Fast Google Play Reviews Scraper API: Extract App Reviews, Ratings & User Feedback at Scale

The Google Play Reviews Scraper is an Apify Actor that extracts user reviews, star ratings, reviewer profiles, developer replies, app version data, and feature-specific criteria ratings from any Google Play Store listing. This google play review scraper api collects 18+ structured fields per review—including thumbs-up counts, review dates, and per-feature quality ratings—across any country and language combination.

$0.10 per 1,000 reviews. Extract app reviews from the Google Play Store at scale with no API key, no rate limits, and no complex authentication. Target specific apps by ID or URL, filter by country and language, and retrieve reviews sorted by newest, relevance, or rating. Built-in date filtering with the until parameter lets you extract only reviews newer than a specific date—ideal for continuous monitoring.

Use this google play store review extractor for app sentiment analysis, user feedback monitoring, competitive benchmarking, or NLP training data. Download Google Play reviews to JSON, CSV, or Excel for product analytics, feature prioritization, and app store optimization (ASO).

Note: Google Play displays two rating mechanisms. Only reviews containing text comments are extracted by this scraper.

Pricing: $0.10 per 1,000 reviews | No API key required

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Table of Contents

1. What Does the Google Play Reviews Scraper Do?
2. Features and Capabilities
3. Pricing
4. Input Parameters
5. Output Format and Data Fields
6. Custom Map Function
7. AI Agent Integration via MCP
8. Related Tools
9. Demo Mode and Free Testing
10. Automated Scheduling and Monitoring
11. Quick Start Guide
12. Use Cases and Industries
13. Troubleshooting
14. Frequently Asked Questions
15. Contact

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What Does the Google Play Reviews Scraper Do?

Google Play review extraction is the automated process of collecting user reviews, ratings, feedback text, and metadata from Android app listings on the Google Play Store. The Play Store hosts over 3 million apps with billions of user reviews—making it the largest source of structured user feedback for Android applications.

The Agents Google Play Reviews Scraper is a high-performance data extraction tool built to scrape Google Play reviews from any app listing at scale. Extract structured review data quickly and reliably—without needing Google's official API, developer console access, or complex authentication flows.

This tool serves as a practical, cost-effective solution for bulk app review collection. At $0.10 per 1,000 reviews, it delivers comprehensive review data including developer replies, app version info, and feature-specific quality ratings that aren't available through most alternatives.

What You Get From Every Review

When you extract Google Play reviews, you receive:

Review Content and Rating

• Full review text and optional title
• Star rating (1–5) with text representation
• Publication date (ISO 8601)
• Thumbs-up count (helpfulness votes)
• Direct review URL

Developer Response

• Developer reply text (when available)
• Developer reply date

App and Version Context

• App ID (e.g., com.whatsapp)
• App version at time of review
• Country and language of the review

Feature-Specific Ratings (Criterias)

• Per-feature quality ratings (e.g., voice messaging, file sharing)
• Structured criteria name and rating pairs

Reviewer Profile

• Reviewer display name
• Reviewer profile image URL

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Features and Capabilities

Input Flexibility

Input Type	Example	Best For
App ID	com.whatsapp	Targeting specific apps by package name
Direct URL	https://play.google.com/store/apps/details?id=com.whatsapp	Scraping from a Google Play listing URL

Core Features

• High-Speed Extraction — Extract thousands of reviews efficiently
• Country and Language Filtering — Target reviews from specific regions and languages
• Date Filtering — Use until parameter to extract only reviews newer than a specific date
• Sort Options — Sort by newest, relevance, or rating
• Developer Replies — Capture developer response text and dates
• Feature Ratings — Extract per-feature quality ratings (criterias)
• App Version Tracking — See which version each reviewer was using
• Multiple Export Formats — JSON, CSV, Excel direct download
• Custom Transformations — Reshape output with custom JavaScript map functions
• API Integration — RESTful API for Python, Node.js, or any HTTP client
• Scheduled Runs — Automate recurring extraction for continuous monitoring
• Multi-Language Support — Set language to all to fetch reviews across every language separately

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Pricing

Simple Per-Review Pricing

No subscriptions, no hidden fees. This google play reviews scraper uses straightforward per-review pricing:

Metric	Price
Per 1,000 reviews	$0.10
Per review	$0.0001

Example: Extracting 50,000 reviews from a popular app costs $5.00. Extracting 1 million reviews costs $100.00.

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Input Parameters

Field	Type	Description	Default
appIds	array	Application IDs from the Google Play URL (extracted from the id query parameter)	[]
country	string	Google Play country code from which to fetch reviews	us
language	string	Language code for reviews. Set to all to fetch reviews for each language separately	en
sort	string	Criteria to sort reviews (e.g., NEWEST)	NEWEST
startUrls	array	Direct Google Play review URLs—scraping begins immediately from these endpoints	[]
maxItems	number	Maximum number of reviews to output	Infinity
until	string	Returns only reviews newer than this date	null
customMapFunction	string	JavaScript function to transform each review object (transformation only, not filtering)	null

Input Examples

Single App — By App ID:

{
    "appIds": ["com.whatsapp"],
    "country": "us",
    "language": "en",
    "sort": "NEWEST",
    "maxItems": 1000
}

Multiple Apps — Competitive Comparison:

{
    "appIds": ["com.whatsapp", "org.telegram.messenger", "com.viber.voip"],
    "country": "us",
    "language": "en",
    "maxItems": 500
}

Date-Filtered — Recent Reviews Only:

{
    "appIds": ["com.spotify.music"],
    "until": "2025-01-01",
    "sort": "NEWEST",
    "maxItems": 5000
}

Multi-Language — Global Sentiment:

{
    "appIds": ["com.instagram.android"],
    "language": "all",
    "country": "us",
    "maxItems": 2000
}

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Output Format and Data Fields

Each extracted review is a structured JSON object containing 18+ fields. Here is a sample:

{
  "id": "acf0e0f8-d90c-46dc-9deb-dbd9541adcdb",
  "userName": "Akintola Samuel",
  "userImage": "https://play-lh.googleusercontent.com/a/ACg8ocK4I3LkwgEHYl0KpnHt75hJQemY3ZNJd4ykknNoyZApALYhOg=mo",
  "date": "2025-02-04T20:41:16.276Z",
  "score": 3,
  "scoreText": "3",
  "url": "https://play.google.com/store/apps/details?id=com.whatsapp&reviewId=acf0e0f8-d90c-46dc-9deb-dbd9541adcdb",
  "title": null,
  "text": "I love this app men it's vibing",
  "replyDate": null,
  "replyText": null,
  "version": "2.24.22.78",
  "thumbsUp": 0,
  "criterias": [
    {
      "criteria": "vaf_phase1_voice_messaging",
      "rating": 1
    },
    {
      "criteria": "vaf_phase1_file_sharing",
      "rating": 1
    }
  ],
  "country": "US",
  "appId": "com.whatsapp",
  "language": "en"
}

Complete Field Reference

Field	Type	Description
id	string	Unique review identifier (UUID)
userName	string	Reviewer's display name
userImage	string	Reviewer's profile image URL
date	string	ISO 8601 review publication date
score	number	Star rating (1–5)
scoreText	string	Rating as text (e.g., "3")
url	string	Direct link to the review on Google Play
title	string	Review title (can be null)
text	string	Full review text
replyDate	string	ISO 8601 date of developer reply (null if no reply)
replyText	string	Developer's response text (null if no reply)
version	string	App version the reviewer was using
thumbsUp	number	Number of helpfulness votes
criterias	array	Per-feature quality ratings (criteria name + rating pairs)
country	string	Country code of the review
appId	string	Application package ID (e.g., com.whatsapp)
language	string	Language code of the review

Data Fields by Use Case

Use Case	Key Fields
Sentiment Analysis	text, score, date, criterias
App Store Optimization (ASO)	score, text, version, country, language
Developer Response Tracking	replyText, replyDate, text, score
Feature Feedback Analysis	criterias, text, score, version
Competitive Benchmarking	appId, score, text, date, thumbsUp
NLP Training Data	text, score (as label), language

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Custom Map Function

Transform each review before it's saved to the dataset. The customMapFunction parameter accepts a JavaScript function that reshapes every review object. Use this to extract specific fields, rename properties, or compute derived values.

Important: The custom map function is for transformation only, not filtering. Every review will still be saved—you're changing its shape, not deciding whether to include it.

Example: Flatten for Sentiment Analysis

(review) => ({
    app: review.appId,
    rating: review.score,
    text: review.text,
    date: review.date,
    version: review.version,
    country: review.country,
    helpful: review.thumbsUp
})

Example: Developer Response Audit

(review) => ({
    app: review.appId,
    reviewText: review.text,
    rating: review.score,
    hasReply: !!review.replyText,
    replyText: review.replyText,
    replyDate: review.replyDate,
    daysBetween: review.replyDate && review.date
        ? Math.round((new Date(review.replyDate) - new Date(review.date)) / 86400000)
        : null
})

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AI Agent Integration via MCP

Apify provides a hosted Model Context Protocol (MCP) server at mcp.apify.com that allows AI agents and LLM-based applications to discover and run Apify Actors as tools—including this Google Play Reviews Scraper.

What This Means

If you're building AI agents using Claude Desktop, VS Code with MCP support, or any framework that implements the MCP specification, you can give your agent the ability to extract Google Play reviews autonomously. The agent can call this scraper as a tool, receive structured JSON results, and use them in downstream analysis.

How to Connect

Add this scraper to your MCP client configuration:

https://mcp.apify.com?tools=agents/googleplay-reviews

Or use the CLI for local development:

$npx @apify/actors-mcp-server --tools agents/googleplay-reviews

Use Cases for AI Agent Integration

• Automated app monitoring — An AI agent periodically extracts new reviews and summarizes sentiment trends, flagging negative spikes for product teams.
• Competitive intelligence workflows — An agent extracts reviews for multiple competing apps, compares feature sentiment, and generates a competitive report.
• Multi-step research pipelines — Combine this scraper with other data sources in a single agent workflow: extract reviews, run sentiment analysis, and generate actionable recommendations.

For full setup instructions, see the Apify MCP documentation.

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Related Tools

Agents Data Intelligence Suite

All tools below are built and maintained by Agents—a team of ex-Big Tech engineers, former ad agency strategists, and data specialists delivering intelligence, precision, and impact at scale.

Tool	What It Extracts	Best For
Google Play Reviews Scraper	App reviews, ratings, developer replies, feature ratings	App intelligence (You are here)
Google Maps Reviews Scraper	Business reviews, ratings, reviewer profiles, location data	Local business intelligence
Google Maps Search Scraper	Business listings, contact, ratings, hours	Lead generation, directories
Trustpilot Reviews Scraper	Reviews, TrustScores, company replies	SaaS/B2B analysis
Yelp Reviews Scraper	Reviews, ratings, reviewer profiles	Restaurant/hospitality
Yelp Business Scraper	Business profiles, ratings, contact	Business data, prospecting
TripAdvisor Reviews Scraper	Hotel/restaurant reviews, ratings	Hospitality intelligence

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Demo Mode and Free Testing

You can test this google play reviews scraper on Apify's Free plan with limited results before committing to larger runs. Validate the output format, data quality, and field coverage before scaling.

How to Test:

• Run the scraper with a small maxItems value (e.g., 10–50 reviews)
• Verify the output structure matches your pipeline requirements
• Confirm country and language filtering works for your target market
• Test the customMapFunction with a sample transformation

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Automated Scheduling and Monitoring

App reviews appear continuously. For product teams and reputation managers, set up automated recurring runs to capture new reviews as they're posted.

Why Schedule Review Extraction?

• Release monitoring — Track user sentiment after each app update by filtering with until
• Continuous feedback loop — Feed fresh reviews into product analytics dashboards
• Competitor tracking — Monitor competitor app reviews weekly for feature gaps
• Rating trend analysis — Detect rating drops before they impact store ranking
• Agency reporting — Automated data for client app performance dashboards

How to Set Up Scheduled Runs

1. Open the Actor in Apify Console
2. Configure your input parameters (appIds, country, language, until)
3. Click Schedule and set frequency (daily, weekly, after each release)
4. Optionally add a webhook to push new data to your pipeline

Webhook Integration

Combine scheduled runs with webhooks to build fully automated review monitoring:

Scheduled Run → New Reviews Extracted → Webhook fires → Your system receives data

Use webhooks to trigger:

• Slack alerts for 1-star reviews mentioning crashes or bugs
• Database updates with new review data
• Dashboard refreshes with latest sentiment metrics
• Jira ticket creation for critical user-reported issues

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Quick Start Guide

For Non-Technical Users (Apify Console)

1. Go to Google Play Reviews Scraper on Apify
2. Click Try for free
3. Enter an App ID (e.g., com.whatsapp) in the appIds field
4. Set maxItems to your desired review count
5. Click Start and wait for results
6. Export Google Play reviews to CSV from the Storage tab

For Developers (Python API)

from apify_client import ApifyClient
client = ApifyClient("YOUR_TOKEN")
run = client.actor("agents/googleplay-reviews").call(run_input={
    "appIds": ["com.whatsapp"],
    "country": "us",
    "language": "en",
    "sort": "NEWEST",
    "maxItems": 1000
})
items = client.dataset(run["defaultDatasetId"]).list_items().items

For Product Teams (Release Monitoring)

{
    "appIds": ["com.yourapp.android"],
    "until": "2025-03-01",
    "sort": "NEWEST",
    "country": "us",
    "maxItems": 5000
}

Schedule after each release. Use the until parameter set to the release date to capture only post-update feedback. Compare sentiment before and after to measure release impact.

For Competitive Analysis

{
    "appIds": ["com.whatsapp", "org.telegram.messenger", "com.viber.voip"],
    "country": "us",
    "language": "en",
    "sort": "NEWEST",
    "maxItems": 500
}

Extract recent reviews from competing apps in a single run. Use the customMapFunction to flatten output for side-by-side comparison in spreadsheets.

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Use Cases and Industries

App Sentiment Analysis and NLP

Extract thousands of Google Play reviews with full text, star ratings, and feature-specific criteria for training sentiment classifiers, topic modeling, or aspect-based sentiment analysis. Each review includes structured metadata (date, rating, app version, country) that enriches NLP pipelines. The criterias field provides granular per-feature quality signals unavailable from most review sources.

Key fields: text, score, date, criterias, version, language

App Store Optimization (ASO)

Analyze review content to identify keywords users associate with your app. Track how ratings change across versions, countries, and languages. Discover what features drive positive reviews and what pain points cause negative ones. Use this data to inform app store listing copy, feature prioritization, and update strategies.

Key fields: score, text, version, country, language, thumbsUp

Developer Response Analytics

Monitor how effectively your team (or competitors) responds to user reviews. Track response rates, response times, and whether replies address user concerns. The replyText and replyDate fields enable automated auditing of developer engagement.

Key fields: replyText, replyDate, text, score, date

Product Management and Feature Prioritization

Feed review data into product analytics to identify the most-requested features and the most-reported bugs. The criterias field reveals per-feature quality ratings, letting you pinpoint exactly which aspects of your app users rate poorly. Cross-reference with version to track whether fixes in new releases actually improved user satisfaction.

Key fields: criterias, text, score, version, date

Competitive Benchmarking

Extract reviews from competing apps in the same category to compare user sentiment, feature gaps, and pain points. Identify where competitors are weak and where they excel. Run multi-app extractions in a single scraper run by providing multiple App IDs.

Key fields: appId, score, text, date, thumbsUp, criterias

Academic and Market Research

Build large-scale review datasets for studying user behavior, app ecosystem dynamics, or digital marketplace trends. Multi-language and multi-country support enables cross-cultural research. Structured output with country, language, and date fields supports longitudinal studies.

Key fields: text, score, country, language, date, appId

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Troubleshooting

Common Issues and Solutions

Issue	Cause	Solution
Fewer reviews than expected	App has fewer text reviews than total ratings	Google Play separates star-only ratings from text reviews—only text reviews are extracted
Unexpected result quantity	maxItems set higher than available reviews	Adjust maxItems or check that the app has enough text reviews in the target country/language
Missing data in output	Results stored in Apify dataset	Check the "Storage" section in your task results for the complete dataset
No developer replies	Developer hasn't responded to reviews	replyText and replyDate will be null when no reply exists—this is expected
Empty criterias array	Not all reviews include feature ratings	The criterias field depends on Google Play's per-feature rating prompts, which vary by app

Performance Tips

• Start small: Test with maxItems: 50 to validate your setup before scaling
• Use date filtering: Set the until parameter to avoid re-extracting old reviews on scheduled runs
• Be specific with country: Each country has different review volumes—target your key markets
• Multi-language with care: Setting language: "all" sends separate requests per language, which increases extraction time
• Monitor billing: You are billed per review extracted, not per maxItems setting—if fewer reviews exist, you pay only for what's delivered

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Frequently Asked Questions

What Google Play review data can I extract?

Extract full review text, star ratings (1–5), review dates, reviewer names, reviewer profile images, developer reply text and dates, app version at review time, thumbs-up counts, per-feature quality ratings (criterias), country codes, language codes, and direct review URLs—all in structured JSON or CSV format.

Can I export Google Play reviews to CSV?

Yes. Download Google Play reviews directly from Apify Console in JSON, CSV, or Excel format. This is ideal for spreadsheet analysis, database import, and product analytics dashboards.

Can I scrape reviews from multiple apps at once?

Yes. Provide multiple App IDs in the appIds array (e.g., ["com.whatsapp", "org.telegram.messenger"]). Each app's reviews are extracted sequentially within a single Actor run, with the appId field identifying which app each review belongs to.

Can I filter reviews by date?

Yes. Use the until parameter to extract only reviews newer than a specific date. This is ideal for continuous monitoring—on each scheduled run, set until to the date of your last extraction to avoid duplicates.

Can I scrape reviews by country and language?

Yes. Set the country parameter to any Google Play country code (e.g., us, gb, de, jp) and the language parameter to any language code (e.g., en, es, fr). Setting language to all sends separate requests for each language, collecting reviews across all available languages.

What are the "criterias" in the output?

The criterias array contains per-feature quality ratings that Google Play collects from reviewers. For example, a messaging app might have criteria like vaf_phase1_voice_messaging and vaf_phase1_file_sharing, each with a numeric rating. These provide granular feature-level feedback beyond the overall star rating. Not all reviews include criteria ratings.

Does this extract developer replies?

Yes. When a developer has replied to a review, the replyText and replyDate fields contain the response text and timestamp. This enables automated tracking of developer engagement and response quality.

Can I use Python to scrape Google Play reviews?

Yes. Full Python support via the Apify Client library. See the Quick Start Guide above for Python integration with client.actor("agents/googleplay-reviews").

Can AI agents use this scraper?

Yes. Through Apify's Model Context Protocol (MCP) server, AI agents built with Claude Desktop, VS Code, or any MCP-compatible framework can call this scraper as a tool. This enables automated app monitoring, competitive analysis, and multi-step research pipelines. See the AI Agent Integration via MCP section for setup details.

Why are some reviews missing text?

Google Play allows users to leave star ratings without writing a review. This scraper only extracts reviews that contain text comments, since ratings-only entries provide no actionable feedback content.

How many reviews can I extract per app?

There is no hard limit from the scraper side. Use the maxItems parameter to control how many reviews to extract. The actual number depends on how many text reviews exist for the app in the target country and language.

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Contact

Built by Agents — Where others search, we uncover. Our team of ex-Big Tech engineers, growth hackers, and data specialists builds high-performance scraping tools engineered for speed, precision, and reliability.

For questions or further assistance:

• Email: Reach out at whoaretheagents@gmail.com
• Discord: Join our community to connect with our support team

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Ready to start extracting Google Play review data? At $0.10 per 1,000 reviews with no API key required, this Google Play Reviews Scraper API by Agents is the definitive tool for app sentiment analysis, ASO research, competitive benchmarking, and product feedback intelligence. Start scraping today.