App Store & Google Play Reviews Scraper

Scrape thousands of user reviews from the Apple App Store and Google Play — by app ID or app name — and export them to Excel, CSV, or JSON. Pull star ratings, full review text, review titles, app versions, up-votes, developer replies, and derived sentiment for App Store Optimization (ASO), sentiment analysis, competitor research, and product feedback mining. No API key, no login, no scraping headaches.

This Actor is built for the review corpus itself — not just app metadata or top-chart rankings. Point it at any app (yours or a competitor's) and walk away with a clean, structured dataset of what real users are saying, ready for analysis.

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What this Actor does

• Collects user reviews from both major app stores in one run:
  • Google Play — deep, reliable pagination pulls thousands of reviews per popular app.
  • Apple App Store — the public customer-reviews feed, swept across multiple storefronts (US, UK, CA, AU, …) to maximize volume.
• Accepts app package names (Google Play, e.g. com.spotify.music), numeric Apple track IDs (e.g. 324684580), or a plain app-name search (e.g. Duolingo) that is resolved automatically on each store.
• Returns rich, analysis-ready rows: rating (as a real number 1–5), title, text, helpful votes, app version, review date (ISO 8601), developer reply, and an auto-derived sentiment label.
• Runs with completely empty input — a bare run returns 1,000+ reviews across a set of hugely-popular apps so you can see the output shape instantly.
• Ships with a time budget and automatic Apify Proxy + direct-connection fallback, so large jobs stay fast, cheap, and resilient.

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Use cases

• App Store Optimization (ASO) — mine the exact language users use in reviews to inform your keywords, title, and description. Track how ratings and sentiment shift after each release.
• Sentiment analysis — feed the review text and derived sentiment into your own NLP / LLM pipeline to quantify user happiness over time and by app version.
• Competitor research — scrape a competitor's reviews to find what their users love, hate, and beg for. Spot their weaknesses before your next release.
• Feature-request & pain-point discovery — surface recurring complaints, crashes, and requested features straight from the people who use the app daily.
• Product & CX teams — build a searchable archive of customer voice across both stores and every storefront, complete with developer-reply tracking.
• Market & investment research — gauge reception of any consumer app at scale, across countries and languages, without touching an official API.
• Reputation monitoring — schedule the Actor to run daily and alert on drops in rating or spikes in negative sentiment.

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Input

Every field is optional. Run the Actor with an empty input {} and it will scrape reviews for a set of hugely-popular apps (WhatsApp, Instagram, Spotify, TikTok, Netflix) so you always get data back.

Field	Type	Description
store	select	Which store(s) to scrape: Both (default), Google Play only, or Apple App Store only.
appIds	list of strings	Apps to scrape. Use the Google Play package name (com.spotify.music) for Google Play and the numeric Apple track ID (324684580) for the App Store. You can mix both in one list — package names route to Google Play, numeric IDs route to the App Store. Leave empty to use popular defaults.
appQuery	string	Optionally resolve an app by name (e.g. Duolingo) instead of an ID. The top match on each selected store is scraped. Combined with any appIds above.
country	select	Primary storefront / region. Sets the Google Play country and the main App Store storefront. Default United States.
language	select	Language for Google Play reviews (ISO 639-1). Default English.
sort	select	Most recent (default), Most helpful, or Highest rating (Google Play). The App Store maps "Most helpful" to its Most Helpful feed.
maxReviews	integer	Maximum total reviews to collect across all apps and stores. Default 1000. Raise it to pull more; large jobs are bounded by a ~4-minute time budget.
appleCountries	list of strings	Advanced. Explicit App Store storefront codes to sweep (e.g. ["us","gb","ca","au","de"]). Each storefront exposes up to ~500 reviews per app, so more storefronts = more App Store volume. Leave empty for sensible defaults.
proxy	proxy	Apify Proxy configuration. Automatic proxy is recommended; the App Store fetcher also falls back to a direct connection if a proxy IP fails.

Example inputs

1. Bare run (returns 1,000+ reviews across popular apps):

{}

2. One specific app on both stores, up to 5,000 reviews:

{
  "appIds": ["com.spotify.music", "324684580"],
  "maxReviews": 5000,
  "sort": "newest"
}

3. Resolve an app by name, Google Play only, Spanish reviews from Mexico:

{
  "store": "google_play",
  "appQuery": "Duolingo",
  "country": "mx",
  "language": "es",
  "maxReviews": 2000
}

4. Apple App Store only, swept across five big storefronts:

{
  "store": "app_store",
  "appIds": ["389801252"],
  "appleCountries": ["us", "gb", "ca", "au", "de"],
  "maxReviews": 2000
}

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Output

Each row is a single review. Open the Dataset tab to browse, filter, and export as CSV, JSON, Excel, HTML, or XML. Numeric fields are stored as real numbers so you can sort and aggregate them directly.

Field	Type	Description
appId	string	Google Play package name or Apple track ID the review belongs to.
appName	string	Human-readable app name.
store	string	google_play or app_store.
country	string	Storefront / country code the review was pulled from.
reviewId	string	Unique identifier of the review within its store.
userName	string	Display name of the reviewer.
rating	number	Star rating from 1 to 5.
title	string	Review title / headline (App Store; usually empty on Google Play).
text	string	Full body text of the review.
thumbsUp	number	Up-votes / helpful votes on the review.
helpfulCount	number	Helpful-vote count (mirrors up-votes).
reviewCreatedVersion	string	App version the review was written against, when available.
appVersion	string	App version associated with the review.
reviewDate	string	When the review was posted / last updated (ISO 8601).
developerReplyText	string	The developer's reply text, when present (Google Play).
developerReplyDate	string	Date of the developer's reply (ISO 8601), when present.
sentiment	string	Auto-derived from the rating: positive (4–5), neutral (3), negative (1–2).
url	string	Link to the review or reviewer profile.

Sample output

[
  {
    "appId": "com.spotify.music",
    "appName": "Spotify: Music and Podcasts",
    "store": "google_play",
    "country": "us",
    "reviewId": "abc247bd-ae0f-465d-be60-fcaff9763042",
    "userName": "Jordan M.",
    "rating": 5,
    "title": null,
    "text": "Best music app out there. The Discover Weekly playlist is scary good.",
    "thumbsUp": 34,
    "helpfulCount": 34,
    "reviewCreatedVersion": "8.9.72.609",
    "appVersion": "8.9.72.609",
    "reviewDate": "2026-07-12T07:12:41.980Z",
    "developerReplyText": "Thanks for the love, Jordan! 🎵",
    "developerReplyDate": "2026-07-12T10:03:00.000Z",
    "sentiment": "positive",
    "url": "https://play.google.com/store/apps/details?id=com.spotify.music&reviewId=abc247bd-ae0f-465d-be60-fcaff9763042"
  },
  {
    "appId": "324684580",
    "appName": "Spotify: Music and Podcasts",
    "store": "app_store",
    "country": "gb",
    "reviewId": "14292661215",
    "userName": "tunes_lover_88",
    "rating": 2,
    "title": "Shuffle isn't random",
    "text": "Keeps playing the same ten songs. Please fix the shuffle algorithm.",
    "thumbsUp": 0,
    "helpfulCount": 0,
    "reviewCreatedVersion": "8.9.72",
    "appVersion": "8.9.72",
    "reviewDate": "2026-07-11T20:54:50-07:00",
    "developerReplyText": null,
    "developerReplyDate": null,
    "sentiment": "negative",
    "url": "https://itunes.apple.com/gb/reviews/id1803720282"
  }
]

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Export formats

Everything the Actor collects is stored in a standard Apify Dataset, which you can export from the UI or pull via API:

• Excel (.xlsx) — one click from the Dataset tab; perfect for slicing reviews in a spreadsheet.
• CSV — for BI tools, pandas, or Google Sheets.
• JSON / JSONL — for pipelines, LLMs, and data warehouses.
• HTML / XML / RSS — for quick sharing and integrations.

You can also fetch the data programmatically:

https://api.apify.com/v2/datasets/{datasetId}/items?format=csv

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Frequently asked questions

How do I scrape App Store reviews?

Set store to Apple App Store only (or Both) and add the app's numeric Apple track ID to appIds — for example 389801252 for Instagram. You can find the ID in the App Store URL (apps.apple.com/app/id389801252) or just use the appQuery field with the app's name and let the Actor resolve it. The Actor pulls reviews from the public customer-reviews feed and can sweep multiple storefronts to gather more.

How do I scrape Google Play reviews?

Set store to Google Play only (or Both) and add the app's package name to appIds — for example com.spotify.music. The package name is the id= part of the Play Store URL (play.google.com/store/apps/details?id=com.spotify.music). The Actor paginates through Google Play and can return thousands of reviews per popular app.

Do I need an API key or developer account?

No. This Actor uses publicly available review feeds and requires no API key, no OAuth, and no login. Just provide an app ID or name and run it.

How do I export Google Play reviews to Excel?

Run the Actor, open the Dataset tab, and click Export → Excel (.xlsx). You'll get a spreadsheet with one review per row and columns for rating, text, date, version, sentiment, and more. CSV and JSON exports are available from the same menu, and via the dataset API URL shown above.

How many reviews can I scrape per app?

On Google Play, popular apps yield thousands of reviews via pagination — set maxReviews as high as you need (bounded by a ~4-minute time budget per run; raise it and re-run for very large corpora). On the App Store, each storefront exposes up to roughly 500 reviews per app, so add more appleCountries to multiply the volume for a single app.

Can I scrape reviews for a competitor's app?

Yes. The Actor works on any public app on either store. Add the competitor's package name or Apple ID (or search by name with appQuery) to build a dataset of their user reviews for competitive and feature-gap analysis.

How do I get reviews in a specific country or language?

Use the country dropdown to pick the storefront/region and the language dropdown for Google Play review language. For the App Store, use appleCountries to target one or more specific storefronts (each country has its own reviews).

How is the sentiment field calculated?

sentiment is derived directly from the star rating for a fast, dependency-free signal: positive for 4–5 stars, neutral for 3 stars, and negative for 1–2 stars. For deeper, text-based sentiment or topic modeling, feed the text field into your own NLP/LLM step — the raw review text is included in every row.

Why do App Store review counts vary between runs?

Apple's public review feed is paginated and can return sparse or shifting pages depending on the storefront and time of day. The Actor handles this gracefully (it never stops on an empty page and sweeps multiple storefronts). For the highest, most consistent volume on a single app, Google Play is the more reliable source, and adding appleCountries increases App Store coverage.

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Tips for best results

• Want maximum volume for one app? Use Both stores, add several appleCountries, and raise maxReviews.
• Building a sentiment dashboard? Sort by newest and schedule a daily run to append fresh reviews.
• Doing ASO keyword mining? Export to CSV and run keyword frequency on the text and title columns.
• Large jobs: each run stops after ~4 minutes and saves everything collected; for tens of thousands of reviews, run per-app or increase memory and re-run.

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Related Actors

Looking for more app-market intelligence? Explore the rest of the suite:

• Google Play Store Scraper — app metadata, ratings, installs, and category charts.
• App Store Scraper — App Store app details, pricing, and top-chart rankings.
• Google Play Search Scraper — discover apps by keyword and category.
• App Reviews Scraper (this Actor) — the review corpus itself, across both stores.

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Reviews are scraped from publicly available feeds for research, analytics, and ASO. Please use the data responsibly and in line with the app stores' terms and applicable laws.