# App Store Reviews Analyzer (`salem5077/app-reviews-analyzer`) Actor Turn hundreds of App Store reviews into a clear report: satisfaction, top praises & complaints, aspect ratings, most-requested features, competitor comparison, recommendations, and a PDF. - **URL**: https://apify.com/salem5077/app-reviews-analyzer.md - **Developed by:** [ReviewLens](https://apify.com/salem5077) (community) - **Categories:** AI, Developer tools, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $50.00 / 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 ## App Store Reviews Analyzer 📱 Stop reading hundreds of app reviews one by one. Type an app's name and get a clear, instant report about what users love, what they hate, and what they're asking for. ### What you get For every app you analyze, this tool produces: - 📝 **Smart summary** — a clear, human-readable paragraph summarizing the app at a glance - 🎯 **Aspect ratings** — separate scores for performance & stability, ease of use & design, features, ads & pricing, customer support, and updates - 💡 **Most-requested features** — the features users keep asking for, auto-detected from review text - 🧠 **Text sentiment** — sentiment read from the actual words of reviews (not just stars), catching nuance and sarcasm - ⭐ **Rating & satisfaction score** — what % of users are happy - 📈 **Rating distribution & monthly trend** — how ratings break down and how they're moving over time - 👍 **Top praises** / 👎 **Top complaints** — what users mention most - 💬 **Highlight quotes** — representative positive and negative reviews - 🧭 **Actionable recommendations** — a prioritized to-do list of what to fix first - 🏆 **Competitor comparison** — analyze your app + competitors side by side - 📄 **Printable PDF report** — a polished, shareable PDF (download link in `pdfReportUrl`) Perfect for **app developers, product managers, and ASO/marketing teams** who want to understand user feedback in seconds. ### How to use - `appNames`: one or more app names, e.g. `Spotify`. Add 2+ to get a competitor comparison. - `country`: App Store country code (e.g. `us`, `gb`, `de`). - `maxReviews`: how many recent reviews to analyze per app (default 100). ### Example input ```json { "appNames": ["Spotify", "Apple Music"], "country": "us", "maxReviews": 100 } ```` ### Notes - Review data is fetched through a trusted App Store reviews scraper, then analyzed by this tool. - Sentiment is based on star ratings (language-independent), with extra text sentiment for English reviews. Themes are detected with multilingual support. # Actor input Schema ## `appNames` (type: `array`): Name(s) of the App Store app(s) to analyze, e.g. 'Spotify'. Add 2 or more to get a competitor comparison. ## `country` (type: `string`): Two-letter country code of the App Store to read reviews from (e.g. 'us', 'gb', 'de'). ## `maxReviews` (type: `integer`): How many recent reviews to pull and analyze for each app. More reviews = deeper analysis but higher cost. ## `compareMode` (type: `boolean`): When you analyze 2 or more apps, also produce a side-by-side comparison report (ranking, who wins each aspect, shared complaints, and a verdict). ## `generatePdf` (type: `boolean`): Also create a polished, printable PDF report for each app (with charts, aspect ratings, requested features, and recommendations). A download link is added to each result as 'pdfReportUrl'. ## Actor input object example ```json { "appNames": [ "Spotify" ], "country": "us", "maxReviews": 100, "compareMode": true, "generatePdf": true } ``` # Actor output Schema ## `analysis` (type: `string`): The full analysis report for each app, plus a competitor comparison when 2 or more are analyzed. ## `pdfReports` (type: `string`): Printable PDF analysis report for each analyzed app. # 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 = { "appNames": [ "Spotify" ], "maxReviews": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("salem5077/app-reviews-analyzer").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 = { "appNames": ["Spotify"], "maxReviews": 100, } # Run the Actor and wait for it to finish run = client.actor("salem5077/app-reviews-analyzer").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 '{ "appNames": [ "Spotify" ], "maxReviews": 100 }' | apify call salem5077/app-reviews-analyzer --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=salem5077/app-reviews-analyzer", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "App Store Reviews Analyzer", "description": "Turn hundreds of App Store reviews into a clear report: satisfaction, top praises & complaints, aspect ratings, most-requested features, competitor comparison, recommendations, and a PDF.", "version": "0.1", "x-build-id": "6pezBt9DEgmxzVumr" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/salem5077~app-reviews-analyzer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-salem5077-app-reviews-analyzer", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/salem5077~app-reviews-analyzer/runs": { "post": { "operationId": "runs-sync-salem5077-app-reviews-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/salem5077~app-reviews-analyzer/run-sync": { "post": { "operationId": "run-sync-salem5077-app-reviews-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "appNames": { "title": "App name(s)", "type": "array", "description": "Name(s) of the App Store app(s) to analyze, e.g. 'Spotify'. Add 2 or more to get a competitor comparison.", "items": { "type": "string" } }, "country": { "title": "App Store country", "type": "string", "description": "Two-letter country code of the App Store to read reviews from (e.g. 'us', 'gb', 'de').", "default": "us" }, "maxReviews": { "title": "Reviews to analyze per app", "minimum": 10, "maximum": 5000, "type": "integer", "description": "How many recent reviews to pull and analyze for each app. More reviews = deeper analysis but higher cost.", "default": 100 }, "compareMode": { "title": "Competitor comparison", "type": "boolean", "description": "When you analyze 2 or more apps, also produce a side-by-side comparison report (ranking, who wins each aspect, shared complaints, and a verdict).", "default": true }, "generatePdf": { "title": "Generate PDF report", "type": "boolean", "description": "Also create a polished, printable PDF report for each app (with charts, aspect ratings, requested features, and recommendations). A download link is added to each result as 'pdfReportUrl'.", "default": true } } }, "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 } } } } } } } } } } ```