Google Play Reviews & App Data Scraper

Scrape Google Play Store reviews and app details for any number of apps, countries and languages in a single run. Built for review monitoring: incremental mode returns only reviews newer than a date and stops paging immediately, so a daily run costs almost nothing.

What you get

• ⭐ Reviews: star rating, review text, likes, app version, date, and the developer's reply with its date.
• 📱 App details: title, developer, average rating, rating count, rating histogram (1–5★), installs (exact and range), price, genre, version, last update date, ads and in-app purchases.
• 🌍 Many markets at once: combine any countries (us, gb, dk, de…) with any languages (en, da, de…).
• 🔎 Search mode: give keywords like "budget app" and the Actor finds the top apps for you.
• 🎯 Exact star filters: ask for 1–2★ reviews only. Google filters server-side, so you get exactly N matching reviews instead of N reviews of which a few match.
• 🔁 Incremental monitoring: reviewsNewerThan: "1 day" plus a daily schedule gives you a feed of only new reviews.
• 🛡️ GDPR-friendly by default: reviewer names are off unless you enable them, and profile images are never collected.

Use cases

• Track negative reviews after each release and alert your team (pairs with Slack/Zapier/Make integrations).
• Competitor analysis: compare rating histograms, update frequency and complaints across apps and countries.
• Feed reviews to an LLM for sentiment and topic analysis. Works great from AI agents via the Apify MCP server.
• App-store optimisation (ASO) research across markets.

Input example

{
  "apps": ["com.spotify.music", "https://play.google.com/store/apps/details?id=com.netflix.mediaclient"],
  "searchTerms": ["habit tracker"],
  "countries": ["us", "gb"],
  "languages": ["en"],
  "maxReviewsPerApp": 500,
  "sort": "newest",
  "maxStars": 2,
  "reviewsNewerThan": "7 days"
}

Output example

{
  "type": "review",
  "appId": "com.spotify.music",
  "country": "us",
  "language": "en",
  "reviewId": "646bd8b5-…",
  "userName": null,
  "score": 2,
  "content": "Casting to my speakers keeps disconnecting since the last update.",
  "thumbsUpCount": 14,
  "appVersion": "9.1.92.3058",
  "at": "2026-10-19T23:14:33",
  "replyContent": "Sorry to hear that! Please try…",
  "repliedAt": "2026-10-20T08:02:11"
}

App rows have "type": "app". Filter on type in the dataset view or export.

Pricing

Pay only for what you get:

Event	Price
Actor start	$0.00005
Review	$0.0001 ($0.10 per 1,000)
App details row	$0.002

A daily monitoring run for 5 apps that finds about 50 new reviews costs about $0.015.

Notes

• Some apps aren't available in every country. They're skipped with a warning and the run continues. If an app fails for another reason (for example a temporary Google error), it's skipped, nothing is charged for it, and it's listed under errors in the run's SUMMARY record.
• Search terms are looked up in the first country and language you list; the apps found are then scraped in all of them.
• reviewsNewerThan needs sort = newest (the Actor switches to it automatically). Dates without a time zone are read as UTC.
• Each review is returned and charged once per app/country/language, even if Google repeats it across pages.
• Google Play exposes a limited history per sort order. For very large backfills, combine several star filters and sort orders.
• This Actor only reads publicly available data. You're responsible for using it in line with applicable laws, including GDPR.

How to use Google Play Reviews & App Data Scraper

1. Add app IDs (like com.spotify.music) or Play Store URLs, or use search terms to find apps.
2. Pick countries and languages, and how many reviews per app.
3. For daily monitoring, sort by newest and set reviewsNewerThan (for example 7 days).
4. Click Start, then export reviews and app details as JSON, CSV or Excel.

Use it from code (API)

Run it from Python with the official client (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("fjordlabs/google-play-reviews").call(run_input={'apps': ['com.spotify.music'], 'countries': ['us'], 'languages': ['en'], 'maxReviewsPerApp': 200})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

Or with one HTTP call that returns the results directly:

curl -X POST "https://api.apify.com/v2/acts/fjordlabs~google-play-reviews/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" -d '{"apps": ["com.spotify.music"], "countries": ["us"], "languages": ["en"], "maxReviewsPerApp": 200}'

It also works with Make, Zapier, n8n, Google Sheets and webhooks through Apify's integrations.

Use with AI agents (MCP)

Agents can call this Actor as a tool through Apify's MCP server (mcp.apify.com). Add fjordlabs/google-play-reviews to the server's Actors. Results are clean JSON with a small default size, so they fit well in an agent's context.

FAQ

How many reviews can I get? Thousands per app. Google pages through reviews, and you set the limit with maxReviewsPerApp.

Is personal data collected? Reviewer names are off by default and profile images are never collected, to keep you GDPR-friendly.

Can I only get new reviews? Yes. With sort = newest and reviewsNewerThan, the run stops as soon as it reaches older reviews, so daily monitoring stays cheap.

Can I get app details without reviews? Set maxReviewsPerApp to 0 to get only the app details rows.

Am I charged for errors? No. Rows that fail are never charged; you only pay for results.

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