# Reddit Keyword Monitor – Brand & Lead Generation (`conceivable_extension/reddit-keyword-monitor`) Actor Monitors Reddit subreddits for keyword mentions, classifies sentiment, scores engagement velocity, and delivers only new alerts since the last run. Affordable GummySearch replacement at $0.01/alert. Works with n8n, Make, and Slack for brand monitoring and lead generation. - **URL**: https://apify.com/conceivable\_extension/reddit-keyword-monitor.md - **Developed by:** [joseph fadero](https://apify.com/conceivable_extension) (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 from $2.00 / 1,000 matching reddit posts 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 Keyword Monitor – Brand & Lead Generation The affordable GummySearch replacement (shut down Dec 2025). Monitor Reddit for keyword mentions, score engagement velocity, classify sentiment, and push only **new** alerts since the last run — all at £0.01 per alert. ### Features - **Multi-watchlist monitoring** — group keywords + subreddits into named watchlists (brand, competitors, leads) - **New-only deduplication** — cross-run KV Store tracks seen posts and comments so you never see duplicates - **Sentiment classification** — keyword-based positive/neutral/negative labelling, no AI API needed - **Engagement velocity** — viral/high/normal/low scoring based on upvotes and comments per hour - **Comment search** — optionally scan post comments for keyword matches, not just titles/bodies - **Author quality filter** — skip low-karma accounts to reduce bot/spam noise ### Inputs | Field | Default | Description | |-------|---------|-------------| | `watchlists` | required | Array of `{name, keywords[], subreddits[], searchComments?}` objects | | `scanDepth` | `recent_7d` | `recent_24h`, `recent_7d`, or `recent_30d` | | `minKarmaFilter` | 50 | Skip authors with less than this total karma | | `minUpvotesFilter` | 0 | Skip posts with fewer upvotes | | `classifySentiment` | true | Add sentiment label to each alert | | `includeComments` | true | Search comment text as well as posts | | `maxPostsPerSubreddit` | 100 | Max posts scanned per subreddit per keyword per run | ### Output fields Each alert in the dataset includes: `postId`, `isComment`, `isNew`, `title`, `body`, `permalink`, `subreddit`, `upvotes`, `sentiment`, `sentimentScore`, `engagementVelocity`, `matchedWatchlist`, `matchedKeywords`, `contextSnippet`, `authorUsername`, `authorKarma`, `scrapedAt`. ### Pricing (PPE) - `post-scanned` — charged per post examined - `new-alert` — charged per new keyword match delivered ### Automation Works natively with n8n, Make, and Zapier. Schedule daily or weekly runs and push `isNew: true` alerts to Slack, email, or a CRM. ### Related actors - [Podcast Guest Discovery](https://apify.com/conceivable_extension/podcast-guest-discovery) — find podcasts covering the same topics your Reddit watchlists surface - [SERP + AI Visibility Tracker](https://apify.com/conceivable_extension/serp-ai-visibility-tracker) — turn Reddit trend intelligence into a keyword ranking strategy - [Hiring Signal Lead Scraper](https://apify.com/conceivable_extension/hiring-signal-lead-scraper) — find companies discussing hiring pain points on Reddit as warm leads - [Newsletter Intelligence](https://apify.com/conceivable_extension/newsletter-intelligence) — find newsletters covering the same topics your Reddit alerts surface # Actor input Schema ## `watchlists` (type: `array`): Define what to monitor. Each watchlist has a name, keywords array, and subreddits array. Use the JSON editor to configure multiple watchlists. ## `scanDepth` (type: `string`): How far back to search for posts. Longer periods find more but take longer to run. ## `minKarmaFilter` (type: `integer`): Ignore posts from accounts with less than this total karma. Helps filter bots and spam accounts. ## `minUpvotesFilter` (type: `integer`): Ignore posts with fewer upvotes than this threshold. Set to 0 to include all posts regardless of upvotes. ## `classifySentiment` (type: `boolean`): Use keyword-based sentiment classification on each match. Fast, no AI API needed. Adds positive/neutral/negative label to each alert. ## `includeComments` (type: `boolean`): If enabled, searches comment text as well as post titles and bodies. Finds more matches but is slower. ## `maxPostsPerSubreddit` (type: `integer`): Maximum number of posts to scan per subreddit per keyword watchlist per run. ## Actor input object example ```json { "watchlists": [ { "name": "Brand mentions", "keywords": [ "YourBrand", "yourcompany.com" ], "subreddits": [ "r/SaaS", "r/entrepreneur", "r/startups" ], "searchComments": true } ], "scanDepth": "recent_7d", "minKarmaFilter": 50, "minUpvotesFilter": 0, "classifySentiment": true, "includeComments": true, "maxPostsPerSubreddit": 100 } ```` # 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 = { "watchlists": [ { "name": "Brand mentions", "keywords": [ "YourBrand", "yourcompany.com" ], "subreddits": [ "r/SaaS", "r/entrepreneur", "r/startups" ], "searchComments": true } ] }; // Run the Actor and wait for it to finish const run = await client.actor("conceivable_extension/reddit-keyword-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 = { "watchlists": [{ "name": "Brand mentions", "keywords": [ "YourBrand", "yourcompany.com", ], "subreddits": [ "r/SaaS", "r/entrepreneur", "r/startups", ], "searchComments": True, }] } # Run the Actor and wait for it to finish run = client.actor("conceivable_extension/reddit-keyword-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 '{ "watchlists": [ { "name": "Brand mentions", "keywords": [ "YourBrand", "yourcompany.com" ], "subreddits": [ "r/SaaS", "r/entrepreneur", "r/startups" ], "searchComments": true } ] }' | apify call conceivable_extension/reddit-keyword-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=conceivable_extension/reddit-keyword-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Keyword Monitor – Brand & Lead Generation", "description": "Monitors Reddit subreddits for keyword mentions, classifies sentiment, scores engagement velocity, and delivers only new alerts since the last run. Affordable GummySearch replacement at $0.01/alert. Works with n8n, Make, and Slack for brand monitoring and lead generation.", "version": "1.0", "x-build-id": "mejbu3vaacalMOM93" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/conceivable_extension~reddit-keyword-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-conceivable_extension-reddit-keyword-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/conceivable_extension~reddit-keyword-monitor/runs": { "post": { "operationId": "runs-sync-conceivable_extension-reddit-keyword-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/conceivable_extension~reddit-keyword-monitor/run-sync": { "post": { "operationId": "run-sync-conceivable_extension-reddit-keyword-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", "required": [ "watchlists" ], "properties": { "watchlists": { "title": "Keyword Watchlists", "type": "array", "description": "Define what to monitor. Each watchlist has a name, keywords array, and subreddits array. Use the JSON editor to configure multiple watchlists." }, "scanDepth": { "title": "Scan Depth", "enum": [ "recent_24h", "recent_7d", "recent_30d" ], "type": "string", "description": "How far back to search for posts. Longer periods find more but take longer to run.", "default": "recent_7d" }, "minKarmaFilter": { "title": "Minimum Author Karma", "minimum": 0, "type": "integer", "description": "Ignore posts from accounts with less than this total karma. Helps filter bots and spam accounts.", "default": 50 }, "minUpvotesFilter": { "title": "Minimum Post Upvotes", "type": "integer", "description": "Ignore posts with fewer upvotes than this threshold. Set to 0 to include all posts regardless of upvotes.", "default": 0 }, "classifySentiment": { "title": "Classify Sentiment", "type": "boolean", "description": "Use keyword-based sentiment classification on each match. Fast, no AI API needed. Adds positive/neutral/negative label to each alert.", "default": true }, "includeComments": { "title": "Search Post Comments", "type": "boolean", "description": "If enabled, searches comment text as well as post titles and bodies. Finds more matches but is slower.", "default": true }, "maxPostsPerSubreddit": { "title": "Max Posts to Check Per Subreddit", "minimum": 10, "maximum": 500, "type": "integer", "description": "Maximum number of posts to scan per subreddit per keyword watchlist per run.", "default": 100 } } }, "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 } } } } } } } } } } ```