# Apple App Store Reviews Scraper (`scrapesmith/apple-app-store-reviews-scraper`) Actor Extract Apple App Store reviews at scale. Get star ratings, review text, author names, helpful votes, app versions, and full app metadata for any iOS app. 50+ countries, date filtering, two sort modes. No browser, no proxy, no API key needed. - **URL**: https://apify.com/scrapesmith/apple-app-store-reviews-scraper.md - **Developed by:** [Scrape Smith](https://apify.com/scrapesmith) (community) - **Categories:** Developer tools, Automation, Other - **Stats:** 2 total users, 1 monthly users, 85.7% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.45 / 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 ## Apple App Store Reviews Scraper — Ratings, Dates, Versions & Helpful Votes Extract every Apple App Store review for any iOS app in seconds. This App Store reviews scraper pulls star ratings, review text, author names, app versions, helpful votes, and full app metadata — all structured and ready to use, with no coding required. --- ### Why Use This App Store Reviews Scraper? - **25,000+ reviews per minute** — one of the fastest App Store review extractors available on Apify - **No browser, no proxy, no API key required** — fully anonymous, zero setup, zero maintenance - **50+ App Store countries supported** — pull localized reviews from the US, UK, Germany, Japan, Brazil, and dozens more storefronts - **Two sort modes** — Most Recent for fresh sentiment tracking, Most Helpful for the reviews users actually read - **Date filtering built in** — only fetch reviews since a given date, perfect for daily or weekly monitoring runs - **App metadata on every review** — app name, developer, overall rating, rating count, and category are attached to each individual review row, so you never need a second scraper for context - **Multi-app, multi-country parallel processing** — feed in dozens of App Store IDs and countries in a single run and get everything back at once - **Lightweight and reliable** — runs on minimal compute with no browser overhead, so runs finish fast and don't get flagged or blocked Whether you're tracking iOS app ratings, monitoring App Store reviews for a client, or building a sentiment analysis pipeline, this scraper gets you clean review data without the usual scraping headaches. --- ### What Data Do You Get? Every review comes back with 20 fields covering the review itself, the reviewer, and the parent app — so a single dataset gives you everything needed for App Store review analysis. | Field | Description | |---|---| | **reviewId** | Unique identifier for the review | | **title** | Review headline written by the user | | **text** | Full review body text | | **rating** | Star rating from 1 to 5 | | **author** | Reviewer's display name | | **authorUrl** | Link to the reviewer's App Store profile | | **date** | Review submission date and time (ISO 8601, with timezone) | | **appVersion** | App version the review was written against | | **helpfulVotes** | Number of users who marked the review as helpful | | **totalVotes** | Total number of helpfulness votes cast | | **appId** | The App Store numeric ID for the app | | **appName** | App name | | **appDeveloper** | Publisher / developer name | | **appRating** | App's current overall average rating | | **appRatingCount** | Total number of ratings the app has received | | **appCategory** | Primary App Store category | | **country** | App Store storefront the review was pulled from | | **sortBy** | Sort order used for this run (mostrecent or mosthelpful) | | **scrapedAt** | Timestamp of when the data was collected | | **status** | Result status for the review row | --- ### Input Parameters ```json { "appIds": ["https://apps.apple.com/us/app/whatsapp-messenger/id310633997"], "countries": ["us"], "sortBy": "mostrecent", "maxReviews": 500 } ```` | Parameter | Type | Required | Default | Description | |---|---|---|---|---| | `appIds` | array | Yes | — | App Store numeric IDs or full App Store URLs. IDs are extracted automatically from URLs, so you can paste either. | | `countries` | array | No | `["us"]` | App Store country codes to pull reviews from (e.g. `us`, `gb`, `de`, `jp`, `br`). Add multiple to get localized reviews from several storefronts in one run. | | `sortBy` | string | No | `mostrecent` | Review sort order: `mostrecent` or `mosthelpful`. | | `maxReviews` | integer | No | 500 | Maximum reviews to return per app per country. | | `sinceDate` | string | No | — | Only include reviews on or after this date. Format: `YYYY-MM-DD`. | *** ### Sample Output ```json { "reviewId": "14249474782", "title": "Amazing app", "text": "WhatsApp is used worldwide...", "rating": 5, "author": "M Ohanlon", "authorUrl": "https://itunes.apple.com/us/reviews/id559572394", "date": "2026-07-01T10:15:02-07:00", "appVersion": "26.25.74", "helpfulVotes": 0, "totalVotes": 0, "appId": "310633997", "appName": "WhatsApp Messenger", "appDeveloper": "WhatsApp Inc.", "appRating": 4.69, "appRatingCount": 18177792, "appCategory": "Social Networking", "country": "us", "sortBy": "mostrecent", "scrapedAt": "2026-07-02T20:30:00Z", "status": "ok" } ``` *** ### How Fast Is It? | Scenario | Reviews | Time | |---|---|---| | Single app, one country | 500 | ~5 seconds | | Small batch (5 apps) | 2,500 | ~8 seconds | | Medium batch (20 apps) | 10,000 | ~15 seconds | | Large batch | 5,000 | ~5 seconds | | Bulk run, multiple countries | 25,000+ | ~1 minute | Since there's no browser to launch and no proxy round-trips to wait on, this App Store reviews scraper spends its time doing exactly one thing — fetching review data — which is why throughput stays consistently fast across small and large runs alike. *** ### Use Cases #### App Store Optimization (ASO) & Review Monitoring - **Track star rating trends over time** by running the scraper on a schedule and comparing `appRating` and `appRatingCount` across runs - **Monitor new reviews daily** using `sinceDate` to only pull what's changed since your last check - **Benchmark against competitor apps** by scraping reviews for multiple App Store IDs in the same category - **Feed ASO tools and dashboards** with clean, structured review data instead of manually copying reviews #### Customer Feedback & Product Analytics - **Surface recurring complaints and feature requests** by running review text through keyword or topic extraction - **Prioritize bug fixes** by filtering the most helpful negative reviews (`sortBy: mosthelpful`) mentioning specific app versions - **Track sentiment by app version** using the `appVersion` field to see if a release improved or hurt user sentiment - **Build a customer voice repository** for product and support teams without needing App Store Connect access #### Market Research & Competitive Intelligence - **Compare rating distribution across competitors** in the same category using `appCategory` and `appRating` - **Identify market gaps** by analyzing what users complain about across multiple apps in a niche - **Localize your understanding of user sentiment** by pulling reviews from multiple `countries` in a single run - **Support due diligence and market entry research** with structured review datasets ready for spreadsheets or BI tools #### AI, NLP & Machine Learning - **Build sentiment analysis training sets** from millions of labeled star ratings paired with review text - **Fine-tune LLMs on real customer feedback** using the `text` and `rating` fields as input-output pairs - **Train review summarization models** using helpful-vote-ranked reviews as ground truth for "most useful feedback" - **Power AI-driven customer support tools** by classifying incoming reviews using patterns learned from historical data #### Marketing & PR - **Find quotable customer testimonials** by filtering high-rating, high-helpful-vote reviews - **Track brand sentiment after a major release** by monitoring reviews in the days following an update - **Identify influential reviewers** whose reviews consistently receive high helpful vote counts *** ### Frequently Asked Questions **How do I scrape App Store reviews without coding?** Just provide the App Store app ID or app URL as input and run the actor. No code, API key, or technical setup is required — the scraper handles everything and returns structured review data directly to your dataset. **Can I get reviews from multiple countries in one run?** Yes. Add multiple country codes to the `countries` array (e.g. `["us", "gb", "de"]`) and the scraper returns localized reviews from each App Store storefront for every app you specify. **What's the difference between Most Recent and Most Helpful sorting?** `mostrecent` returns the newest reviews first, ideal for daily monitoring and catching fresh complaints or praise. `mosthelpful` returns reviews with the most helpful votes first, which tend to be the most detailed and representative of common user opinions. **How many reviews can I scrape per app?** Apple's App Store exposes up to 500 reviews per app per country through the review pages this scraper reads. Set `maxReviews` up to that limit, or run once per country to gather more total reviews across storefronts. **Can I filter reviews by date?** Yes. Use the `sinceDate` parameter with a `YYYY-MM-DD` date to only receive reviews submitted on or after that day — useful for incremental daily or weekly monitoring without re-processing old reviews. **Does the output include the app's overall rating, or just individual review ratings?** Both. Each review row includes its own `rating` (1-5 stars for that specific review) plus the app-level `appRating` and `appRatingCount`, so you get individual and aggregate sentiment in the same dataset. **Do I need an App Store Connect account or Apple Developer credentials?** No. This scraper works entirely from publicly available App Store review pages. You don't need to own the app, have developer access, or authenticate with Apple in any way. **Is a proxy needed to scrape App Store reviews?** No. This scraper runs without any proxy configuration and without a browser. It's built to be lightweight and fast by design, not because it's cutting corners — it simply doesn't need either to reliably pull review data. **Can I track reviews for competitor apps?** Yes. Since this scraper only needs a public App Store ID or URL, you can monitor reviews for any published app, including competitors, to benchmark ratings and extract insights from their user feedback. **What does the `status` field mean?** It indicates the result of processing that review row, confirming the review was captured and parsed successfully so you can filter your dataset with confidence. **Can I run this scraper on a schedule?** Yes. Apify's built-in scheduler lets you run this actor daily, weekly, or on any custom interval so you can continuously monitor new App Store reviews without manual effort. **Does this work for apps that only have a few reviews?** Yes. The scraper returns however many reviews are available up to your `maxReviews` setting — if an app only has 12 reviews, you'll get all 12. **Can I export the results to Excel or Google Sheets?** Yes. Apify datasets support exporting to JSON, CSV, Excel, XML, and other formats, plus direct integrations to Google Sheets and other tools. **How current is the review data?** Every run fetches reviews live from the App Store at the time the actor runs — there's no caching or stale data involved, so you always get the latest reviews available. **Can I scrape reviews for apps that aren't in English?** Yes. Set the appropriate `countries` value for the storefront you want, and reviews will come back in whatever language users wrote them in for that region. *** ### Output Formats Results are available directly from your dataset in every format Apify supports: - **JSON** — structured data for programmatic use and API integration - **CSV** — flat table format, opens directly in Excel and Google Sheets - **Excel (.xlsx)** — native spreadsheet format with proper headers - **XML** — structured markup for enterprise integrations *** ### Integration & Automation Connect this App Store reviews scraper to your existing workflow: - **Google Sheets** — append new reviews to a spreadsheet automatically - **Slack / Discord** — get notified when a scheduled run finds new reviews - **Webhooks** — trigger your own systems when a run completes - **Zapier / Make** — connect to thousands of apps without writing code - **BigQuery / Snowflake / data warehouses** — load review data for long-term analysis Set up a recurring schedule with Apify's built-in scheduler to monitor new App Store reviews daily or weekly without lifting a finger. # Actor input Schema ## `appIds` (type: `array`): App Store numeric IDs or URLs. ID extracted automatically from URLs. ## `countries` (type: `array`): App Store country codes (e.g. us, gb, de, jp). ## `sortBy` (type: `string`): Review sort order. ## `maxReviews` (type: `integer`): Max reviews per app per country. Apple exposes at most 500 (10 pages x 50). ## `sinceDate` (type: `string`): Only include reviews on or after this date. Format: YYYY-MM-DD ## Actor input object example ```json { "appIds": [ "https://apps.apple.com/us/app/whatsapp-messenger/id310633997" ], "countries": [ "us" ], "sortBy": "mostrecent", "maxReviews": 500 } ``` # 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 = { "appIds": [ "https://apps.apple.com/us/app/whatsapp-messenger/id310633997" ], "countries": [ "us" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapesmith/apple-app-store-reviews-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 = { "appIds": ["https://apps.apple.com/us/app/whatsapp-messenger/id310633997"], "countries": ["us"], } # Run the Actor and wait for it to finish run = client.actor("scrapesmith/apple-app-store-reviews-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 '{ "appIds": [ "https://apps.apple.com/us/app/whatsapp-messenger/id310633997" ], "countries": [ "us" ] }' | apify call scrapesmith/apple-app-store-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapesmith/apple-app-store-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Apple App Store Reviews Scraper", "description": "Extract Apple App Store reviews at scale. Get star ratings, review text, author names, helpful votes, app versions, and full app metadata for any iOS app. 50+ countries, date filtering, two sort modes. No browser, no proxy, no API key needed.", "version": "0.0", "x-build-id": "Jz8RMfPJMOVFcRrVy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapesmith~apple-app-store-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapesmith-apple-app-store-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapesmith~apple-app-store-reviews-scraper/runs": { "post": { "operationId": "runs-sync-scrapesmith-apple-app-store-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapesmith~apple-app-store-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-scrapesmith-apple-app-store-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "appIds" ], "properties": { "appIds": { "title": "App Store IDs or URLs", "type": "array", "description": "App Store numeric IDs or URLs. ID extracted automatically from URLs.", "items": { "type": "string" } }, "countries": { "title": "Countries", "type": "array", "description": "App Store country codes (e.g. us, gb, de, jp).", "default": [ "us" ], "items": { "type": "string" } }, "sortBy": { "title": "Sort reviews by", "enum": [ "mostrecent", "mosthelpful" ], "type": "string", "description": "Review sort order.", "default": "mostrecent" }, "maxReviews": { "title": "Max reviews per app per country", "minimum": 1, "maximum": 500, "type": "integer", "description": "Max reviews per app per country. Apple exposes at most 500 (10 pages x 50).", "default": 500 }, "sinceDate": { "title": "Reviews since date", "type": "string", "description": "Only include reviews on or after this date. Format: YYYY-MM-DD" } } }, "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 } } } } } } } } } } ```