App Store Review Scraper — iOS App Store reviews across 175 country storefronts

App Store reviews are served per storefront, so this Actor scrapes them for any iOS or iPadOS app across as many country storefronts as you choose — returning star rating, title, body, reviewer nickname, app version, helpful votes and country for every review. Because Apple stores reviews per country, your country list decides which reviews exist at all: a US-only run will never show you the German one-star reviews tanking your DACH conversion. No API key or login is needed — add your apps and countries, then click Start.

What you get

• rating, title, body, authorName and reviewedAt for each review.
• appVersion plus isCurrentVersion, so you can attribute complaints to a specific build.
• storefront on every row, tagging the country the review came from.
• helpfulVotes / totalVotes, and sentimentHint (deterministic, rule-based).
• reviewUid and contentHash for clean de-duplication across runs.
• An optional app profile row with ratings, price, genres, release notes and screenshots.

Quick start

1. Add your apps — a numeric App Store ID, bundle ID, full App Store URL, or name:Duolingo.
2. Add country storefronts — two-letter codes such as us, gb, de, fr, jp.
3. Set Max reviews per app (this is the number that controls your cost).
4. Click Start and read the Reviews and App profiles dataset tabs.

{
  "apps": ["310633997", "com.spotify.client"],
  "countries": ["us", "gb", "de"],
  "maxReviewsPerApp": 300
}

Want a free look first? Set Max reviews per app to 10 with one app and one country.

Example output

One representative review row:

{
  "recordType": "review",
  "ok": true,
  "errorCode": null,
  "reviewUid": "apple:310633997:us:14614285121",
  "reviewId": "14614285121",
  "appId": "310633997",
  "appName": "WhatsApp Messenger",
  "bundleId": "net.whatsapp.WhatsApp",
  "developerName": "WhatsApp Inc.",
  "storefront": "us",
  "rating": 2,
  "title": "Keeps crashing after update",
  "body": "Since 26.38 the app closes whenever I open a group chat.",
  "bodyChars": 56,
  "authorName": "appuser2024",
  "appVersion": "26.38.74",
  "isCurrentVersion": true,
  "helpfulVotes": 12,
  "totalVotes": 15,
  "reviewedAt": "2026-10-01T09:50:55.000Z",
  "sentimentHint": "negative",
  "contentHash": "7c1aa3f05be24d19",
  "scrapedAt": "2026-10-02T12:00:00.000Z"
}

Why storefront choice is the whole game

Apple stores reviews per country. A US-only run will never show you the German one-star reviews that are tanking your DACH conversion. This Actor takes a list of countries and a list of apps, so one run covers your whole market footprint instead of one run per app per country.

What this App Store review scraper does

• 🌍 Multi-country by design — pass ["us","gb","de","fr","jp"] and get every storefront in a single dataset, each row tagged with storefront.
• 🔢 Version-mapped reviews — appVersion plus isCurrentVersion means you can answer "did release 26.38 fix the sync complaints?" directly from the data. Join it against releaseNotes on the app profile row.
• 🪪 Four ways to name an app — numeric App Store ID, bundle ID (com.whatsapp.WhatsApp), a full App Store URL, or name:Duolingo to resolve the top search match.
• 🎯 Filters that cut your bill — minRating/maxRating, reviewedAfter and review keywords are applied before anything is written, so filtered reviews are never charged. Set both ratings to 1 to collect only one-star complaints.
• 🧮 Deterministic sentiment — sentimentHint buckets 1–2 stars as negative, 3 as neutral, 4–5 as positive. Rule-based, so it is reproducible and costs nothing. No LLM, no hidden third-party API fee.
• 🔁 Built for schedules — reviewUid deduplicates across runs and contentHash catches edited reviews, so you can diff two runs to get only what's new.
• 🛟 Honest failures — an app that does not exist in a storefront produces an ok: false row explaining exactly that, and every other storefront still lands.

Running on Apify adds scheduling, webhooks, monitoring, API and SDK access, and one-click export to JSON, CSV, Excel, Google Sheets and 20+ integrations.

How to use it

1. Add your apps to Apps. Competitor apps work just as well as your own.
2. Add the storefronts to Country storefronts — two-letter codes such as us, gb, de, fr, es, it, br, jp, kr, in.
3. Set Max reviews per app. This is the number that determines your cost.
4. Choose Most recent for monitoring, Most helpful for the reviews Apple actually shows shoppers.
5. Optionally narrow with star range, Reviewed after, or Review keywords such as crash, refund, login.
6. Click Start, then use the Reviews, Release quality and App profiles dataset tabs.

How do I track only new reviews?

Set Reviewed after to a relative value like 7 days, schedule the Actor daily, and deduplicate downstream on reviewUid. With Most recent sorting the Actor also stops paging once it is past your cutoff, so a daily run is cheap.

Full example input and output

{
  "apps": ["310633997", "com.spotify.client", "name:Duolingo"],
  "countries": ["us", "gb", "de"],
  "maxReviewsPerApp": 300,
  "maxReviewsPerCountry": 200,
  "sortBy": "mostRecent",
  "includeAppProfile": true,
  "minRating": 1,
  "maxRating": 3,
  "reviewedAfter": "30 days",
  "keywords": ["crash", "subscription"]
}

An app profile row from the same run:

{
  "recordType": "app",
  "ok": true,
  "appId": "310633997",
  "appName": "WhatsApp Messenger",
  "developerName": "WhatsApp Inc.",
  "storefront": "us",
  "formattedPrice": "Free",
  "isFree": true,
  "primaryGenre": "Social Networking",
  "genres": ["Social Networking", "Utilities"],
  "averageUserRating": 4.7,
  "userRatingCount": 15324991,
  "averageUserRatingCurrentVersion": 4.6,
  "userRatingCountCurrentVersion": 48211,
  "version": "26.38.74",
  "currentVersionReleaseDate": "2026-09-28T14:02:11Z",
  "releaseNotes": "Bug fixes and performance improvements.",
  "contentAdvisoryRating": "12+",
  "minimumOsVersion": "15.0",
  "screenshotCount": 8,
  "appStoreUrl": "https://apps.apple.com/us/app/whatsapp-messenger/id310633997"
}

Use cases

• Release triage — group negative reviews by appVersion to find out which build broke what.
• Competitor intelligence — scrape rivals' one- and two-star reviews to find the feature gaps their users complain about.
• Localisation and market priority — compare averageUserRating and complaint themes across storefronts.
• Voice-of-customer feeds — pipe body into an LLM or a BI tool; the text is already clean.
• ASO and store-listing research — pair with the App Store Search & ASO Keyword Scraper to see where an app ranks and how users respond to it.
• Support deflection — alert on new one-star reviews containing refund, charged or cancel.

How much does it cost to scrape App Store reviews?

Pricing is pay per event:

Event	What triggers it	Billed
Review	One review written to the dataset	per review
App profile	One app metadata row per app and storefront	per profile row
Actor start	Once per run, platform fee	per run

Reviews removed by your filters are not billed, because they are never written. Apps that cannot be resolved are not billed either.

A concrete example: 3 apps × 3 countries × 200 reviews = 1,800 review events, plus 9 app profile rows. Multiply by the per-review price and that is your total. Compute, bandwidth and storage are included — there is no separate platform-usage charge on top.

Set Max cost per run in the run options for a hard ceiling; the Actor stops cleanly and says so in the log. Higher Apify plans get progressively lower per-review pricing through Apify Store tier discounts.

Related Actors by Axiora Solutions

Actor	Use it for
App Store Search & ASO Keyword Scraper	Keyword rankings, competitor discovery and top-chart positions for the same apps
News & RSS Feed Scraper	Catch press and release coverage about the apps you monitor
Domain Contact Enricher	Enrich the developer websites behind the apps into contactable company records

Frequently asked questions

How many reviews can I actually get per app?

Apple's public customer-reviews feed serves up to 500 reviews per app per country storefront — 10 pages of 50. That is a hard platform limit, not a limit of this Actor. The way to get more volume is more storefronts, which is exactly why countries is an array. Note that userRatingCount on the app profile row is often in the millions; that is the number of ratings, while only the most recent or most helpful 500 written reviews per storefront are published.

Does it scrape Google Play too?

Not in this version. This Actor is Apple-only on purpose: Apple publishes a stable public feed, which is why it is reliable enough to run on a schedule. Google Play has no equivalent public endpoint, so bolting it on here would make the Actor fail unpredictably and would be dishonest about what you are paying for.

What personal data does it return?

Only the public nickname the reviewer chose to display on the App Store, plus the review text itself. Apple publishes no real name, no e-mail address and no other identifier, and this Actor does not attempt to resolve one. You are responsible for your lawful basis when processing review text.

Why is a review in a language I did not expect?

Because storefront and language are different things. German-storefront reviews are usually German, but Apple does not restrict language. Keep storefront on every row and filter downstream.

Why did an app return nothing for one country?

Either the app is not published in that storefront, or it has no written reviews there. You will get an ok: false row with NOT_FOUND in the first case, and simply no review rows in the second. Both are visible in the run summary.

Is sentimentHint a real sentiment model?

No, and it does not pretend to be. It is a deterministic mapping of the star rating. That makes it free, reproducible and auditable. If you want genuine text sentiment, send body to your own model — you will not be paying this Actor for an opaque inference.

Can I run this on a schedule?

Yes. Daily with Reviewed after set to 2 days and Most recent sorting is the cheap monitoring pattern. Deduplicate on reviewUid.

Something looks wrong — how do I report it?

Open the Issues tab on this Actor page with the app ID, the storefront and what you expected to see.

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Runnable examples and how-to guides for these Actors: github.com/batow133/axiora-apify-actors