# 📊 Reddit Brand Monitor -- Track Mentions & Sentiment (`nexgendata/reddit-brand-monitor`) Actor Monitor any brand, product, or topic on Reddit. Track mentions with AI sentiment analysis across all subreddits. Brandwatch alternative at 1/100th the cost. Trend tracking, competitive comparison & engagement analytics. - **URL**: https://apify.com/nexgendata/reddit-brand-monitor.md - **Developed by:** [Stephan Corbeil](https://apify.com/nexgendata) (community) - **Categories:** Marketing, AI - **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 Brand Monitor -- Track Mentions, Sentiment & Competitive Intelligence Stop flying blind on Reddit. Every day, thousands of conversations happen about your brand, your competitors, and your industry -- and you're missing them. Reddit Brand Monitor gives you real-time visibility into what people are saying, how they feel about it, and which conversations matter most. All for less than a penny per mention. Whether you're a startup founder tracking product feedback, a marketing team monitoring brand reputation, or an agency running competitive intelligence -- this actor replaces tools that cost $800/month with something that costs $5 per 1,000 mentions. ### Key Features - **Multi-keyword monitoring** -- Track multiple brands, products, or topics in a single run. Compare sentiment across competitors side by side. - **Built-in sentiment analysis** -- Every mention is scored from -1.0 (very negative) to +1.0 (very positive) using an advanced word-list engine with negation detection and intensifier handling. No external API costs. - **Subreddit targeting** -- Search all of Reddit or focus on specific subreddits where your audience lives (r/startups, r/SaaS, r/technology, etc.). - **Comment-level search** -- Go beyond post titles. Enable comment search to find deep mentions buried in discussion threads. - **Tracker analytics mode** -- Get a full analytics dashboard: sentiment trends, mention velocity, top subreddits, competitive comparison, controversial mentions, and auto-generated insights. - **Engagement & reach estimation** -- Each mention includes a reach estimate based on upvotes and comment count, so you can prioritize high-impact conversations. - **Mention context extraction** -- See the exact context around each keyword mention without reading the full post. - **Flexible time ranges** -- Monitor the last hour, day, week, month, year, or all time. Perfect for both real-time alerts and historical analysis. ### Output Example Each mention in the dataset includes these fields: ```json { "keyword": "apify", "subreddit": "webscraping", "postTitle": "Best web scraping platforms in 2026?", "postUrl": "https://www.reddit.com/r/webscraping/comments/abc123/best_web_scraping_platforms_2026/", "author": "dev_enthusiast", "score": 142, "numComments": 87, "created": "2026-04-10T14:32:00+00:00", "selfText": "I've been evaluating different scraping platforms and wanted to share my experience...", "permalink": "/r/webscraping/comments/abc123/best_web_scraping_platforms_2026/", "sentiment": "positive", "sentimentScore": 0.65, "reachEstimate": 719, "mentionContext": "...evaluating platforms and apify stands out for its actor..." } ```` In **tracker mode**, you also get an analytics summary with sentiment breakdown, top subreddits, mention velocity, competitive comparison, and auto-generated insights. ### How to Use 1. **Set your keywords** -- Enter the brand names, product names, or topics you want to monitor. Use multiple keywords to compare competitors. 2. **Choose your scope** -- Optionally restrict to specific subreddits. Select a time range (hour, day, week, month, year, or all). 3. **Pick your output mode** -- Use "raw" for individual mentions or "tracker" for mentions plus an analytics summary dashboard. 4. **Run and export** -- Start the actor and download results as JSON, CSV, or Excel. Schedule daily runs for continuous monitoring. ### Integration Examples #### Python SDK ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run_input = { "keywords": ["your-brand", "competitor-brand"], "subreddits": ["startups", "SaaS"], "timeFilter": "week", "maxResults": 100, "includeSentiment": True, "outputMode": "tracker", "sortBy": "relevance" } run = client.actor("nexgendata/reddit-brand-monitor").call(run_input=run_input) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(f"{item['postTitle']} | {item.get('sentiment', 'N/A')} | Score: {item.get('sentimentScore', 0)}") ``` #### cURL ```bash curl "https://api.apify.com/v2/acts/nexgendata~reddit-brand-monitor/runs" \ -X POST \ -H "Content-Type: application/json" \ -H "Authorization: Bearer YOUR_API_TOKEN" \ -d '{ "keywords": ["your-brand"], "timeFilter": "week", "maxResults": 50, "includeSentiment": true, "outputMode": "raw" }' ``` ### Use Cases #### 1. Brand Reputation Monitoring Track what people are saying about your brand in real time. Get alerted to negative mentions before they become crises. Identify brand advocates who consistently speak positively about you. #### 2. Competitive Intelligence Monitor competitor brands alongside your own. Compare sentiment scores, mention volume, and engagement. Discover which subreddits prefer your competitor and why. #### 3. Product Feedback Mining Find unfiltered product feedback from real users. Identify common complaints, feature requests, and praise. Use sentiment trends to measure the impact of product launches and updates. #### 4. Market Research & Trend Analysis Track industry keywords and emerging topics. Measure mention velocity to spot rising trends before they peak. Understand which communities are driving conversations in your space. #### 5. PR & Crisis Management Detect negative sentiment spikes early. Find controversial mentions with high engagement that need immediate attention. Track sentiment recovery after PR responses. #### 6. Content & SEO Strategy Discover which topics generate the most Reddit engagement in your niche. Find content gaps by analyzing questions people ask. Identify high-traffic subreddits for community marketing. ### FAQ **Q: Does this actor require a Reddit account or API key?** A: No. It uses Reddit's public JSON API which does not require authentication. No setup beyond entering your keywords is needed. **Q: How accurate is the sentiment analysis?** A: The built-in engine uses a curated list of 120+ sentiment words with negation detection and intensifier handling. It achieves good accuracy for English-language content and is suitable for trend analysis and volume-based insights. **Q: How many mentions can I collect per run?** A: Up to 500 per keyword. With multiple keywords, you can collect thousands of mentions in a single run. Reddit's API returns up to 250 results per search query. **Q: Can I schedule this to run automatically?** A: Yes. Use Apify's built-in scheduler to run the actor daily, weekly, or at any interval. Combine with webhooks or integrations to get notified of new mentions. **Q: What is tracker mode?** A: Tracker mode includes everything in raw mode plus an analytics summary. You get sentiment breakdown percentages, mention velocity, top subreddits, competitive comparison between keywords, sentiment trends over time, and auto-generated insights. **Q: Does this work for non-English content?** A: The sentiment analysis is optimized for English. Non-English posts will still be collected with all metadata, but sentiment scores may be less accurate. ### Pricing | Feature | Brandwatch | Brand24 | Reddit Brand Monitor | |---|---|---|---| | Monthly cost | $800/mo | $79/mo | Pay per use | | Cost per 1,000 mentions | ~$8.00 | ~$1.58 | **$5.00** | | Reddit-specific monitoring | Limited | Basic | **Deep Reddit focus** | | Sentiment analysis | Included | Included | **Included** | | Competitive comparison | Included | Limited | **Included** | | Setup required | Onboarding call | Account setup | **None -- run instantly** | | API access | Enterprise only | Paid add-on | **Included** | **Pricing: $0.01 per actor start + $0.005 per mention.** A typical monitoring run of 200 mentions costs about $1.01. No subscriptions, no minimums, no contracts. ### Why Choose This Actor 1. **Purpose-built for Reddit** -- Unlike generic social monitoring tools that treat Reddit as an afterthought, this actor is designed specifically for Reddit's structure, API, and community dynamics. 2. **No API keys or accounts needed** -- Works out of the box with zero configuration beyond entering your keywords. No Reddit developer application, no OAuth setup, no API key management. 3. **Transparent, pay-per-use pricing** -- No monthly subscriptions. Pay only for what you use. A typical brand monitoring run costs less than a cup of coffee. 4. **Full analytics built in** -- Tracker mode gives you the same insights that enterprise tools charge hundreds per month for: sentiment trends, competitive comparison, mention velocity, and auto-generated summaries. *** New to Apify? [Sign up here](https://apify.com/?fpr=2ayu9b) to get started with free credits every month. Run this actor in minutes with no setup required. # Actor input Schema ## `keywords` (type: `array`): Brand names, product names, or topics to monitor on Reddit. Each keyword is searched separately and results are combined. ## `subreddits` (type: `array`): Restrict search to specific subreddits. Leave empty to search all of Reddit. Example: startups, SaaS, technology. ## `timeFilter` (type: `string`): Time range for the search. Controls how far back to look for mentions. ## `maxResults` (type: `integer`): Maximum number of mentions to collect per keyword. Higher values take longer but give more complete data. ## `includeSentiment` (type: `boolean`): Enable built-in sentiment analysis for each mention. Classifies mentions as positive, negative, or neutral with a score from -1.0 to 1.0. ## `includeComments` (type: `boolean`): Also search Reddit comments, not just posts. Finds deeper mentions but increases run time. ## `outputMode` (type: `string`): Raw mode outputs individual mentions. Tracker mode adds analytics summary with sentiment trends, competitive comparison, and insights. ## `sortBy` (type: `string`): How to sort Reddit search results. Relevance finds the best matches, Hot shows trending posts, New shows latest, Top shows highest voted. ## Actor input object example ```json { "keywords": [ "apify", "web scraping" ], "subreddits": [], "timeFilter": "week", "maxResults": 100, "includeSentiment": true, "includeComments": false, "outputMode": "raw", "sortBy": "relevance" } ``` # 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 = { "keywords": [ "apify", "web scraping" ], "subreddits": [], "timeFilter": "week", "maxResults": 100, "includeSentiment": true, "includeComments": false, "outputMode": "raw", "sortBy": "relevance" }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/reddit-brand-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 = { "keywords": [ "apify", "web scraping", ], "subreddits": [], "timeFilter": "week", "maxResults": 100, "includeSentiment": True, "includeComments": False, "outputMode": "raw", "sortBy": "relevance", } # Run the Actor and wait for it to finish run = client.actor("nexgendata/reddit-brand-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 '{ "keywords": [ "apify", "web scraping" ], "subreddits": [], "timeFilter": "week", "maxResults": 100, "includeSentiment": true, "includeComments": false, "outputMode": "raw", "sortBy": "relevance" }' | apify call nexgendata/reddit-brand-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/reddit-brand-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "📊 Reddit Brand Monitor -- Track Mentions & Sentiment", "description": "Monitor any brand, product, or topic on Reddit. Track mentions with AI sentiment analysis across all subreddits. Brandwatch alternative at 1/100th the cost. Trend tracking, competitive comparison & engagement analytics.", "version": "0.0", "x-build-id": "hKqsUN2axs9UOQIdp" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~reddit-brand-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-reddit-brand-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~reddit-brand-monitor/runs": { "post": { "operationId": "runs-sync-nexgendata-reddit-brand-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~reddit-brand-monitor/run-sync": { "post": { "operationId": "run-sync-nexgendata-reddit-brand-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keywords" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "Brand names, product names, or topics to monitor on Reddit. Each keyword is searched separately and results are combined.", "items": { "type": "string" } }, "subreddits": { "title": "Subreddits", "type": "array", "description": "Restrict search to specific subreddits. Leave empty to search all of Reddit. Example: startups, SaaS, technology.", "items": { "type": "string" } }, "timeFilter": { "title": "Time Filter", "enum": [ "hour", "day", "week", "month", "year", "all" ], "type": "string", "description": "Time range for the search. Controls how far back to look for mentions.", "default": "week" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of mentions to collect per keyword. Higher values take longer but give more complete data.", "default": 100 }, "includeSentiment": { "title": "Include Sentiment Analysis", "type": "boolean", "description": "Enable built-in sentiment analysis for each mention. Classifies mentions as positive, negative, or neutral with a score from -1.0 to 1.0.", "default": true }, "includeComments": { "title": "Include Comments", "type": "boolean", "description": "Also search Reddit comments, not just posts. Finds deeper mentions but increases run time.", "default": false }, "outputMode": { "title": "Output Mode", "enum": [ "raw", "tracker" ], "type": "string", "description": "Raw mode outputs individual mentions. Tracker mode adds analytics summary with sentiment trends, competitive comparison, and insights.", "default": "raw" }, "sortBy": { "title": "Sort By", "enum": [ "relevance", "hot", "new", "top" ], "type": "string", "description": "How to sort Reddit search results. Relevance finds the best matches, Hot shows trending posts, New shows latest, Top shows highest voted.", "default": "relevance" } } }, "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 } } } } } } } } } } ```