App Store & Google Play Reviews Scraper + Insights Report

The only Google Play review scraper and Apple App Store review scraper that also delivers a built-in insights report — no extra cost, no LLM, no API key required. Runs on the free Apify plan.

Competitors return raw review rows. This actor gives you raw reviews plus analytics: rating trends by app version, top complaint/praise keywords, feature-request signals, suspicious spike detection, and cross-app comparison.

App review insights report: complaint analysis, version trends, and cross-app comparison

The built-in insights report turns raw reviews into answers: a complaint and praise keyword analysis, rating trends by app version, feature-request signals, suspicious-spike detection, and a side-by-side cross-app comparison when you scrape more than one app.

What it does

1. Scrapes reviews from Google Play and/or the Apple App Store (pure HTTP — no browser, free-plan compatible).
2. Normalises both sources into a unified schema (same fields for both stores).
3. Computes insights (pure Python analytics):
   • Rating distribution (1–5 stars)
   • Rating trend by month
   • Rating by app version — the killer developer insight: which release tanked or improved the score
   • Top complaint keywords from 1–2★ reviews
   • Top praise keywords from 4–5★ reviews
   • Feature-request signal detection ("please add", "wish", "would be great", "fehlt", etc.)
   • Suspicious spike months (possible fake/incentivised burst of reviews)
   • Cross-app comparison table (when scraping multiple apps)
4. Writes the insights as JSON (INSIGHTS KVS key) and as a clean HTML report (REPORT KVS key).

Use cases

• ASO (App Store Optimisation): understand what users love and hate to improve your store listing.
• Competitive analysis: compare your app's sentiment against competitors across both stores.
• Release quality monitoring: see exactly which version caused a rating drop.
• Feature roadmap: surface the most-requested features from user reviews.
• Review moderation / support: identify complaint clusters to address in the next release.

Input

Field	Type	Default	Description
googlePlayAppIds	string[]	["com.whatsapp"]	Package names or Play Store URLs
appleAppIds	string[]	[]	Numeric Apple IDs or App Store URLs
country	string	"us"	Store country code (ISO 3166-1 alpha-2)
language	string	"en"	Language code (ISO 639-1)
maxReviewsPerApp	integer	200	Max reviews per app (Apple caps at ~500 via RSS)
generateInsights	boolean	true	Generate the insights report
maxRunTimeSecs	integer	3000	Internal run deadline

At least one of googlePlayAppIds or appleAppIds must be non-empty.

Example input (JSON)

{
  "googlePlayAppIds": ["com.whatsapp", "com.spotify.music"],
  "appleAppIds": ["310633997"],
  "country": "us",
  "language": "en",
  "maxReviewsPerApp": 200,
  "generateInsights": true
}

Output

Dataset — unified review records

Each record has the same fields regardless of the source store:

{
  "source": "googlePlay",
  "appId": "com.whatsapp",
  "appName": "WhatsApp Messenger",
  "reviewId": "gp:AbcDef123...",
  "userName": "JohnDoe",
  "rating": 5,
  "title": null,
  "text": "Works perfectly, love the encryption.",
  "appVersion": "2.24.10.73",
  "thumbsUp": 12,
  "date": "2024-05-03T14:22:00+00:00",
  "replyContent": null,
  "replyDate": null,
  "country": "us",
  "language": "en"
}

Note: title is null for Google Play (no review titles). thumbsUp is null for Apple App Store. replyContent/replyDate are null for Apple (not available in the public RSS feed).

KVS: INSIGHTS (JSON)

{
  "apps": {
    "googlePlay:com.whatsapp": {
      "appName": "WhatsApp Messenger",
      "averageRating": 4.21,
      "storeAverageRating": 4.4,
      "storeRatingCount": 185000000,
      "ratingDistribution": { "5": {"count": 31, "pct": 62.0}, ... },
      "ratingByVersion": {
        "2.24.10.73": {"reviewCount": 18, "avgRating": 4.50},
        "2.24.9.81":  {"reviewCount": 12, "avgRating": 3.25}
      },
      "topComplaintTerms": [{"term": "crashes", "count": 8}, ...],
      "topPraiseTerms": [{"term": "easy use", "count": 14}, ...],
      "featureRequestSignals": {"count": 6, "snippets": ["please add voice messages..."]},
      "suspiciousSpikeMonths": [],
      ...
    }
  },
  "comparison": [
    {"appName": "WhatsApp Messenger", "store": "googlePlay", "averageRating": 4.21, ...}
  ]
}

KVS: REPORT (HTML)

A standalone HTML page with colour-coded rating cards, star distribution bars, version rating table, keyword pills, feature request snippets, trend table, and comparison table. Open directly in a browser or embed in a dashboard.

Google Play field mapping

google-play-scraper field	Actor field
title (app metadata)	appName
score (app metadata)	storeAverageRating
ratings	storeRatingCount
version	currentVersion (metadata)
reviewId	reviewId
userName	userName
content	text
score (review)	rating
thumbsUpCount	thumbsUp
reviewCreatedVersion	appVersion
at (datetime)	date (ISO 8601)
replyContent	replyContent
repliedAt	replyDate (ISO 8601)

Apple App Store field mapping

iTunes endpoint / field	Actor field
Lookup trackName	appName
Lookup averageUserRating	storeAverageRating
Lookup userRatingCount	storeRatingCount
Lookup version	currentVersion (metadata)
RSS id.label	reviewId
RSS author.name.label	userName
RSS title.label	title
RSS content.label	text
RSS im:rating.label	rating
RSS im:version.label	appVersion
RSS updated.label	date
n/a	thumbsUp = null
n/a	replyContent = null

Pricing

Pay per review scraped ($0.0003/review = $0.30 per 1,000), no per-run start fee. The insights report is always included free. Cheaper than most App Store review scrapers — and the only one that also returns a built-in analysis report. A run with 200 Google Play reviews + 200 Apple reviews = $0.12 total.

Limitations

• Apple App Store RSS caps at ~500 reviews per app (10 pages × 50).
• Apple RSS does not provide developer replies or thumbs-up counts.
• Reviews are fetched in "most recent" order; historical bulk export is not supported by the public endpoints.
• Language/country filter on Apple applies to the store region; Apple RSS returns mixed languages.

Technical notes

• Pure HTTP — no browser, no Playwright. Runs on Apify free plan (512 MB memory is sufficient).
• google-play-scraper PyPI package handles Google Play pagination and anti-bot headers.
• Apple App Store uses the public iTunes RSS feed + lookup API (no authentication).
• Insights computed in pure Python (no LLM, no paid API).