# Scrape Reddit for Business Ideas (`wombat951/reddit-pain-point-ai`) Actor 🚀 Automatically scan Reddit for user complaints and unmet needs. This AI-powered Actor extracts real human frustrations in your niche and uses Gemini to analyze them, generating a report with the Top 3 Recurring Pain Points and specific Micro-SaaS ideas to solve them. Stop guessing, start building! - **URL**: https://apify.com/wombat951/reddit-pain-point-ai.md - **Developed by:** [Nikita Kovalenko](https://apify.com/wombat951) (community) - **Categories:** Automation, AI, Social media - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $500.00 / 1,000 report generateds 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 ## 🚀 Reddit Pain Point AI #### Stop Guessing. Build What People Actually Want. **Reddit Pain Point AI** is a powerful market research tool that scans Reddit communities to find real user frustrations and transforms them into actionable business opportunities using **Google Gemini AI**. --- ### ✨ Why use this Actor? Most startups fail because they build solutions for problems that don't exist. This Actor helps you: * **Find Profitable Niches:** Discover what people are struggling with right now. * **Generate Product Ideas:** Get 3 specific Micro-SaaS concepts based on real data. * **Save Days of Research:** What takes a human 10 hours, this AI does in 30 seconds. --- ### 🛠 How It Works 1. **Choose a Subreddit:** Enter any community (e.g., `r/realestate` or `r/SaaS`). 2. **Define Keywords:** Use terms like *"hate"*, *"how to"*, *"is there a tool"*. 3. **Get AI Insights:** The Actor scrapes high-engagement posts and uses **Gemini 3.1 Flash** to generate a structured PMF report. --- ### 📥 Input Requirements * **Subreddit:** The target community name. * **Search Keywords:** Phrases that signal pain points. * **Gemini API Key:** Your personal key from Google AI Studio (optional/required based on your setup). --- ### 📦 Output You get a beautifully formatted **AI Analysis Report** located in the **Output** tab (Dataset) or **Key-Value Store**, including: 1. **Top 3 Recurring Pain Points** found in the discussions. 2. **3 Micro-SaaS Ideas** with suggested features. 3. **Raw Data** of all analyzed posts for your own records. --- *Built with ❤️ for Indie Hackers and Product Managers.* # Actor input Schema ## `subreddit` (type: `string`): The subreddit to scrape (e.g., 'startup', 'SaaS', 'smallbusiness'). Do not include the 'r/'. ## `searchKeywords` (type: `array`): Pain point keywords to search for (e.g., 'hate', 'frustrated', 'how to'). ## `maxPosts` (type: `integer`): Maximum number of filtered posts (>5 upvotes) to collect and pass to the AI. ## `geminiApiKey` (type: `string`): Your Google Gemini API Key required for generating the Product-Market Fit analysis report. ## `proxyConfiguration` (type: `object`): Select proxies to be used. Reddit aggressively blocks non-residential traffic. RESIDENTIAL proxies are highly recommended. ## Actor input object example ```json { "subreddit": "SaaS", "searchKeywords": [ "hate", "sucks", "struggle", "frustrated expected" ], "maxPosts": 30, "proxyConfiguration": { "useApifyProxy": true } } ```` # Actor output Schema ## `results` (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 = { "subreddit": "SaaS", "searchKeywords": [ "hate", "sucks", "struggle", "frustrated expected" ], "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("wombat951/reddit-pain-point-ai").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 = { "subreddit": "SaaS", "searchKeywords": [ "hate", "sucks", "struggle", "frustrated expected", ], "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("wombat951/reddit-pain-point-ai").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 '{ "subreddit": "SaaS", "searchKeywords": [ "hate", "sucks", "struggle", "frustrated expected" ], "proxyConfiguration": { "useApifyProxy": true } }' | apify call wombat951/reddit-pain-point-ai --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=wombat951/reddit-pain-point-ai", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Scrape Reddit for Business Ideas", "description": "🚀 Automatically scan Reddit for user complaints and unmet needs. This AI-powered Actor extracts real human frustrations in your niche and uses Gemini to analyze them, generating a report with the Top 3 Recurring Pain Points and specific Micro-SaaS ideas to solve them. Stop guessing, start building!", "version": "0.0", "x-build-id": "ArFqCdfedHNZlb2QL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/wombat951~reddit-pain-point-ai/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-wombat951-reddit-pain-point-ai", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/wombat951~reddit-pain-point-ai/runs": { "post": { "operationId": "runs-sync-wombat951-reddit-pain-point-ai", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/wombat951~reddit-pain-point-ai/run-sync": { "post": { "operationId": "run-sync-wombat951-reddit-pain-point-ai", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "subreddit", "searchKeywords", "geminiApiKey" ], "properties": { "subreddit": { "title": "Subreddit", "type": "string", "description": "The subreddit to scrape (e.g., 'startup', 'SaaS', 'smallbusiness'). Do not include the 'r/'." }, "searchKeywords": { "title": "Search Keywords", "type": "array", "description": "Pain point keywords to search for (e.g., 'hate', 'frustrated', 'how to').", "items": { "type": "string" } }, "maxPosts": { "title": "Max Posts limit", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of filtered posts (>5 upvotes) to collect and pass to the AI.", "default": 30 }, "geminiApiKey": { "title": "Google Gemini API Key", "type": "string", "description": "Your Google Gemini API Key required for generating the Product-Market Fit analysis report." }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Select proxies to be used. Reddit aggressively blocks non-residential traffic. RESIDENTIAL proxies are highly recommended." } } }, "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 } } } } } } } } } } ```