# Social App Review Monitor (`scenic_telescope/a2a-appstore-review-scraper`) Actor Track recent Apple App Store reviews for Instagram, TikTok, YouTube, Facebook, Snapchat, and X. Built for social app monitoring, ASO research, release impact analysis, and competitor review dashboards. - **URL**: https://apify.com/scenic\_telescope/a2a-appstore-review-scraper.md - **Developed by:** [ping](https://apify.com/scenic_telescope) (community) - **Categories:** Developer tools, Automation, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $0.09 / 1,000 reviews 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 ## Social App Review Monitor Monitor recent Apple App Store reviews for major social apps without wiring up a custom scraper for every competitor. This Actor extracts structured review data for Instagram, TikTok, YouTube, Facebook, Snapchat, and X, then saves it as clean JSON/CSV-ready records for dashboards, ASO research, sentiment analysis, and release monitoring. Use it when you need a fast, bounded review feed for social app intelligence, not a universal App Store crawler. ### Proof artifact Use the latest sample report when buyers ask what the Actor produces: `../../reports/social-app-review-monitor-proof-2026-06-17.md` The report uses `targetId=all`, `countries=["us"]`, and `maxItems=120` to show how a balanced social app review snapshot can become a weekly complaint and rating brief. ### What you can do - Track fresh reviews for the largest social apps in the US App Store. - Compare complaints and praise across Instagram, TikTok, YouTube, Facebook, Snapchat, and X. - Watch review sentiment after product releases, policy changes, or outages. - Feed review titles, text, ratings, dates, versions, countries, and app IDs into BI dashboards, notebooks, or AI agents. - Schedule recurring runs and export results from Apify as JSON, CSV, Excel, or via API. ### Best fit - Product teams watching competitor reviews. - ASO and growth teams mining review language for keywords and objections. - Agencies building weekly social app market reports. - Researchers and agent builders that need predictable public review data. - Developers who want a safe fixed-target input instead of arbitrary URL scraping. ### Current target apps The Actor supports a fixed allowlist: - Instagram - TikTok - YouTube - Facebook - Snapchat - X Choose one target for a focused run, or choose `all` to collect a balanced competitor snapshot across every configured social app. ### Quick start 1. Click **Try for free**. 2. Keep `targetId` set to `all` for a social app review snapshot, or select one app. 3. Keep `countries` as `["us"]`, or add more App Store country codes. 4. Set `maxItems` to the maximum number of review records you want. 5. Start the run and export the dataset from Apify Storage. Example input: ```json { "targetId": "all", "countries": ["us"], "maxItems": 300 } ```` For scheduled monitoring, set `until` to the newest review date already stored in your own system so each run only returns newer reviews. ### Pricing This Actor charges only when a review record is successfully written to the default dataset. - Event name: `review` - Price: `$0.00009` per review - Equivalent: `$0.09 / 1,000 reviews` Example: collecting 300 reviews costs up to `$0.027` before any platform usage costs. If fewer reviews are available, you pay only for the records written. ### Output Each dataset item uses a compact review schema compatible with common App Store review analysis workflows: ```json { "parentId": "10954854441", "id": "10954854441", "date": "2024-02-18T19:48:09-07:00", "userName": "reviewer", "userUrl": "https://itunes.apple.com/us/reviews/id123", "version": "1.0.0", "score": 5, "title": "Great app", "text": "Useful and polished.", "url": "https://itunes.apple.com/us/review?id=123456&type=Purple%20Software", "country": "US", "appId": "123456" } ``` Useful fields by workflow: | Workflow | Fields | | --- | --- | | ASO keyword research | `title`, `text`, `score`, `country` | | Release impact monitoring | `version`, `date`, `score`, `text` | | Competitor benchmarking | `appId`, `score`, `title`, `text`, `country` | | Sentiment or NLP pipelines | `title`, `text`, `score`, `date` | | Review dashboards | `date`, `score`, `version`, `country`, `appId` | ### How it is different Broad App Store review scrapers accept arbitrary app IDs or URLs. This Actor is purposefully narrower: it focuses on major social apps and rejects arbitrary targets, URLs, cookies, authorization headers, proxy settings, and custom network code. That narrower scope is useful when you want a repeatable social app monitoring job with predictable inputs, pricing, and output fields. ### Limitations - This is not a universal App Store scraper. - Only configured target apps are supported. - Results depend on the public Apple App Store review RSS feeds available for each selected country. - Some countries or apps may return fewer reviews than requested. ### Security This Actor follows the shared workspace security policy in `../../SECURITY.md`. Public input is limited to schema fields, runtime validation rejects unknown and dangerous JSON keys, and the `review` event is charged only after a review record is successfully written to the dataset. ### Local commands ```bash npm test npm start ``` For local pay-per-event testing: ```bash ACTOR_TEST_PAY_PER_EVENT=true ACTOR_USE_CHARGING_LOG_DATASET=true npm start ``` # Actor input Schema ## `targetId` (type: `string`): Choose one social app or all configured apps for a quick competitor review snapshot. ## `countries` (type: `array`): App Store country codes to monitor, such as us, gb, ca, au, or de. ## `maxItems` (type: `integer`): Maximum review records to return across the selected apps and countries. You are charged only for reviews written to the dataset. ## `until` (type: `string`): Optional date cutoff for scheduled monitoring. Reviews at or older than this date are skipped. ## Actor input object example ```json { "targetId": "all", "countries": [ "us" ], "maxItems": 300 } ``` # 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 = { "countries": [ "us" ], "maxItems": 300 }; // Run the Actor and wait for it to finish const run = await client.actor("scenic_telescope/a2a-appstore-review-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 = { "countries": ["us"], "maxItems": 300, } # Run the Actor and wait for it to finish run = client.actor("scenic_telescope/a2a-appstore-review-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 '{ "countries": [ "us" ], "maxItems": 300 }' | apify call scenic_telescope/a2a-appstore-review-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scenic_telescope/a2a-appstore-review-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Social App Review Monitor", "description": "Track recent Apple App Store reviews for Instagram, TikTok, YouTube, Facebook, Snapchat, and X. Built for social app monitoring, ASO research, release impact analysis, and competitor review dashboards.", "version": "0.1", "x-build-id": "MLuRCcUOwwujbqhP3" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scenic_telescope~a2a-appstore-review-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scenic_telescope-a2a-appstore-review-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scenic_telescope~a2a-appstore-review-scraper/runs": { "post": { "operationId": "runs-sync-scenic_telescope-a2a-appstore-review-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scenic_telescope~a2a-appstore-review-scraper/run-sync": { "post": { "operationId": "run-sync-scenic_telescope-a2a-appstore-review-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "countries", "maxItems" ], "properties": { "targetId": { "title": "Target app", "enum": [ "all", "instagram", "tiktok", "youtube", "facebook", "snapchat", "x" ], "type": "string", "description": "Choose one social app or all configured apps for a quick competitor review snapshot.", "default": "all" }, "countries": { "title": "Countries", "minItems": 1, "maxItems": 10, "type": "array", "description": "App Store country codes to monitor, such as us, gb, ca, au, or de.", "items": { "type": "string" } }, "maxItems": { "title": "Maximum reviews", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum review records to return across the selected apps and countries. You are charged only for reviews written to the dataset.", "default": 300 }, "until": { "title": "Only reviews newer than", "type": "string", "description": "Optional date cutoff for scheduled monitoring. Reviews at or older than this date are skipped." } } }, "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 } } } } } } } } } } ```