# App Review Scraper & Monitor (`digitalstamp/app-review-scraper-monitor`) Actor Scrape app reviews from Apple App Store and Google Play in one unified schema. Backfill up to 500 reviews or monitor for new ones on a schedule. Optional AI sentiment tagging (BYOK). Built for product managers, ASO teams, and agencies. - **URL**: https://apify.com/digitalstamp/app-review-scraper-monitor.md - **Developed by:** [Marcello Alves](https://apify.com/digitalstamp) (community) - **Categories:** E-commerce, AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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 ## App Store & Google Play Review Scraper & Monitor **Scrape app reviews from the Apple App Store and Google Play in one unified format**, monitor new reviews on a schedule, and optionally tag every review with **AI sentiment and themes**. Built for app developers, ASO teams, product managers, and competitive-intelligence workflows that need reliable mobile app review data without juggling two separate scrapers. Paste a single App Store or Google Play URL and get clean, structured review data as JSON, CSV, or Excel — both stores, one schema. --- ### What you get Every review — whether from Apple or Google — comes back in the **same unified schema**: | Field | Description | |---|---| | `store` | `apple` or `google` | | `appId` | Apple numeric ID or Google package name | | `appName` | Human-readable app name | | `country` | App Store / Play country (ISO 2-letter) | | `reviewId` | Unique review identifier | | `rating` | Star rating, 1–5 | | `title` | Review title (Apple; Google may be null) | | `body` | Review text | | `author` | Reviewer name | | `authorUrl` | Reviewer profile URL (Google) or null | | `version` | App version reviewed (when available) | | `date` | Review date (ISO 8601) | | `sentiment` | `positive` / `neutral` / `negative` *(only if sentiment enabled)* | | `themes` | Short topic tags e.g. `["crashes","pricing"]` *(only if sentiment enabled)* | | `isNew` | `true` for reviews new since the last run *(monitor mode)* | | `scrapedAt` | When this run scraped the review (ISO 8601) | --- ### Two modes #### Backfill mode (default) Pull **all available reviews** for each app, up to your limit. Great for a one-time export, sentiment baseline, or competitor snapshot. #### Monitor mode — track new reviews on a schedule On the first run it stores the current reviews as state. On **every subsequent run it outputs only the reviews that are new since last time** (`isNew: true`). Point Apify's scheduler at it (daily or weekly) and you get a continuous feed of fresh reviews — perfect for support alerts, release monitoring, and tracking sentiment over time. If there are no new reviews, the run finishes cleanly with an empty dataset (not an error). --- ### AI sentiment & theme tagging (optional) Turn on **Enable AI sentiment & theme tagging** and each review is classified as **positive / neutral / negative** and tagged with short themes such as `crashes`, `pricing`, `onboarding`, `ui`, `performance`, or `customer support`. This turns raw reviews into an instant, queryable picture of what users love and complain about. - Choose your provider: **Anthropic (Claude Haiku)** or **OpenAI (GPT-4o-mini)**. - Supply the matching API key in the input (stored securely). - Sentiment is billed as a **separate pay-per-event** (see Pricing). If no key is supplied, the run still succeeds — reviews are simply returned without sentiment fields. --- ### Input The simplest input is a single store URL pasted into `apps`: ```json { "apps": [ "https://apps.apple.com/us/app/whatsapp-messenger/id310633997" ] } ```` Mix URLs and structured objects, scrape both stores at once, and turn on monitoring + sentiment: ```json { "apps": [ "https://apps.apple.com/us/app/whatsapp-messenger/id310633997", "https://play.google.com/store/apps/details?id=com.whatsapp&gl=US", { "store": "google", "appId": "com.spotify.music", "country": "gb" } ], "mode": "monitor", "maxReviewsPerApp": 500, "language": "en", "enableSentiment": true, "sentimentProvider": "anthropic", "anthropicApiKey": "sk-ant-..." } ``` Both **URL strings** and **structured `{ store, appId, country }` objects** work. App Store URLs (`.../id310633997`) and Google Play URLs (`...?id=com.whatsapp`) are parsed automatically, including the country segment. *** ### Output examples **Apple review:** ```json { "store": "apple", "appId": "310633997", "appName": "WhatsApp Messenger", "country": "us", "reviewId": "10987654321", "rating": 2, "title": "Keeps crashing after update", "body": "Since the latest version the app crashes when I open a chat...", "author": "frustrated_user", "authorUrl": null, "version": "24.5.0", "date": "2026-06-15T09:31:00.000Z", "isNew": true, "scrapedAt": "2026-06-18T12:00:00.000Z" } ``` **Google Play review with sentiment:** ```json { "store": "google", "appId": "com.whatsapp", "appName": "WhatsApp Messenger", "country": "us", "reviewId": "gp:AOq...", "rating": 5, "title": null, "body": "Fast, reliable and the new UI looks great.", "author": "Alex M.", "authorUrl": "https://play.google.com/store/apps/details?id=com.whatsapp&reviewId=gp:AOq...", "version": "2.24.5.78", "date": "2026-06-16T18:02:00.000Z", "sentiment": "positive", "themes": ["performance", "ui"], "isNew": true, "scrapedAt": "2026-06-18T12:00:00.000Z" } ``` *** ### Use cases - **App Store Optimization (ASO):** track rating and review trends across both stores. - **Product management:** surface feature requests and recurring pain points from sentiment themes. - **Release monitoring:** schedule monitor mode to catch new negative reviews right after a release. - **Customer support:** feed new 1–2★ reviews into Slack/email via Apify integrations. - **Competitive intelligence:** compare review sentiment across competing apps. - **App agencies:** monitor reviews for many client apps from a single scheduled actor. *** ### Pricing (Pay-Per-Event) This actor uses Apify's Pay-Per-Event model. You are billed only for what you use: | Event | When charged | |---|---| | **Actor run start** | Once per run | | **Review scraped** | Per review extracted (in monitor mode, only new reviews are charged) | | **Review sentiment tagged** | Per review tagged with AI sentiment (only when sentiment is enabled) | Note: when sentiment is enabled you also pay your own LLM provider (Anthropic/OpenAI) directly for the API usage, using your supplied key. *** ### Limitations (read before you run) - **Apple caps reviews at ~500 per app.** The public Apple feed exposes only the 10 most-recent pages (~500 reviews) per app/country. This is an Apple-side limit. For deep history use multiple countries, or lean on **monitor mode** (where the cap rarely matters because you only need what's new). - **Google Play** can return more history, but Google occasionally changes its markup; if a Google run starts returning empty, it usually means a parser update is needed — Apple runs are unaffected. - Reviews are public data exposed by each store's own public feeds/endpoints. *** ### FAQ **Can I scrape multiple countries?** Yes — add the same app with different `country` values (Apple), or `gl=` in the Play URL. **Does monitor mode need any setup?** No. Just set `mode: monitor` and attach an Apify schedule. State is stored automatically between runs. **What languages are supported?** Set `language` (e.g. `en`, `es`, `de`) for Google Play reviews. Apple reviews are returned per country. **Is an API key required?** Only if you enable AI sentiment. Plain scraping needs no key. **Can I call this from code / an AI agent?** Yes — run it via the Apify API, or call it as a tool through Apify's MCP integration. # Actor input Schema ## `apps` (type: `array`): Apps to scrape reviews for. Paste a full App Store or Google Play URL as a string, OR provide a structured object { store, appId, country }. The simplest input is a single store URL. ## `mode` (type: `string`): backfill = pull all available reviews up to the limit. monitor = on the first run store the latest reviews as state, then on later runs output ONLY reviews new since the previous run (ideal for scheduled daily/weekly runs). ## `maxReviewsPerApp` (type: `integer`): Upper bound on reviews per app per run. Apple's public feed caps at ~500 reviews per app; Google Play can go deeper. ## `language` (type: `string`): ISO 2-letter language code used for Google Play reviews (e.g. en, es, de). Apple reviews are returned per-country. ## `enableSentiment` (type: `boolean`): When enabled, each review is classified as positive / neutral / negative and tagged with short themes (e.g. crashes, pricing, onboarding). Billed as a separate pay-per-event. Requires an API key below. ## `sentimentProvider` (type: `string`): Which LLM provider to use for sentiment tagging (only used when sentiment is enabled). ## `sentimentModel` (type: `string`): Override the default model. Defaults: anthropic -> claude-haiku-4-5, openai -> gpt-4o-mini. ## `anthropicApiKey` (type: `string`): Required only when sentiment is enabled and provider = anthropic. Stored securely. ## `openaiApiKey` (type: `string`): Required only when sentiment is enabled and provider = openai. Stored securely. ## Actor input object example ```json { "apps": [ "https://apps.apple.com/us/app/whatsapp-messenger/id310633997", { "store": "google", "appId": "com.whatsapp", "country": "us" } ], "mode": "backfill", "maxReviewsPerApp": 500, "language": "en", "enableSentiment": false, "sentimentProvider": "anthropic", "sentimentModel": "" } ``` # 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 = { "apps": [ "https://apps.apple.com/us/app/whatsapp-messenger/id310633997", { "store": "google", "appId": "com.whatsapp", "country": "us" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("digitalstamp/app-review-scraper-monitor").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 = { "apps": [ "https://apps.apple.com/us/app/whatsapp-messenger/id310633997", { "store": "google", "appId": "com.whatsapp", "country": "us", }, ] } # Run the Actor and wait for it to finish run = client.actor("digitalstamp/app-review-scraper-monitor").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 '{ "apps": [ "https://apps.apple.com/us/app/whatsapp-messenger/id310633997", { "store": "google", "appId": "com.whatsapp", "country": "us" } ] }' | apify call digitalstamp/app-review-scraper-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=digitalstamp/app-review-scraper-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "App Review Scraper & Monitor", "description": "Scrape app reviews from Apple App Store and Google Play in one unified schema. Backfill up to 500 reviews or monitor for new ones on a schedule. Optional AI sentiment tagging (BYOK). Built for product managers, ASO teams, and agencies.", "version": "0.0", "x-build-id": "3Ve9FyrERgMJQ7pIM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/digitalstamp~app-review-scraper-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-digitalstamp-app-review-scraper-monitor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/digitalstamp~app-review-scraper-monitor/runs": { "post": { "operationId": "runs-sync-digitalstamp-app-review-scraper-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/digitalstamp~app-review-scraper-monitor/run-sync": { "post": { "operationId": "run-sync-digitalstamp-app-review-scraper-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "apps" ], "properties": { "apps": { "title": "Apps", "type": "array", "description": "Apps to scrape reviews for. Paste a full App Store or Google Play URL as a string, OR provide a structured object { store, appId, country }. The simplest input is a single store URL." }, "mode": { "title": "Mode", "enum": [ "backfill", "monitor" ], "type": "string", "description": "backfill = pull all available reviews up to the limit. monitor = on the first run store the latest reviews as state, then on later runs output ONLY reviews new since the previous run (ideal for scheduled daily/weekly runs).", "default": "backfill" }, "maxReviewsPerApp": { "title": "Max reviews per app", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Upper bound on reviews per app per run. Apple's public feed caps at ~500 reviews per app; Google Play can go deeper.", "default": 500 }, "language": { "title": "Language", "type": "string", "description": "ISO 2-letter language code used for Google Play reviews (e.g. en, es, de). Apple reviews are returned per-country.", "default": "en" }, "enableSentiment": { "title": "Enable AI sentiment & theme tagging", "type": "boolean", "description": "When enabled, each review is classified as positive / neutral / negative and tagged with short themes (e.g. crashes, pricing, onboarding). Billed as a separate pay-per-event. Requires an API key below.", "default": false }, "sentimentProvider": { "title": "Sentiment AI provider", "enum": [ "anthropic", "openai" ], "type": "string", "description": "Which LLM provider to use for sentiment tagging (only used when sentiment is enabled).", "default": "anthropic" }, "sentimentModel": { "title": "Sentiment model (optional)", "type": "string", "description": "Override the default model. Defaults: anthropic -> claude-haiku-4-5, openai -> gpt-4o-mini.", "default": "" }, "anthropicApiKey": { "title": "Anthropic API key", "type": "string", "description": "Required only when sentiment is enabled and provider = anthropic. Stored securely." }, "openaiApiKey": { "title": "OpenAI API key", "type": "string", "description": "Required only when sentiment is enabled and provider = openai. Stored securely." } } }, "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 } } } } } } } } } } ```