Store Reviews Scraper — App Data & Ratings, No Personal Data Scrape Apple App Store reviews, ratings, and full app metadata from any iOS app. This App Store scraper extracts review titles, review text, star scores, dates, app versions, and helpful votes, plus complete app listing data: price, category, release date, current version, and rating count. **Reviewer names and profile links are never collected.** Every review is returned with an irreversible pseudonymous hash instead of a nickname, so you get the analysis you need without holding personal data. See [Privacy and GDPR](#privacy-and-gdpr) below. Output uses the same field names as our [Google Play Reviews Scraper](https://apify.com/datamill.top/google-play-reviews-scraper), so both stores merge into one table without renaming a single column. > **Unofficial tool.** This Actor is not affiliated with, sponsored by, or endorsed by > Apple Inc. "App Store" and "Apple" are trademarks of Apple Inc. This Actor reads only > Apple's own publicly available endpoints. ### Pricing Currently **free** — you only pay Apify platform usage for the compute a run consumes. No per-result fee on top. ### The one limit you need to know first Apple's public review feed returns **at most 500 reviews per app per country storefront** — 10 pages of 50. There is no way around it, and any scraper claiming otherwise for the public feed is either paginating the same 500 rows or reading a private endpoint. Two things actually work, and this actor is built for both: - **Collect from several storefronts.** The cap is per country. Ten countries means up to 5,000 reviews for the same app, and you get a useful per-market breakdown for free. Put the codes in `countries`. - **Run it on a schedule.** Set `reviewsSince` to yesterday and run daily. The 500-review window keeps moving, so your own dataset grows past the cap over time. If you own the app, Apple's App Store Connect API returns your complete review history with no cap. That needs your own API key and is a different tool. ### What this App Store scraper extracts **App data** — title, developer, developer website, bundle ID, price, currency, average rating, rating count, current-version rating and count, content rating, genre and genre list, version, release date, last update date, minimum iOS version, download size, icon, store URL, supported languages, description, release notes, iPhone and iPad screenshots. **Review data** — review title, review text, star rating (1–5), review date, app version the review was written on, helpful votes, total votes, storefront, pseudonymous author hash with duplicate-nickname indicators. ### Why choose this iOS app scraper - **No personal data.** No nicknames, no profile links, no developer contact details. Nothing in the output identifies a person. - **Merges with Google Play.** Field names, date format, and the author-hash scheme are identical to our Google Play actor. Concatenate the two datasets and every column lines up. Rows carry a `source` field so you can always tell them apart. - **Reliable dates.** Apple returns review timestamps in the storefront's own offset — `-07:00` for the US, `+02:00` for Germany. This scraper converts everything to UTC in ISO 8601, so a column sorted across markets is actually sorted. The original release date string is kept in `releasedText`. - **Handles messy input.** Paste a full App Store URL, an `id310633997` fragment, a bare numeric ID, or an iOS bundle ID like `net.whatsapp.WhatsApp`. Bundle IDs are resolved automatically. Duplicates are removed, so you never pay twice for the same app. - **Retries built in.** Four attempts with exponential backoff on every request. One unavailable app never kills the whole run — you get the rest of your data plus a clear warning in the log. - **Incremental scraping.** Set `reviewsSince` to a date and the scraper stops paging as soon as it reaches older reviews. - **Efficient metadata.** App cards are fetched in batches of 20 through Apple's official lookup endpoint — one request per 20 apps instead of one per app. ### Use cases **App Store Optimization (ASO)** — track rating trends and metadata changes for your app and competitor apps across markets. **Review analysis and sentiment analysis** — export review titles and text to your own pipeline, LLM, or spreadsheet to find recurring complaints, feature requests, and bugs. App Store reviews carry a title, which is often a cleaner sentiment signal than the body. **Cross-platform comparison** — run this actor and the Google Play one on the same product, stack the two datasets, and compare complaint mix between iOS and Android without any column mapping work. **Release monitoring** — filter reviews by `appVersion` to see exactly how sentiment changed after a release. **Market comparison** — the same app scraped across `us`, `gb`, `de`, `br`, and `jp` gives you five separate review pools plus five separate price and rating snapshots. **Fake review detection** — `authorHashCount` and `authorHashApps` reveal nicknames appearing across multiple apps, without exposing who wrote what. ### Input Give the scraper app IDs, a search query, or both. ```json { "appIds": [ "310633997", "https://apps.apple.com/us/app/spotify/id324684580", "net.whatsapp.WhatsApp" ], "searchQuery": "habit tracker", "maxAppsFromSearch": 10, "scrapeAppDetails": true, "scrapeReviews": true, "maxReviewsPerApp": 500, "reviewsSort": "newest", "reviewsSince": "2026-01-01", "countries": ["us", "gb", "de"] } ``` | Field | Description | |---|---| | `appIds` | Numeric App Store IDs, bundle IDs, or app page URLs. Duplicates removed automatically. | | `searchQuery` | Search the App Store instead of listing IDs. | | `maxAppsFromSearch` | How many search results to scrape. | | `scrapeAppDetails` | Return the app listing data. | | `scrapeReviews` | Return reviews. Set `maxReviewsPerApp` to 0 to skip. | | `maxReviewsPerApp` | Reviews per app **per country**, up to Apple's cap of 500. | | `reviewsSort` | `newest` or `helpfulness`. Apple's feed has no sort by rating. | | `filterByScore` | Only reviews with this star rating (1–5). Applied after fetching — see below. | | `reviewsSince` | `YYYY-MM-DD`. Stops early once older reviews are reached. | | `countries` | Two-letter storefront codes. Each one has its own reviews, prices, and its own 500-review cap. | | `country` | Shortcut for a single storefront. Ignored when `countries` is set. | | `includeDescription` | Turn off for a lighter dataset without description and screenshots. | | `annotateAuthorCollisions` | Adds duplicate-nickname indicators to reviews. | | `maxConcurrency` | Parallel requests, 1–10. | **About `filterByScore`.** Apple has no server-side score filter, so filtering happens after the feed is fetched. Setting it to 1 gives you the one-star reviews *out of the 500 reachable ones* — not 500 one-star reviews. Most scrapers do the same thing without telling you. ### Output Results go to a single dataset. App rows have `"type": "app"`, review rows have `"type": "review"`, and every row carries `"source": "app_store"`, so you can filter, split, or merge with Google Play data after export to JSON, CSV, Excel, or Google Sheets. App record, shortened: ```json { "type": "app", "source": "app_store", "appId": "310633997", "bundleId": "net.whatsapp.WhatsApp", "country": "us", "title": "WhatsApp Messenger", "developer": "WhatsApp Inc.", "installs": null, "realInstalls": null, "score": 4.7, "ratings": 12345678, "histogram": null, "free": true, "price": 0, "currency": "USD", "genre": "Social Networking", "contentRating": "12+", "released": "2009-05-03T07:00:00+00:00", "releasedText": "2009-05-03T07:00:00Z", "updated": "2026-09-01T18:00:00+00:00", "version": "25.1.0", "minimumOsVersion": "15.1", "fileSizeBytes": 243167232, "scrapedAt": "2026-09-07T12:04:11+00:00" } ``` Review record: ```json { "type": "review", "source": "app_store", "appId": "324684580", "country": "us", "reviewId": "12345678901", "reviewTitle": "Sync finally works", "content": "Solid update, playlists sync across devices now.", "score": 5, "thumbsUpCount": 7, "voteCount": 9, "appVersion": "9.1.78", "at": "2026-09-04T18:23:07+00:00", "replyContent": null, "repliedAt": null, "authorHash": "667312a54c6ae870", "authorHashCount": 1, "authorHashApps": 1, "authorHashCountries": 1, "scrapedAt": "2026-09-07T12:04:11+00:00" } ``` #### Fields that are always null, and why These columns exist so the App Store dataset stacks cleanly on the Google Play one. An empty column is more honest than a missing one: you can see at a glance that the data does not exist rather than wondering whether it was skipped. | Field | Why it is empty | |---|---| | `installs`, `realInstalls` | Apple does not publish download counts for any app. | | `histogram` | Apple does not publish the 1–5 star breakdown in a public endpoint. | | `replyContent`, `repliedAt` | Developer replies are not included in Apple's public review feed. Google Play does include them, so the columns stay for cross-store alignment. | Fields that exist here but not on Google Play: `reviewTitle`, `voteCount`, `bundleId`, `minimumOsVersion`, `fileSizeBytes`, `authorHashCountries`, `country`. ### Privacy and GDPR App Store reviewer nicknames are personal data under the GDPR. This scraper does not return them. Each review carries `authorHash` — a salted SHA-256 hash of the display nickname, truncated to 16 characters. The same nickname always produces the same hash, so you can still group reviews by author, but the nickname cannot be recovered from the hash. **Apple's feed also contains a link to each reviewer's profile — a stable user ID. We do not read it and do not hash it.** Hashing a real user ID would let anyone track one individual reliably across every app they have ever reviewed. That is profiling, and it is not what this tool is for. The hash is derived from the nickname instead, which is weaker on purpose. Three fields tell you exactly how much to trust it: - `authorHashCount` — how many reviews in this run share the hash. A large number means a very common nickname that should not be treated as one person. - `authorHashApps` — how many different apps the hash appeared in. - `authorHashCountries` — how many different storefronts. A repeat across storefronts almost always means different people, since markets do not share an audience. One Apple ID can leave only one review per app. A repeated hash **within a single app and storefront** therefore always means different people with the same nickname. A repeat **across different apps in the same storefront** may be the same reviewer and is worth a closer look. The salt is configurable through the `AUTHOR_HASH_SALT` environment variable. Set the same salt here and in the Google Play actor and the hashes stay comparable across both stores. ### Integrations Run this App Store scraper from the Apify API, schedule it to monitor app reviews daily, or connect it to Make, Zapier, Google Sheets, Slack, or an MCP client. Results export as JSON, CSV, Excel, XML, or RSS. ### FAQ **How many reviews can I scrape from an App Store app?** 500 per app per country storefront, which is Apple's own limit on the public feed. Add countries to `countries` to multiply that, or schedule daily runs to accumulate history. **Can I get more than 500 reviews for one app in one country?** Not from any public source. If it is your own app, App Store Connect gives you all of them with an API key you own. **Why are `replyContent` and `repliedAt` always empty?** Apple's public review feed does not carry developer responses. The columns exist so the output lines up with the Google Play dataset, where they are populated. **Can I scrape only negative reviews?** Set `filterByScore` to 1 or 2. Note that filtering runs after fetching, so you get the low-rated share of the 500 reachable reviews. **Does it work with Google Play apps?** No — use our Google Play Reviews Scraper for Android. The two produce the same output schema on purpose, so you can run both and merge the results. **Why is the reviewer name missing?** By design — see [Privacy and GDPR](#privacy-and-gdpr). Use `authorHash` to group reviews by author without storing personal data. **Is scraping the App Store legal?** This actor reads Apple's official public RSS review feed, lookup endpoint, and search endpoint. It does not authenticate, does not bypass any technical protection, and does not access private data. You remain responsible for how you use the data under the laws that apply to you. This is not legal advice. **Is this an official Apple tool?** No. It is an independent, unofficial Actor with no affiliation to Apple Inc. It reads only endpoints Apple publishes openly, and it holds no special access or partnership. # Actor input Schema ## `appIds` (type: `array`): Numeric App Store IDs, bundle IDs, or full app page URLs. Find the ID in the App Store URL after /id, e.g. 310633997 in apps.apple.com/us/app/whatsapp-messenger/id310633997 ## `searchQuery` (type: `string`): Instead of listing app IDs, search the store. Results are added to App IDs above. ## `maxAppsFromSearch` (type: `integer`): How many apps to take from the search results. ## `scrapeAppDetails` (type: `boolean`): Title, developer, price, rating, version, category, release date, screenshots. ## `scrapeReviews` (type: `boolean`): Review title, text, score, date and app version. Author name and profile link are never returned. ## `maxReviewsPerApp` (type: `integer`): Apple's public review feed is capped at 500 reviews per app per country storefront. Higher values are clamped to 500. Set 0 to skip reviews entirely. Add more countries to collect more. ## `reviewsSort` (type: `string`): Newest is the usual choice for monitoring. Apple's feed offers no sort by rating — use the score filter below instead. ## `filterByScore` (type: `integer`): Leave empty for all. Apple has no server-side score filter, so this is applied after fetching: you get the 1-star reviews out of the 500 reachable ones, not 500 one-star reviews. ## `reviewsSince` (type: `string`): Format YYYY-MM-DD. Works with Newest first. Useful for daily monitoring. ## `annotateAuthorCollisions` (type: `boolean`): Adds authorHashCount, authorHashApps and authorHashCountries to each review. One Apple ID can leave only one review per app, so a repeated hash within a single app means different people with the same nickname. A repeat across apps may mean the same reviewer. A repeat across storefronts usually means different people. ## `countries` (type: `array`): Two-letter codes, e.g. us, gb, de. Each storefront has its own reviews, prices and its own 500-review cap, so adding countries is the way to get more reviews for one app. Defaults to us. ## `country` (type: `string`): Shortcut for one storefront, kept for input compatibility with our Google Play actor. Ignored when Country storefronts above is filled in. ## `includeDescription` (type: `boolean`): Turn off for a lighter dataset when you only need numbers. ## `maxConcurrency` (type: `integer`): Higher is faster but more likely to be rate limited by Apple. ## Actor input object example ```json { "appIds": [ "310633997" ], "searchQuery": "note taking", "maxAppsFromSearch": 10, "scrapeAppDetails": true, "scrapeReviews": true, "maxReviewsPerApp": 200, "reviewsSort": "newest", "reviewsSince": "2026-01-01", "annotateAuthorCollisions": true, "countries": [ "us" ], "includeDescription": true, "maxConcurrency": 5 } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "appIds": [ "310633997" ], "countries": [ "us" ] }; // Run the Actor and wait for it to finish const run = await client.actor("datamill.top/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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "appIds": ["310633997"], "countries": ["us"], } # Run the Actor and wait for it to finish run = client.actor("datamill.top/app-store-reviews-scraper").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 '{ "appIds": [ "310633997" ], "countries": [ "us" ] }' | apify call datamill.top/app-store-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,datamill.top/app-store-reviews-scraper" } } } ``` 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 ` 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/Ha1dhl8ssRseQtLdK/builds/11cKGSKRY5Ng0hGB8/openapi.json