# App Store Opportunity Radar (`immortal_crossbill/app-store-opportunity-radar`) Actor Find high-demand App Store competitors with recurring complaints, feature requests, and product gaps. - **URL**: https://apify.com/immortal\_crossbill/app-store-opportunity-radar.md - **Developed by:** [Jam](https://apify.com/immortal_crossbill) (community) - **Categories:** Developer tools, SEO tools, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $10.00 / 1,000 app analyzeds 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 Opportunity Radar Find App Store niches where demand already exists but users are still asking for something better. This Actor searches Apple's public App Store data, reads a bounded set of recent public reviews, and ranks competitors by: - proven demand from lifetime ratings; - recent low-rating share and rating gap; - recurring complaint themes; - explicit feature requests; - recent review velocity; - time since the last app update. It produces one clean row per app, ready for CSV, Google Sheets, an API workflow, or an AI agent. > **Unofficial independent tool:** This Actor is not affiliated with, sponsored > by, or endorsed by Apple. Apple and App Store are trademarks of Apple Inc. ### What makes it useful Raw review scrapers give you thousands of rows to read. This Actor turns those reviews into a shortlist of product opportunities with the evidence attached. It uses deterministic analysis, so there is no LLM key, surprise AI bill, proxy, login, or invented quote. ### Example use cases - An indie developer compares the top habit trackers before building. - An ASO agency finds recurring complaints in a client's keyword category. - A product team watches competitor pain after a major release. - An investor screens a mobile-app niche before deeper research. ### Quick start Run a ten-app market scan with: ```json { "searchTerms": ["habit tracker"], "country": "us", "maxAppsPerSearch": 10, "reviewsPerApp": 100 } ```` Or analyze exact competitors: ```json { "searchTerms": [], "appIds": [ "https://apps.apple.com/us/app/example/id123456789", "987654321" ], "country": "us", "reviewsPerApp": 100 } ``` ### Input Use one or both discovery modes: 1. `searchTerms`: category keywords such as `habit tracker`, `invoice maker`, or `photo cleaner` (up to 20 unique terms per run). 2. `appIds`: exact Apple app IDs or App Store URLs for direct competitor analysis. Up to 200 unique apps can be supplied per run. Set `searchTerms` to `[]` for a direct-only run because the input form starts with an example keyword. Important controls: - `country`: two-letter App Store storefront, default `us`. - `maxAppsPerSearch`: 1-50 apps per keyword. - `reviewsPerApp`: 0-500 recent reviews per app. - `minimumRatings`: removes tiny apps from keyword discovery. - `negativeRatingThreshold`: choose whether 1-2 or 1-3 stars count as negative. ### Output Every dataset row contains: - `analysisCoverage`: `review-intelligence` or `metadata-only`; - `opportunityScore` and `scoreBand`; - App Store metadata and demand indicators; - recent rating and negative-review share; - ranked complaint themes with public review excerpts; - feature-request evidence; - transparent signals explaining the score; - source URLs and analysis timestamp. The `OUTPUT` record contains a run-level market summary with the top opportunities and most common pain points, plus the number of full review analyses and metadata-only results. Example row: ```json { "analysisCoverage": "review-intelligence", "opportunityScore": 68.4, "scoreBand": "test", "appName": "Example App", "totalRatingCount": 28400, "recentReviewCount": 100, "negativeReviewShare": 0.31, "featureRequestCount": 12, "signals": [ "high proven demand", "30%+ of sampled reviews are negative" ], "painPoints": [ { "topic": "pricing-and-subscription", "count": 14 } ] } ``` ### Coverage and billing The Actor tries two public Apple review feeds. When review entries are available, the row is labeled `review-intelligence` and triggers one `app-analyzed` event. At the current price of **$0.01 per event**, a ten-app scan costs at most **$0.10**, with platform usage included. If Apple returns no public review entries, the Actor still returns useful App Store metadata, labels the row `metadata-only`, adds a data warning, and does **not** trigger the paid event. It never interprets an empty feed as proof that users have no complaints. ### How to interpret the score The score is a prioritization tool, not a promise of downloads or revenue. - `strong-test`: strong enough to justify customer interviews, a landing page, or a small prototype. - `test`: collect more evidence before building. - `watch`: weak or insufficient evidence in this run. Always validate distribution, willingness to pay, platform rules, and build cost before committing to a product. ### Data boundaries - Uses public Apple search and customer-review endpoints. - Apple can return fewer reviews than requested. - Review availability differs by country. - No personal enrichment, login, CAPTCHA bypass, or private data. - Deterministic topic rules are explainable but less nuanced than a human review. ### Pricing The current Store price is **$0.01 per `app-analyzed` event**, with platform usage included. Only rows with review intelligence trigger the event; metadata-only fallback rows are returned without that charge. Pricing should change only after observing repeat usage and compute margin. # Actor input Schema ## `searchTerms` (type: `array`): Keywords or product categories to research, such as habit tracker or invoice maker. ## `appIds` (type: `array`): Optional Apple app IDs or full App Store URLs to analyze directly. Set searchTerms to an empty list for a direct-only run. ## `country` (type: `string`): Two-letter storefront country code. ## `maxAppsPerSearch` (type: `integer`): Maximum ranked apps to analyze for every search term. ## `reviewsPerApp` (type: `integer`): Maximum recent reviews used to detect pain points and feature requests. Apple may return fewer. ## `minimumRatings` (type: `integer`): Ignore tiny apps with too little evidence when using search terms. Direct app IDs are never filtered. ## `negativeRatingThreshold` (type: `integer`): Ratings at or below this value count as negative. ## `includeReviewExamples` (type: `boolean`): Include a small number of public review excerpts as evidence for each pain point. ## `maxConcurrency` (type: `integer`): Lower this if Apple rate-limits a large run. ## `requestTimeoutSecs` (type: `integer`): Timeout for each public Apple API request. ## Actor input object example ```json { "searchTerms": [ "habit tracker" ], "appIds": [], "country": "us", "maxAppsPerSearch": 10, "reviewsPerApp": 100, "minimumRatings": 100, "negativeRatingThreshold": 2, "includeReviewExamples": true, "maxConcurrency": 4, "requestTimeoutSecs": 20 } ``` # Actor output Schema ## `rankedOpportunities` (type: `string`): No description ## `marketSummary` (type: `string`): No description # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("immortal_crossbill/app-store-opportunity-radar").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 = {} # Run the Actor and wait for it to finish run = client.actor("immortal_crossbill/app-store-opportunity-radar").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 '{}' | apify call immortal_crossbill/app-store-opportunity-radar --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=immortal_crossbill/app-store-opportunity-radar", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "App Store Opportunity Radar", "description": "Find high-demand App Store competitors with recurring complaints, feature requests, and product gaps.", "version": "0.1", "x-build-id": "fIDEzCdskRiimEOdZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/immortal_crossbill~app-store-opportunity-radar/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-immortal_crossbill-app-store-opportunity-radar", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/immortal_crossbill~app-store-opportunity-radar/runs": { "post": { "operationId": "runs-sync-immortal_crossbill-app-store-opportunity-radar", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/immortal_crossbill~app-store-opportunity-radar/run-sync": { "post": { "operationId": "run-sync-immortal_crossbill-app-store-opportunity-radar", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchTerms": { "title": "App Store search terms", "maxItems": 20, "type": "array", "description": "Keywords or product categories to research, such as habit tracker or invoice maker.", "default": [ "habit tracker" ], "items": { "type": "string" } }, "appIds": { "title": "Specific app IDs or App Store URLs", "maxItems": 200, "type": "array", "description": "Optional Apple app IDs or full App Store URLs to analyze directly. Set searchTerms to an empty list for a direct-only run.", "default": [], "items": { "type": "string" } }, "country": { "title": "App Store country", "minLength": 2, "maxLength": 2, "type": "string", "description": "Two-letter storefront country code.", "default": "us" }, "maxAppsPerSearch": { "title": "Apps per search term", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum ranked apps to analyze for every search term.", "default": 10 }, "reviewsPerApp": { "title": "Recent reviews per app", "minimum": 0, "maximum": 500, "type": "integer", "description": "Maximum recent reviews used to detect pain points and feature requests. Apple may return fewer.", "default": 100 }, "minimumRatings": { "title": "Minimum lifetime rating count", "minimum": 0, "maximum": 1000000000, "type": "integer", "description": "Ignore tiny apps with too little evidence when using search terms. Direct app IDs are never filtered.", "default": 100 }, "negativeRatingThreshold": { "title": "Negative review threshold", "minimum": 1, "maximum": 3, "type": "integer", "description": "Ratings at or below this value count as negative.", "default": 2 }, "includeReviewExamples": { "title": "Include review examples", "type": "boolean", "description": "Include a small number of public review excerpts as evidence for each pain point.", "default": true }, "maxConcurrency": { "title": "Concurrent app analyses", "minimum": 1, "maximum": 10, "type": "integer", "description": "Lower this if Apple rate-limits a large run.", "default": 4 }, "requestTimeoutSecs": { "title": "Request timeout", "minimum": 5, "maximum": 60, "type": "integer", "description": "Timeout for each public Apple API request.", "default": 20 } } }, "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 } } } } } } } } } } ```