# App Store & Google Play Reviews Scraper + Insights Report (`berkaydev/app-review-insights-scraper`) Actor Scrape Google Play AND Apple App Store reviews, then get a built-in insights report — rating trends by version, complaint/praise keywords, feature-request signals, suspicious spike detection, and cross-app comparison. No API key needed. Pure HTTP, free-plan compatible. Pay per review scraped. - **URL**: https://apify.com/berkaydev/app-review-insights-scraper.md - **Developed by:** [Berkay](https://apify.com/berkaydev) (community) - **Categories:** Developer tools, Business, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $0.30 / 1,000 review scrapeds 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 **The only Google Play review scraper and Apple App Store review scraper that also delivers a built-in insights report** — no extra cost, no LLM, no API key required. Runs on the free Apify plan. Competitors return raw review rows. This actor gives you raw reviews **plus** analytics: rating trends by app version, top complaint/praise keywords, feature-request signals, suspicious spike detection, and cross-app comparison. ### App review insights report: complaint analysis, version trends, and cross-app comparison The built-in insights report turns raw reviews into answers: a complaint and praise keyword analysis, rating trends by app version, feature-request signals, suspicious-spike detection, and a side-by-side cross-app comparison when you scrape more than one app. ### What it does 1. **Scrapes reviews** from Google Play and/or the Apple App Store (pure HTTP — no browser, free-plan compatible). 2. **Normalises** both sources into a unified schema (same fields for both stores). 3. **Computes insights** (pure Python analytics): - Rating distribution (1–5 stars) - Rating trend by month - **Rating by app version** — the killer developer insight: which release tanked or improved the score - Top complaint keywords from 1–2★ reviews - Top praise keywords from 4–5★ reviews - Feature-request signal detection ("please add", "wish", "would be great", "fehlt", etc.) - Suspicious spike months (possible fake/incentivised burst of reviews) - Cross-app comparison table (when scraping multiple apps) 4. **Writes** the insights as JSON (`INSIGHTS` KVS key) and as a clean HTML report (`REPORT` KVS key). ### Use cases - **ASO (App Store Optimisation)**: understand what users love and hate to improve your store listing. - **Competitive analysis**: compare your app's sentiment against competitors across both stores. - **Release quality monitoring**: see exactly which version caused a rating drop. - **Feature roadmap**: surface the most-requested features from user reviews. - **Review moderation / support**: identify complaint clusters to address in the next release. ### Input | Field | Type | Default | Description | |---|---|---|---| | `googlePlayAppIds` | string[] | `["com.whatsapp"]` | Package names or Play Store URLs | | `appleAppIds` | string[] | `[]` | Numeric Apple IDs or App Store URLs | | `country` | string | `"us"` | Store country code (ISO 3166-1 alpha-2) | | `language` | string | `"en"` | Language code (ISO 639-1) | | `maxReviewsPerApp` | integer | `200` | Max reviews per app (Apple caps at ~500 via RSS) | | `generateInsights` | boolean | `true` | Generate the insights report | | `maxRunTimeSecs` | integer | `3000` | Internal run deadline | At least one of `googlePlayAppIds` or `appleAppIds` must be non-empty. #### Example input (JSON) ```json { "googlePlayAppIds": ["com.whatsapp", "com.spotify.music"], "appleAppIds": ["310633997"], "country": "us", "language": "en", "maxReviewsPerApp": 200, "generateInsights": true } ```` ### Output #### Dataset — unified review records Each record has the same fields regardless of the source store: ```json { "source": "googlePlay", "appId": "com.whatsapp", "appName": "WhatsApp Messenger", "reviewId": "gp:AbcDef123...", "userName": "JohnDoe", "rating": 5, "title": null, "text": "Works perfectly, love the encryption.", "appVersion": "2.24.10.73", "thumbsUp": 12, "date": "2024-05-03T14:22:00+00:00", "replyContent": null, "replyDate": null, "country": "us", "language": "en" } ``` > **Note:** `title` is null for Google Play (no review titles). `thumbsUp` is null for Apple App Store. `replyContent`/`replyDate` are null for Apple (not available in the public RSS feed). #### KVS: INSIGHTS (JSON) ```json { "apps": { "googlePlay:com.whatsapp": { "appName": "WhatsApp Messenger", "averageRating": 4.21, "storeAverageRating": 4.4, "storeRatingCount": 185000000, "ratingDistribution": { "5": {"count": 31, "pct": 62.0}, ... }, "ratingByVersion": { "2.24.10.73": {"reviewCount": 18, "avgRating": 4.50}, "2.24.9.81": {"reviewCount": 12, "avgRating": 3.25} }, "topComplaintTerms": [{"term": "crashes", "count": 8}, ...], "topPraiseTerms": [{"term": "easy use", "count": 14}, ...], "featureRequestSignals": {"count": 6, "snippets": ["please add voice messages..."]}, "suspiciousSpikeMonths": [], ... } }, "comparison": [ {"appName": "WhatsApp Messenger", "store": "googlePlay", "averageRating": 4.21, ...} ] } ``` #### KVS: REPORT (HTML) A standalone HTML page with colour-coded rating cards, star distribution bars, version rating table, keyword pills, feature request snippets, trend table, and comparison table. Open directly in a browser or embed in a dashboard. ### Google Play field mapping | google-play-scraper field | Actor field | |---|---| | `title` (app metadata) | `appName` | | `score` (app metadata) | `storeAverageRating` | | `ratings` | `storeRatingCount` | | `version` | `currentVersion` (metadata) | | `reviewId` | `reviewId` | | `userName` | `userName` | | `content` | `text` | | `score` (review) | `rating` | | `thumbsUpCount` | `thumbsUp` | | `reviewCreatedVersion` | `appVersion` | | `at` (datetime) | `date` (ISO 8601) | | `replyContent` | `replyContent` | | `repliedAt` | `replyDate` (ISO 8601) | ### Apple App Store field mapping | iTunes endpoint / field | Actor field | |---|---| | Lookup `trackName` | `appName` | | Lookup `averageUserRating` | `storeAverageRating` | | Lookup `userRatingCount` | `storeRatingCount` | | Lookup `version` | `currentVersion` (metadata) | | RSS `id.label` | `reviewId` | | RSS `author.name.label` | `userName` | | RSS `title.label` | `title` | | RSS `content.label` | `text` | | RSS `im:rating.label` | `rating` | | RSS `im:version.label` | `appVersion` | | RSS `updated.label` | `date` | | n/a | `thumbsUp` = null | | n/a | `replyContent` = null | ### Pricing Pay per review scraped (**$0.0003/review = $0.30 per 1,000**), no per-run start fee. The insights report is always included free. Cheaper than most App Store review scrapers — and the only one that also returns a built-in analysis report. A run with 200 Google Play reviews + 200 Apple reviews = $0.12 total. ### Limitations - Apple App Store RSS caps at ~500 reviews per app (10 pages × 50). - Apple RSS does not provide developer replies or thumbs-up counts. - Reviews are fetched in "most recent" order; historical bulk export is not supported by the public endpoints. - Language/country filter on Apple applies to the store region; Apple RSS returns mixed languages. ### Technical notes - Pure HTTP — no browser, no Playwright. Runs on Apify free plan (512 MB memory is sufficient). - `google-play-scraper` PyPI package handles Google Play pagination and anti-bot headers. - Apple App Store uses the public iTunes RSS feed + lookup API (no authentication). - Insights computed in pure Python (no LLM, no paid API). # Actor input Schema ## `googlePlayAppIds` (type: `array`): Package names or full Google Play URLs to scrape. Examples: 'com.whatsapp', 'https://play.google.com/store/apps/details?id=com.spotify.music'. One per line. ## `appleAppIds` (type: `array`): Numeric Apple app IDs or full App Store URLs to scrape. Examples: '310633997', 'https://apps.apple.com/us/app/whatsapp-messenger/id310633997'. One per line. ## `country` (type: `string`): Two-letter ISO 3166-1 alpha-2 country code for the store region (e.g. 'us', 'de', 'gb'). ## `language` (type: `string`): Two-letter ISO 639-1 language code for the review language (e.g. 'en', 'de'). Used for Google Play; Apple RSS returns mixed languages. ## `maxReviewsPerApp` (type: `integer`): Maximum number of reviews to scrape per app. Google Play supports up to several thousand; Apple App Store RSS caps at ~500 (10 pages x 50). ## `generateInsights` (type: `boolean`): Compute an analytics/insights report after scraping: rating trends by version, top complaint/praise keywords, feature-request signals, suspicious spikes, and cross-app comparison. Written to key-value store as JSON (INSIGHTS) and HTML (REPORT). ## `maxRunTimeSecs` (type: `integer`): Internal run deadline. The actor will flush collected data and exit cleanly before this limit. ## Actor input object example ```json { "googlePlayAppIds": [ "com.whatsapp" ], "appleAppIds": [], "country": "us", "language": "en", "maxReviewsPerApp": 50, "generateInsights": true, "maxRunTimeSecs": 3000 } ``` # Actor output Schema ## `reviews` (type: `string`): One row per app review from Google Play and the iOS App Store: rating, title, text, author, version, and date. ## `report` (type: `string`): Ready-to-read report: rating trends, complaint and praise keywords, version sentiment, and suspicious spike detection. ## `insights` (type: `string`): The full analytics object behind the report, machine-readable for your own pipelines. # 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 = { "googlePlayAppIds": [ "com.whatsapp" ], "country": "us", "language": "en", "maxReviewsPerApp": 50, "generateInsights": true }; // Run the Actor and wait for it to finish const run = await client.actor("berkaydev/app-review-insights-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 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); }); // 📚 Want to learn more 📖? Go to → 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 = { "googlePlayAppIds": ["com.whatsapp"], "country": "us", "language": "en", "maxReviewsPerApp": 50, "generateInsights": True, } # Run the Actor and wait for it to finish run = client.actor("berkaydev/app-review-insights-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "googlePlayAppIds": [ "com.whatsapp" ], "country": "us", "language": "en", "maxReviewsPerApp": 50, "generateInsights": true }' | apify call berkaydev/app-review-insights-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=berkaydev/app-review-insights-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "App Store & Google Play Reviews Scraper + Insights Report", "description": "Scrape Google Play AND Apple App Store reviews, then get a built-in insights report — rating trends by version, complaint/praise keywords, feature-request signals, suspicious spike detection, and cross-app comparison. No API key needed. Pure HTTP, free-plan compatible. Pay per review scraped.", "version": "0.1", "x-build-id": "TE2VMBlYIS8xYeh5o" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/berkaydev~app-review-insights-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-berkaydev-app-review-insights-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/berkaydev~app-review-insights-scraper/runs": { "post": { "operationId": "runs-sync-berkaydev-app-review-insights-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/berkaydev~app-review-insights-scraper/run-sync": { "post": { "operationId": "run-sync-berkaydev-app-review-insights-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "googlePlayAppIds": { "title": "Google Play App IDs / URLs", "type": "array", "description": "Package names or full Google Play URLs to scrape. Examples: 'com.whatsapp', 'https://play.google.com/store/apps/details?id=com.spotify.music'. One per line.", "items": { "type": "string" } }, "appleAppIds": { "title": "Apple App Store App IDs / URLs", "type": "array", "description": "Numeric Apple app IDs or full App Store URLs to scrape. Examples: '310633997', 'https://apps.apple.com/us/app/whatsapp-messenger/id310633997'. One per line.", "default": [], "items": { "type": "string" } }, "country": { "title": "Country code", "type": "string", "description": "Two-letter ISO 3166-1 alpha-2 country code for the store region (e.g. 'us', 'de', 'gb').", "default": "us" }, "language": { "title": "Language code", "type": "string", "description": "Two-letter ISO 639-1 language code for the review language (e.g. 'en', 'de'). Used for Google Play; Apple RSS returns mixed languages.", "default": "en" }, "maxReviewsPerApp": { "title": "Max reviews per app", "minimum": 1, "type": "integer", "description": "Maximum number of reviews to scrape per app. Google Play supports up to several thousand; Apple App Store RSS caps at ~500 (10 pages x 50).", "default": 200 }, "generateInsights": { "title": "Generate insights report", "type": "boolean", "description": "Compute an analytics/insights report after scraping: rating trends by version, top complaint/praise keywords, feature-request signals, suspicious spikes, and cross-app comparison. Written to key-value store as JSON (INSIGHTS) and HTML (REPORT).", "default": true }, "maxRunTimeSecs": { "title": "Max run time (seconds)", "minimum": 60, "maximum": 3500, "type": "integer", "description": "Internal run deadline. The actor will flush collected data and exit cleanly before this limit.", "default": 3000 } } }, "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 } } } } } } } } } } ```