App Store & Google Play Review Analyzer

Scrape app reviews and instantly see what users love and hate.

Give it App Store apps (by name, ID, or URL) and Google Play apps (by package ID), and get per-app review analysis: rating distribution, sentiment breakdown, top complaints, top praises, keyword themes, and whether the rating is improving or declining — plus every individual review.

Responsible use: Uses only public endpoints — Apple's iTunes reviews RSS/lookup and Google Play's public app pages (JSON-LD). No login, no anti-bot bypass, no private data.

Who it's for

App developers, product managers, ASO/marketing teams, and competitor researchers.

Input

Field	Type	Description
appStoreApps	array	App names, IDs, or apps.apple.com URLs (e.g. "Spotify", "324684580").
googlePlayApps	array	Play package IDs or URLs (e.g. "com.spotify.music").
countries	array	Store country codes, default ["us"].
maxReviewsPerApp	integer	App Store reviews per country (≤500). Default 200.
includeAnalysis	boolean	Compute sentiment/themes. Default true.

Example

{ "appStoreApps": ["Notion","Spotify"], "googlePlayApps": ["com.spotify.music"], "countries": ["us","gb"], "maxReviewsPerApp": 300 }

Output

Per-app analysis (default dataset)

{
  "appName": "Spotify: Music and Podcasts", "store": "app-store", "country": "us",
  "avgRating": 4.0, "storeAvgRating": 4.7, "storeRatingCount": 32000000,
  "reviewsAnalyzed": 300,
  "ratingDistribution": { "1": 40, "2": 15, "3": 20, "4": 35, "5": 190 },
  "sentimentBreakdown": { "positive": 153, "negative": 48, "neutral": 99 },
  "positivePct": 51, "negativePct": 16,
  "topComplaints": ["ads","premium","money","song","plays"],
  "topPraises": ["love","best","amazing","awesome"],
  "keywordThemes": [{ "word": "ads", "count": 61 }],
  "ratingTrend": "declining",
  "collectedAt": "2026-08-30T18:00:00Z"
}

Individual reviews (named dataset reviews)

{ "store":"app-store","country":"us","appName":"Spotify","rating":2,"title":"Ads out of control","text":"...","author":"...","version":"8.9","updated":"2026-08-28T...","sentiment":"negative" }

Run summary in key-value store OUTPUT.

How the analysis works (transparent)

• Sentiment: lexicon-based positive/negative scoring per review (no black-box model).
• Top complaints / praises: distinctive terms — words that appear disproportionately in negative vs positive reviews (not just frequent words), so you get real differentiators.
• Rating trend: average rating of the most-recent half vs the older half → improving / stable / declining.

Notes / limitations

• App Store: full review text + analysis (Apple RSS returns up to ~500 most-recent reviews per country).
• Google Play (v1): app-level rating, rating count, developer, category and description from the public app page. Per-review text on Google Play requires a fragile internal endpoint and is out of scope for v1 — the analysis fields are App Store based.
• Sentiment/themes are heuristic signals for triage, not a trained model.