# Reddit Lead & Trend Monitor (`techionik9993/reddit-lead-trend-monitor`) Actor Find Reddit posts from public RSS search and subreddit feeds, score buyer-intent keywords, and monitor new conversations for lead generation and trend tracking. - **URL**: https://apify.com/techionik9993/reddit-lead-trend-monitor.md - **Developed by:** [Techionik](https://apify.com/techionik9993) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 1,000 reddit post rows This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 Lead & Trend Monitor ![Reddit Lead & Trend Monitor hero](./assets/hero.svg) Find Reddit conversations from public RSS feeds and monitor new posts for lead generation, niche research, brand tracking, and trend discovery. ![Reddit Lead & Trend Monitor icon](./assets/icon.svg) ### What You Get - Reddit post title - Post URL - Subreddit - Author when available - Published timestamp - Source query or subreddit - Relevance score and matched query terms - Intent score - Matched intent keywords - Optional RSS content summary - Optional monitoring change rows ### Why This Actor Is Premium - It uses public Reddit RSS surfaces that are lighter and more reliable than browser scraping. - It is built for lead and trend monitoring, not just generic post export. - It scores buyer-intent phrases such as `need`, `looking for`, `recommend`, `alternative`, and `hire`. - It filters noisy Reddit search results with query-term relevance scoring. - It supports keyword searches and subreddit monitoring in one run. - It stores monitoring snapshots outside the paid dataset. - It keeps billing predictable with a strict `Max results` cap. ### Quick Start 1. Add buyer-intent searches such as `shopify automation`, `need wordpress developer`, or `hubspot alternative`. 2. Add subreddits such as `shopify`, `smallbusiness`, `SaaS`, or `entrepreneur`. 3. Keep `Sort` set to `Newest` for monitoring. 4. Keep `Minimum relevance score` at 1 for clean output, or set it to 0 for broad research. 5. Set `Minimum intent score` to 1 when you want stronger lead-generation output. 6. Set `Max results` to 100 or higher for stronger lead batches. 7. Turn on monitoring when running the Actor on a schedule. ### Result Limits And Billing `Max results` is a run-level cap, not a guaranteed count. - The Actor never writes more than `Max results`. - The minimum cap is 50 results. - Users are charged only for rows written to the default dataset. - Monitoring snapshots and internal notices are stored in a named key-value store. ### Monitoring Monitoring saves a snapshot in `reddit-lead-trend-monitor-state`. - First monitoring run creates the baseline. - Later runs detect newly found posts. - `Output only new posts` writes only new post events. ### Relevance And Intent Reddit search can be broad. This Actor keeps output cleaner by scoring each search result: - `relevanceScore` counts meaningful query terms found in the post title, content, subreddit, or URL. - `matchedQueryTerms` shows which query terms matched. - `intentScore` counts buyer-intent phrases such as `need`, `looking for`, `recommend`, `alternative`, and `hire`. - `matchedIntentKeywords` shows which intent terms matched. For broad trend research, use `Minimum relevance score: 0` and `Minimum intent score: 0`. For lead generation, use `Minimum relevance score: 1` and `Minimum intent score: 1`. ### Pricing Recommendation Recommended pay-per-event pricing: - Start event: `$0.005` - Reddit post row: `$0.003` per row - Store discounts: down to `$0.0015` per row for higher tiers That positions the Actor around `$3 per 1,000 posts` before discounts, with very low runtime cost and healthy margin. ### Notes - Reddit RSS availability can vary by subreddit, query, and Reddit rate limits. - This Actor does not log in to Reddit and does not access private communities. - Search RSS can include posts from many subreddits; subreddit RSS focuses on one community. # Actor input Schema ## `searchQueries` (type: `array`): Reddit search queries to monitor. Use buyer-intent phrases such as looking for Shopify developer, need automation, agency recommendations, CRM problem, or alternatives to. ## `subreddits` (type: `array`): Optional subreddits to scan via public RSS, without the r/ prefix. Examples: shopify, smallbusiness, entrepreneur, SaaS. ## `sort` (type: `string`): Sort mode for Reddit search RSS. ## `maxResults` (type: `integer`): Maximum post rows to write for the whole run. The minimum is 50 for better lead-monitor economics. ## `includeContent` (type: `boolean`): Include post summary/content from the RSS feed when available. ## `intentKeywords` (type: `array`): Optional keywords used to score buyer intent in title/content. ## `minimumRelevanceScore` (type: `integer`): Minimum number of meaningful query words that must appear in the post title, content, subreddit, or URL for search results. Use 1 for clean lead/trend output, or 0 for broad research. ## `minimumIntentScore` (type: `integer`): Minimum number of intent keywords that must appear in the post title/content. Use 0 for trend monitoring, 1 or higher for stronger lead generation. ## `monitorChanges` (type: `boolean`): Compare against the previous saved snapshot and detect newly found posts. ## `onlyChanges` (type: `boolean`): When monitoring is enabled, write only newly detected posts to the dataset. ## Actor input object example ```json { "searchQueries": [ "shopify automation", "need wordpress developer", "hubspot alternative" ], "subreddits": [ "shopify", "smallbusiness", "SaaS" ], "sort": "new", "maxResults": 100, "includeContent": true, "intentKeywords": [ "need", "looking for", "hire", "recommend" ], "minimumRelevanceScore": 1, "minimumIntentScore": 0, "monitorChanges": false, "onlyChanges": false } ```` # Actor output Schema ## `results` (type: `string`): Normal runs contain Reddit post rows. When Output only the changes is enabled, rows contain new post events. # 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 = { "searchQueries": [ "shopify automation", "need wordpress developer" ] }; // Run the Actor and wait for it to finish const run = await client.actor("techionik9993/reddit-lead-trend-monitor").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 = { "searchQueries": [ "shopify automation", "need wordpress developer", ] } # Run the Actor and wait for it to finish run = client.actor("techionik9993/reddit-lead-trend-monitor").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 '{ "searchQueries": [ "shopify automation", "need wordpress developer" ] }' | apify call techionik9993/reddit-lead-trend-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=techionik9993/reddit-lead-trend-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Lead & Trend Monitor", "description": "Find Reddit posts from public RSS search and subreddit feeds, score buyer-intent keywords, and monitor new conversations for lead generation and trend tracking.", "version": "0.0", "x-build-id": "HUQam9FXazA7ypwKt" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/techionik9993~reddit-lead-trend-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-techionik9993-reddit-lead-trend-monitor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/techionik9993~reddit-lead-trend-monitor/runs": { "post": { "operationId": "runs-sync-techionik9993-reddit-lead-trend-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/techionik9993~reddit-lead-trend-monitor/run-sync": { "post": { "operationId": "run-sync-techionik9993-reddit-lead-trend-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQueries": { "title": "Search queries", "type": "array", "description": "Reddit search queries to monitor. Use buyer-intent phrases such as looking for Shopify developer, need automation, agency recommendations, CRM problem, or alternatives to.", "default": [], "items": { "type": "string" } }, "subreddits": { "title": "Subreddits", "type": "array", "description": "Optional subreddits to scan via public RSS, without the r/ prefix. Examples: shopify, smallbusiness, entrepreneur, SaaS.", "default": [], "items": { "type": "string" } }, "sort": { "title": "Sort", "enum": [ "new", "relevance", "hot", "top" ], "type": "string", "description": "Sort mode for Reddit search RSS.", "default": "new" }, "maxResults": { "title": "Max results", "minimum": 50, "maximum": 1000, "type": "integer", "description": "Maximum post rows to write for the whole run. The minimum is 50 for better lead-monitor economics.", "default": 100 }, "includeContent": { "title": "Include content", "type": "boolean", "description": "Include post summary/content from the RSS feed when available.", "default": true }, "intentKeywords": { "title": "Intent keywords", "type": "array", "description": "Optional keywords used to score buyer intent in title/content.", "default": [ "need", "looking for", "recommend", "alternative", "hire", "problem", "help" ], "items": { "type": "string" } }, "minimumRelevanceScore": { "title": "Minimum relevance score", "minimum": 0, "maximum": 10, "type": "integer", "description": "Minimum number of meaningful query words that must appear in the post title, content, subreddit, or URL for search results. Use 1 for clean lead/trend output, or 0 for broad research.", "default": 1 }, "minimumIntentScore": { "title": "Minimum intent score", "minimum": 0, "maximum": 10, "type": "integer", "description": "Minimum number of intent keywords that must appear in the post title/content. Use 0 for trend monitoring, 1 or higher for stronger lead generation.", "default": 0 }, "monitorChanges": { "title": "Monitor changes since last run", "type": "boolean", "description": "Compare against the previous saved snapshot and detect newly found posts.", "default": false }, "onlyChanges": { "title": "Output only new posts", "type": "boolean", "description": "When monitoring is enabled, write only newly detected posts to the dataset.", "default": false } } }, "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 } } } } } } } } } } ```