# Reddit Scraper for Pain Points & Buying Signals (`happyfhantum/reddit-opportunity-scraper---pain-points-buying-intent`) Actor Search Reddit posts and comments for complaints, recommendations, and buying-intent signals. - **URL**: https://apify.com/happyfhantum/reddit-opportunity-scraper---pain-points-buying-intent.md - **Developed by:** [Kelsey Todd](https://apify.com/happyfhantum) (community) - **Categories:** Social media, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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 ## Reddit Scraper for Pain Points & Buying Signals Search Reddit for complaints, recommendation requests, and buying-signal conversations without manually digging through threads. ### What it does - Searches Reddit sitewide or inside specific subreddits. - Pulls post metadata plus the first useful comment for extra context. - Tags patterns like complaints, recommendation requests, comparisons, pricing signals, integration needs, and migration signals. - Scores each post for likely buying intent using tags, score, and discussion volume. - Produces flat output that is easy to export into CSV, Sheets, Airtable, or lead-research workflows. - Uses Apify Proxy by default for cloud runs where Reddit blocks plain datacenter IPs. ### Best fit - product marketers looking for pain-point language - founders validating demand and switch intent - agencies building community listening workflows - sales teams looking for public buying-signal conversations # Actor input Schema ## `searchTerms` (type: `array`): Keywords or phrases to search for on Reddit. ## `subreddits` (type: `array`): Optional subreddit names like analytics, excel, or businessintelligence. Leave empty for sitewide search. ## `maxPostsPerQuery` (type: `integer`): Cap how many posts to return for each search term or subreddit-term pair. ## `includeTopComments` (type: `boolean`): Fetch the first high-signal comment for extra context and intent tagging. ## `sort` (type: `string`): Reddit search sort mode. ## `timeFilter` (type: `string`): Reddit time window for the search. ## `requestTimeoutSecs` (type: `integer`): Maximum time to wait for a Reddit request before skipping it. ## `useApifyProxy` (type: `boolean`): Route Reddit requests through Apify Proxy. Recommended for cloud runs where Reddit blocks datacenter IPs. ## Actor input object example ```json { "searchTerms": [ "power bi alternative" ], "maxPostsPerQuery": 25, "includeTopComments": true, "sort": "relevance", "timeFilter": "year", "requestTimeoutSecs": 30, "useApifyProxy": true } ```` # 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 = { "searchTerms": [ "power bi alternative" ] }; // Run the Actor and wait for it to finish const run = await client.actor("happyfhantum/reddit-opportunity-scraper---pain-points-buying-intent").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 = { "searchTerms": ["power bi alternative"] } # Run the Actor and wait for it to finish run = client.actor("happyfhantum/reddit-opportunity-scraper---pain-points-buying-intent").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 '{ "searchTerms": [ "power bi alternative" ] }' | apify call happyfhantum/reddit-opportunity-scraper---pain-points-buying-intent --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=happyfhantum/reddit-opportunity-scraper---pain-points-buying-intent", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Scraper for Pain Points & Buying Signals", "description": "Search Reddit posts and comments for complaints, recommendations, and buying-intent signals.", "version": "0.1", "x-build-id": "ZBzWbhbMZpZvRMdvX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/happyfhantum~reddit-opportunity-scraper---pain-points-buying-intent/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-happyfhantum-reddit-opportunity-scraper---pain-points-buying-intent", "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/happyfhantum~reddit-opportunity-scraper---pain-points-buying-intent/runs": { "post": { "operationId": "runs-sync-happyfhantum-reddit-opportunity-scraper---pain-points-buying-intent", "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/happyfhantum~reddit-opportunity-scraper---pain-points-buying-intent/run-sync": { "post": { "operationId": "run-sync-happyfhantum-reddit-opportunity-scraper---pain-points-buying-intent", "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": "Search terms", "type": "array", "description": "Keywords or phrases to search for on Reddit.", "items": { "type": "string" } }, "subreddits": { "title": "Subreddits", "type": "array", "description": "Optional subreddit names like analytics, excel, or businessintelligence. Leave empty for sitewide search.", "items": { "type": "string" } }, "maxPostsPerQuery": { "title": "Max posts per query", "minimum": 1, "maximum": 100, "type": "integer", "description": "Cap how many posts to return for each search term or subreddit-term pair.", "default": 25 }, "includeTopComments": { "title": "Include top comment", "type": "boolean", "description": "Fetch the first high-signal comment for extra context and intent tagging.", "default": true }, "sort": { "title": "Sort", "enum": [ "relevance", "top", "new", "comments" ], "type": "string", "description": "Reddit search sort mode.", "default": "relevance" }, "timeFilter": { "title": "Time filter", "enum": [ "hour", "day", "week", "month", "year", "all" ], "type": "string", "description": "Reddit time window for the search.", "default": "year" }, "requestTimeoutSecs": { "title": "Request timeout (seconds)", "minimum": 5, "maximum": 60, "type": "integer", "description": "Maximum time to wait for a Reddit request before skipping it.", "default": 30 }, "useApifyProxy": { "title": "Use Apify Proxy", "type": "boolean", "description": "Route Reddit requests through Apify Proxy. Recommended for cloud runs where Reddit blocks datacenter IPs.", "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 } } } } } } } } } } ```