# Google Play Reviews Intelligence & Insights Scraper (`ahmed_jasarevic/google-play-reviews-scraper`) Actor Extract structured Google Play app reviews and turn them into actionable market intelligence. Analyze user feedback, ratings, and trends across multiple apps using powerful filters like keywords, rating, and time range. Perfect for competitor research, ASO optimization, and sentiment analysis. - **URL**: https://apify.com/ahmed\_jasarevic/google-play-reviews-scraper.md - **Developed by:** [Ahmed Jasarevic](https://apify.com/ahmed_jasarevic) (community) - **Categories:** Developer tools, Other, Integrations - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.08 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## ๐Ÿ“ฑ Google Play Reviews Scraper & App Intelligence Tool A powerful Apify Actor for scraping **Google Play Store apps and user reviews at scale**. Extract structured **app data, reviews, ratings, and metadata** for: * ๐Ÿ“Š sentiment analysis * ๐Ÿค– AI / LLM training datasets * ๐Ÿง  market & competitor research * ๐Ÿž user feedback mining --- ### ๐Ÿš€ Features * ๐Ÿ” Search apps by keyword (e.g. `vpn`, `chatgpt`, `finance`) * โญ Extract user reviews with full metadata * ๐ŸŽฏ Filter by rating (1โ€“5 stars) * ๐ŸŒ Language & country targeting * ๐Ÿ” Deduplicate reviews (optional) * ๐Ÿ“… Filter by recency (last N days) * ๐Ÿง  AI-ready structured output * โšก Scalable multi-app scraping --- ### ๐Ÿ“ฆ Input Parameters | Field | Type | Description | | --------------- | ------- | ------------------------------------------ | | `term` | string | Search keyword for Google Play apps | | `maxItems` | integer | Maximum number of reviews to collect | | `appsLimit` | integer | Number of apps to scan from search results | | `reviewsPerApp` | integer | Max reviews per app | | `sort` | string | Sorting: `newest`, `rating`, `helpfulness` | | `country` | string | Country code (e.g. `us`, `gb`, `de`) | | `language` | string | Language code (e.g. `en`, `hr`) | | `uniqueOnly` | boolean | Remove duplicate reviews | | `ratingFilter` | integer | Exact rating filter (1โ€“5, `0 = all`) | | `keywords` | array | Only include reviews containing keywords | | `recentDays` | integer | Only reviews from last N days (`0 = off`) | --- ### ๐Ÿงช Example Inputs #### ๐Ÿ”น Basic scraping ```json { "term": "vpn", "maxItems": 50, "appsLimit": 5, "reviewsPerApp": 100, "sort": "newest", "country": "us", "language": "en", "uniqueOnly": true, "ratingFilter": 0, "keywords": [], "recentDays": 0 } ```` *** #### ๐Ÿ”น 1-star complaint mining (bug & negative feedback) ```json { "term": "vpn", "maxItems": 100, "appsLimit": 10, "reviewsPerApp": 200, "sort": "newest", "country": "us", "language": "en", "uniqueOnly": true, "ratingFilter": 1, "keywords": [], "recentDays": 0 } ``` *** #### ๐Ÿ”น Keyword-based sentiment dataset ```json { "term": "chatgpt", "maxItems": 200, "appsLimit": 10, "reviewsPerApp": 200, "sort": "helpfulness", "country": "us", "language": "en", "uniqueOnly": true, "ratingFilter": 0, "keywords": ["bug", "crash", "slow", "amazing"], "recentDays": 30 } ``` *** ### ๐Ÿ“ค Output Format Each dataset item returns **structured app + review intelligence data**: ```json { "type": "review", "appTitle": "VPN - Super Unlimited Proxy", "appId": "com.free.vpn.super.hotspot.open", "appUrl": "https://play.google.com/store/apps/details?id=com.free.vpn.super.hotspot.open", "developer": "VPN Super Inc", "summary": "Fast secure VPN service", "appScore": 4.7, "installs": "100,000,000+", "reviewId": "abc123", "user": "John Doe", "rating": 1, "text": "App keeps crashing", "date": "2026-05-01T00:00:00Z", "thumbsUp": 3, "version": "2.1.0", "language": "en", "country": "us", "source": "google-play-scraper" } ``` *** ### ๐ŸŽฏ Use Cases - ๐Ÿ“Š Sentiment analysis datasets - ๐Ÿค– AI training (LLM fine-tuning) - ๐Ÿง  App market intelligence - ๐Ÿ† Competitor analysis - ๐Ÿž Bug & complaint mining - ๐Ÿ“ˆ Product research *** ### โš™๏ธ How it works 1. Search Google Play apps by keyword (`term`) 2. Select top apps (`appsLimit`) 3. Extract reviews per app (`reviewsPerApp`) 4. Apply filters: - rating - keywords - date range - duplicates 5. Return structured dataset *** ### ๐Ÿง  Optimization Tips For best results: - Use `reviewsPerApp >= 100` - Combine multiple `appsLimit` - Use `recentDays = 30` for fresh data - Use `keywords` for niche insights - Use `ratingFilter = 1` for complaint mining *** ### โš ๏ธ Notes - Google Play does not expose full review history - Pagination improves coverage but is still limited - Some reviews vary by region/language # Actor input Schema ## `term` (type: `string`): Keyword to search apps on Google Play Store ## `maxItems` (type: `integer`): Maximum number of reviews to collect ## `appsLimit` (type: `integer`): Number of apps from search results ## `reviewsPerApp` (type: `integer`): Max reviews per app fetch batch ## `sort` (type: `string`): Review sorting method ## `country` (type: `string`): Country code (us, gb, de, hr...) ## `language` (type: `string`): Language code ## `uniqueOnly` (type: `boolean`): Remove duplicates ## `ratingFilter` (type: `integer`): Exact rating filter (1-5, 0 = all) ## `keywords` (type: `array`): Only include reviews containing keywords ## `recentDays` (type: `integer`): Only last N days reviews (0 = off) ## Actor input object example ```json { "term": "chatgpt", "maxItems": 50, "appsLimit": 5, "reviewsPerApp": 100, "sort": "newest", "country": "us", "language": "en", "uniqueOnly": true, "ratingFilter": 0, "keywords": [], "recentDays": 0 } ``` # Actor output Schema ## `datasetItems` (type: `string`): Scraped Google Play reviews dataset ## `datasetUrl` (type: `string`): No description ## `totalItems` (type: `string`): No description ## `actorRunId` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("ahmed_jasarevic/google-play-reviews-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("ahmed_jasarevic/google-play-reviews-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call ahmed_jasarevic/google-play-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ahmed_jasarevic/google-play-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Play Reviews Intelligence & Insights Scraper", "description": "Extract structured Google Play app reviews and turn them into actionable market intelligence. Analyze user feedback, ratings, and trends across multiple apps using powerful filters like keywords, rating, and time range. Perfect for competitor research, ASO optimization, and sentiment analysis.", "version": "1.0", "x-build-id": "XgVfw756a5yRacVtn" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ahmed_jasarevic~google-play-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ahmed_jasarevic-google-play-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ahmed_jasarevic~google-play-reviews-scraper/runs": { "post": { "operationId": "runs-sync-ahmed_jasarevic-google-play-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ahmed_jasarevic~google-play-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-ahmed_jasarevic-google-play-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "term" ], "properties": { "term": { "title": "Search Term", "type": "string", "description": "Keyword to search apps on Google Play Store", "default": "chatgpt" }, "maxItems": { "title": "Max Reviews", "type": "integer", "description": "Maximum number of reviews to collect", "default": 50 }, "appsLimit": { "title": "Apps to Scan", "type": "integer", "description": "Number of apps from search results", "default": 5 }, "reviewsPerApp": { "title": "Reviews per App", "type": "integer", "description": "Max reviews per app fetch batch", "default": 100 }, "sort": { "title": "Sort By", "enum": [ "newest", "rating", "helpfulness" ], "type": "string", "description": "Review sorting method", "default": "newest" }, "country": { "title": "Country", "type": "string", "description": "Country code (us, gb, de, hr...)", "default": "us" }, "language": { "title": "Language", "type": "string", "description": "Language code", "default": "en" }, "uniqueOnly": { "title": "Unique Reviews Only", "type": "boolean", "description": "Remove duplicates", "default": true }, "ratingFilter": { "title": "Rating Filter", "type": "integer", "description": "Exact rating filter (1-5, 0 = all)", "default": 0 }, "keywords": { "title": "Keywords Filter", "type": "array", "description": "Only include reviews containing keywords", "items": { "type": "string" }, "default": [] }, "recentDays": { "title": "Recent Days Filter", "type": "integer", "description": "Only last N days reviews (0 = off)", "default": 0 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```