# Apify Store Opportunity Radar (`nectared_screen/apify-store-opportunity-radar`) Actor Find underserved Apify Store opportunities by comparing search demand signals, competition, run counts, and top Actor metadata. - **URL**: https://apify.com/nectared\_screen/apify-store-opportunity-radar.md - **Developed by:** [jaehan byun](https://apify.com/nectared_screen) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Apify Store Opportunity Radar Find underserved Apify Store niches by querying the Store API and scoring demand, competition, pricing, and quality signals. ### What it does This Actor helps Apify builders decide what to build next. It searches Apify Store for each query you provide, then returns a scored dataset of competing Actors with signals such as recent users, run volume, pricing model, reviews, rating, agentic-payment eligibility, and a short opportunity note. It is designed for early product research, not revenue forecasting. Use it to compare niches, spot weak competitors, and choose where to do deeper manual validation. ### Input - `queries`: Store search phrases such as `saas pricing`, `website change`, or `apify store`. - `maxResultsPerQuery`: Number of results to evaluate per query. - `minUsers30Days`: Threshold used to flag low-demand niches. Example: ```json { "queries": ["saas pricing", "website change", "apify store"], "maxResultsPerQuery": 10, "minUsers30Days": 3 } ```` ### Output Each dataset item contains the Actor identity, usage signals, pricing model, review quality, an opportunity score, and short notes explaining the score. Important fields: - `opportunityScore`: 0-100 score combining demand, paid-market signal, review gap, competition gap, and reliability penalty. - `users30Days`: Recent usage signal from Apify Store. - `runs30Days`: Recent public run volume. - `pricingModel`: Whether competitors already use paid pricing. - `notes`: Human-readable reasons behind the score. Example output item: ```json { "query": "saas pricing", "title": "SaaS Pricing & Feature Tracker", "actorName": "constructive_calm/saas-pricing-tracker", "pricingModel": "PAY_PER_EVENT", "users30Days": 3, "runs30Days": 34, "opportunityScore": 71, "notes": [ "paid model exists in this niche", "few reviews: quality gap may be available" ] } ``` ### Intended use Use this as a research tool before building new Actors. It does not scrape private data, log in to websites, or bypass access controls. ### Limitations - Search relevance depends on Apify Store search results. - A high score means "worth investigating", not "guaranteed revenue". - Low recent usage can mean either an underserved niche or weak demand; validate manually before building. # Actor input Schema ## `queries` (type: `array`): Apify Store search phrases to evaluate. ## `maxResultsPerQuery` (type: `integer`): Number of Store results to score per query. ## `minUsers30Days` (type: `integer`): Flag niches below this user count as low-demand. ## Actor input object example ```json { "queries": [ "saas pricing", "website change", "apify store", "docs changelog" ], "maxResultsPerQuery": 10, "minUsers30Days": 3 } ``` # 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("nectared_screen/apify-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("nectared_screen/apify-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 nectared_screen/apify-store-opportunity-radar --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nectared_screen/apify-store-opportunity-radar", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Apify Store Opportunity Radar", "description": "Find underserved Apify Store opportunities by comparing search demand signals, competition, run counts, and top Actor metadata.", "version": "0.1", "x-build-id": "u5fsNeO626vDM8pcQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nectared_screen~apify-store-opportunity-radar/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nectared_screen-apify-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/nectared_screen~apify-store-opportunity-radar/runs": { "post": { "operationId": "runs-sync-nectared_screen-apify-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/nectared_screen~apify-store-opportunity-radar/run-sync": { "post": { "operationId": "run-sync-nectared_screen-apify-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", "required": [ "queries" ], "properties": { "queries": { "title": "Search queries", "type": "array", "description": "Apify Store search phrases to evaluate.", "default": [ "saas pricing", "website change", "apify store", "docs changelog" ], "items": { "type": "string" } }, "maxResultsPerQuery": { "title": "Max results per query", "minimum": 1, "maximum": 50, "type": "integer", "description": "Number of Store results to score per query.", "default": 10 }, "minUsers30Days": { "title": "Minimum 30-day users", "minimum": 0, "maximum": 1000, "type": "integer", "description": "Flag niches below this user count as low-demand.", "default": 3 } } }, "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 } } } } } } } } } } ```