Monitor brand mentions with OpenAI across Twitter/X, Reddit, News, Airtable and Slack

Monitors brand mentions across Twitter/X, Reddit, and News APIs in real-time (or scheduled), fetches mentions in parallel, normalizes data, uses AI to analyze sentiment/urgency/topics, detects duplicates, filters critical mentions, logs everything to Airtable, posts alerts to Slack, and emails daily HTML digest reports to the marketing team.

Good to Know - Runs every hour (configurable) to provide near-real-time brand monitoring - Pulls mentions from multiple platforms in parallel: Twitter/X, Reddit, News sources - Uses AI (OpenAI/Grok/etc.) for advanced sentiment classification, urgency detection, topic extraction, and duplicate deduplication - Focuses on actionable insights: flags negative/urgent mentions for immediate response - Generates beautiful HTML daily digest with summarized mentions, sentiment trends, and key highlights - Stores historical data in Airtable for tracking, analytics, and long-term reporting - Sends real-time Slack alerts for high-priority/negative mentions - Reduces manual social monitoring time dramatically and helps catch reputation issues early

How It Works

1. Trigger & configure - Schedule Trigger — Runs every hour (or custom interval) to check for new brand mentions - Set brand monitoring config — Defines brand name, keywords, excluded terms, monitoring parameters (via Set node or variables)

2. Fetch & collect mentions - Fetch Twitter/X mentions — Uses Twitter/X node or HTTP Request to search recent tweets (mentions, keywords) - Fetch Reddit mentions — Searches relevant subreddits or Reddit-wide for brand keywords/posts - Fetch news article mentions — Queries news APIs (e.g. NewsAPI, Google News via RSS/HTTP) for brand coverage - Merge platform mentions — Combines results from all sources into a unified stream - Normalize mentions into unified schema — Standardizes fields (text, author, platform, timestamp, URL, etc.) for consistent processing

3. AI analyze & deduplicate - AI sentiment and urgency analysis — Sends mentions to AI model (OpenAI node) with prompt to classify: - Sentiment: positive / neutral / negative - Urgency/severity: low / medium / high / critical - Topics/themes - Key excerpts - Wait For Result — Ensures AI responses are complete - Process analysis results — Parses structured JSON output from AI - Filter mentions requiring alerts — Routes based on sentiment/urgency thresholds - Deduplicate — Removes near-duplicate mentions (e.g. same content reposted)

4. Store, alert & report - Log mention to Airtable — Appends/updates records with full details, sentiment, AI analysis, timestamp - Route by sentiment and urgency — Critical/negative → immediate action path - Send mention alert — Posts formatted message to Slack (or Discord/Teams) with link, text snippet, sentiment badge - Generate HTML daily digest report — Compiles summary: total mentions, sentiment breakdown, top issues, trends - Email HTML digest — Sends polished report to marketing team via Email node (SMTP/Gmail) - Log success and update listings — Records workflow completion, stats for monitoring

Data Sources - Twitter/X — Recent search for mentions/keywords (via Twitter node or HTTP Request with API) - Reddit — Subreddit or site-wide search for brand mentions - News APIs — NewsAPI.org, Google News RSS, or similar for article mentions - AI Model — OpenAI (GPT-4o / GPT series), Grok, or other LLM for sentiment/urgency analysis - Storage — Airtable base (tables for mentions, daily summaries) - Notifications — Slack (webhook or app), Email (SMTP)