Google Play Reviews Scraper - Ratings, Replies & History

Disclaimer: This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Google LLC or any of its subsidiaries. All trademarks mentioned are the property of their respective owners. "Google Play" is referenced only to describe the publicly available website this Actor collects data from.

Pull Google Play app reviews at depth and export them to JSON, CSV or Excel: star rating, full review text, reviewer, date, helpful votes, the app version reviewed, and the developer's public reply. Add the app's 1-5 star histogram in the same run, and read a different review set per country without starting a second job.

Built for app teams, ASO and product analysts, competitor research, support-quality benchmarking and LLM/sentiment pipelines that need clean review text with dates attached.

What you get

Full review history	Pages through Google's review feed until your limit or the source runs out - not just the first page
Developer replies	Reply text, reply date, and a computed reply-latency in hours for every answered review
Ratings histogram	One appRatings row per app and country: overall score, total ratings, written reviews, and the 1-5 star split in counts and percentages
Per-country review sets	Google serves different reviews per store country. Ask for us, gb, de… in one run; every row carries its country
Filters that cost nothing	Star rating, date window, app version, keyword, has-a-reply. Filtered rows are never charged
Find apps by name	No package name? Give a search term and the Actor resolves the top matches for you
Bulk import	Paste hundreds of package names, or link a .txt / .csv / Google Sheet / Drive file
Monitor mode	Remembers what it has seen, so a scheduled run returns only new reviews
No browser, no login	Plain HTTP through Apify's datacenter proxy. Fast, cheap, and nothing to configure

Use cases

• Competitor teardown - pull 1★-2★ reviews for a rival app and read what its users actually complain about; the histogram tells you how representative that tail is.
• Release regression watch - filter by appVersion (or a date window around a release) and compare average score before and after.
• Support benchmarking - onlyWithDeveloperReply plus developerReplyLatencyHours measures how fast a competitor answers, and in what tone.
• Localisation gaps - the same app across us, de, br, in often has very different complaints.
• LLM input - clean, dated review text with a star rating attached, ready for sentiment or theme clustering.
• Continuous monitoring - schedule it with Monitor mode on and receive only what is new.

How to use

1. Sign up for Apify - the free plan is enough to try this Actor.
2. Open the Google Play Reviews Scraper and give it one or more package names (com.spotify.music) - or a search term if you do not know the package name.
3. Pick your countries, set Max reviews per app and any filters, then click Start.
4. Export as JSON, CSV, Excel, XML or RSS - or pull results programmatically through the Apify API.

Input

Minimum - one package name:

{ "appIds": ["com.spotify.music"] }

A realistic competitor pull - the last month of critical reviews in three markets:

{
  "appIds": ["com.duolingo", "com.babbel.mobile.android.en"],
  "countries": ["us", "gb", "de"],
  "ratings": ["1", "2"],
  "publishedAfter": "2026-08-01",
  "maxReviewsPerApp": 500,
  "includeRatingsSummary": true
}

Everything a developer answered, for a support-tone study:

{ "appIds": ["com.ubercab"], "onlyWithDeveloperReply": true, "maxReviewsPerApp": 200 }

Don't know the package name:

{ "searchTerms": ["habit tracker"], "maxAppsPerSearchTerm": 3, "maxReviewsPerApp": 100 }

Bulk - paste a block, or link a file, into Import app IDs from a file:

com.duolingo
com.spotify.music
https://play.google.com/store/apps/details?id=com.whatsapp

Output

A review row:

{
  "type": "review",
  "appId": "com.spotify.music",
  "appName": "Spotify: Music and Podcasts",
  "country": "us",
  "reviewId": "72005d29-e252-409a-8089-03b19afd3145",
  "userName": "Karthick Priyan",
  "score": 5,
  "text": "Great for podcasts, but the shuffle keeps resetting.",
  "textLength": 52,
  "thumbsUp": 0,
  "appVersion": "9.1.80.2221",
  "publishedAt": "2026-09-06T06:19:20.951Z",
  "hasDeveloperReply": false,
  "developerReplyText": null,
  "developerReplyAt": null,
  "developerReplyLatencyHours": null,
  "criteria": [{ "criteria": "vaf_app_quality_usability", "rating": 1 }],
  "reviewUrl": "https://play.google.com/store/apps/details?id=com.spotify.music&reviewId=72005d29-…"
}

An appRatings row (one per app and country, switch off with includeRatingsSummary):

{
  "type": "appRatings",
  "appId": "com.spotify.music",
  "appName": "Spotify: Music and Podcasts",
  "country": "us",
  "score": 4.345,
  "ratingsCount": 36253828,
  "reviewsCount": 1851210,
  "histogram": { "1": 3704549, "2": 1067487, "3": 1319242, "4": 3088388, "5": 27074140 },
  "histogramPercent": { "1": 10.2, "2": 2.9, "3": 3.6, "4": 8.5, "5": 74.7 },
  "installs": "1,000,000,000+",
  "developer": "Spotify AB",
  "genre": "Music & Audio",
  "currentVersion": "VARY",
  "sampleSize": 100,
  "sampleAverageScore": 3.75,
  "sampleReplyRate": 0
}

Three dataset views ship with the Actor: Reviews, Developer replies and Ratings & histogram.

Good to know

• On every row: app ID and name, country, language, review ID and URL, reviewer name and avatar, star rating, review text, helpful votes, review date, and hasDeveloperReply.
• appVersion is attached to most reviews, not all. Google records the reviewed version only when it knows it, so a null means Google published none.
• Developer replies depend entirely on the developer. Some answer nearly every review; many never answer publicly at all. hasDeveloperReply is populated on every row, and Only reviews with a developer reply keeps just the answered subset.
• criteria exists only for apps that use rating criteria (usability, ads, battery…), and only when the reviewer actually filled it in.
• Google Play has no review titles. Other stores do; Play does not, so no empty title column is shipped.
• Reviews are served per store country. A review written in Germany is not in the us feed - list several countries if you need a global picture.
• A narrow filter reads a lot to find a little. Max reviews scanned per app (default 5,000) bounds that search, and the run tells you when it stops there.
• A run never fails on a transient block. It ends Succeeded with whatever it collected plus a status message explaining what happened.

How much does it cost to scrape Google Play?

This Actor uses Apify's pay-per-event pricing: you are charged only for the results it delivers, with no monthly rental and no start fee. The events it can charge are:

• Review scraped - Charged once per review written to your dataset - star rating, full text, reviewer, date, helpful votes, app version and the developer's public reply. Reviews removed by your filters, reviews already seen in monitor mode, and apps that are not on Google Play are never charged.
• App ratings summary - Charged once per app and country when the ratings summary is switched on - overall score, total ratings and written reviews, the 1-5 star histogram in counts and percentages, installs, category, price and current version. Turn off 'Include the app ratings summary' to skip it entirely.

The current price of each event is shown on the Pricing tab of this page. Set a maximum total charge on the run if you want a hard cap on spend, and use the input limits to control how much the Actor fetches.

Related Actor

If you need app metadata, top charts, developer portfolios or developer contact details rather than reviews, use the sibling Google Play Store Scraper - this Actor is deliberately focused on reviews and ratings.

Automate & schedule

Run this Actor on autopilot and pull results into your own stack:

• Apify API - start runs, fetch datasets and manage schedules over REST.
• apify-client for JavaScript and apify-client for Python - official SDKs.
• Schedules - run it hourly, daily or weekly and keep your dataset current.
• Webhooks - trigger downstream actions (CRM import, Slack alert, email sequence) the moment a run finishes.

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'MY_APIFY_TOKEN' });

const run = await client.actor('scrapesage/google-play-reviews-scraper').call({
    "appIds": [
        "com.spotify.music"
    ],
    "maxReviewsPerApp": 100,
    "countries": [
        "us"
    ],
    "language": "en",
    "sort": "NEWEST",
    "includeRatingsSummary": true
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Got ${items.length} records`);

Integrate with any app

Connect the dataset to thousands of apps - no code required:

• Make - multi-step automation scenarios.
• Zapier - push new records straight into your CRM or spreadsheet.
• Slack - get notified when a scheduled run finds something new.
• Google Drive / Sheets - auto-export every run to a spreadsheet.
• Airbyte - pipe results into your data warehouse.
• GitHub - trigger runs from commits or releases.

Use with AI assistants (MCP)

The output is clean, LLM-ready JSON. You can call this Actor from Claude, ChatGPT or any agent framework through the Apify MCP server - describe the data you need and let the assistant run this Actor for you.

Agent-ready: autonomous payments (x402 & Skyfire)

This actor is agent-ready — AI agents can discover it, run it, and pay for it autonomously, with no Apify account and no human in the loop. It uses pay-per-event pricing and limited permissions, so it qualifies for Apify's agentic-payment standards:

• x402 — an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the Apify MCP server — no account, no API key.
• Skyfire — agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes.

Tips

• Country coverage is the whole game. Google serves a different review set per store country, so listing us, gb, de, fr, es in one run gets you five times the reviews of a single-country job.
• Benchmark support quality by keeping developerReplyLatencyHours and comparing median reply time against your competitors.
• Complaint mining. Combine the 1-2 star filter with a keyword to isolate a single recurring issue, then feed the text to a topic model.
• Version regression checks. Filter on appVersion to see whether a release moved the rating.
• Daily monitoring. Monitor mode plus a Schedule charges you only for reviews that are genuinely new.

FAQ

How is this Actor billed? Pay-per-event: you pay only for the results it delivers, with no monthly rental and no start fee. The per-event price is shown on the Pricing tab.

Can I schedule it and get results automatically? Yes - create a Schedule and add a webhook or an integration (Google Sheets, Slack, Make, Zapier) to push each run's dataset wherever you need it.

Which export formats are available? Every run's dataset can be downloaded as JSON, CSV, Excel (XLSX), XML, HTML or RSS from the Apify Console or the API.

Can I run it from code or an AI agent? Yes - through the Apify API and client libraries, or from Claude, ChatGPT and other assistants via the Apify MCP server.

Is it legal to scrape Google Play? This Actor collects publicly available data only. You are responsible for using the output in compliance with applicable laws (including data-protection law where personal data is involved) and the source's terms. See Data & lawful use and the Disclaimer below.

Is this an official Google Play tool? No. It is an independent, third-party Actor with no affiliation to, endorsement by or sponsorship from Google LLC. See the Disclaimer below.

Data & lawful use

This Actor reads only what Google Play publishes to logged-out visitors: it does not log in, create accounts, or reach anything behind a sign-in. It keeps the ordinary anonymous cookies Google Play itself sets, because the public review feed needs them to page consistently; no account, login or session token is ever used. Names, handles, bios and engagement figures are public, but they relate to identifiable people, so treat the output as personal data. If you are in the EU or UK you are the data controller for what you do with it: have a lawful basis (usually legitimate interest for research, marketing analytics or B2B prospecting), honour access and deletion requests, and do not use the output for spam or unsolicited messaging.

Under Apify's Standard Actor Contract, which governs your use of this Actor, you are the controller of any personal data in your input and output and scrapesage acts only as your processor: that data is processed solely to run your job, written only to your own Apify storage, never used for any other purpose and never shared onward. If you need help with a data-subject request that involves this Actor's output, open an issue on the Issues tab.

Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Google LLC or any of its subsidiaries. All trademarks mentioned are the property of their respective owners.

"Google Play" and any related marks are the property of their respective owners and are used here only in a descriptive, nominative sense - to identify the publicly accessible website from which this Actor collects data. This Actor is not an official Google Play product, is not authorised or certified by Google LLC, and does not distribute Google Play software. It collects only publicly available information; you are responsible for ensuring your use of that data complies with applicable laws, regulations and the terms of the source website.

Need help?

Open an issue on the Actor's Issues tab, or visit the Apify help center. Feature requests are welcome - this Actor is actively maintained.