🔧 Track competitor X announcements with Bright Data, OpenAI, Sheets and Slack

⚡ 3 views · 🔧 Miscellaneous

💡 Pro Tip — Twitter’s API is paid now, which makes simple data pulls expensive. ScraperNode is a community node that scrapes Twitter profiles and posts without needing API access.

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Description

Quick Overview

This workflow runs each weekday morning to crawl selected X (Twitter) accounts via Bright Data, score posts against each account’s normal engagement, summarize notable announcements with OpenAI, log all posts to Google Sheets, and send a digest (or “quiet day” notice) to Slack.

How it works

  1. Runs on a weekday morning schedule (or manually) and reads the list of X handles and thresholds from Settings.
  2. Loads previously seen post IDs from an n8n Data Table and sends them to Bright Data so already-processed posts are skipped during the crawl.
  3. Triggers a Bright Data X posts dataset crawl for each profile URL, then polls Bright Data until the snapshot is ready (or fails/times out).
  4. Downloads the posts, computes an engagement baseline per account (median of recent non-repost posts), tags each post (launch/pricing/funding/hiring/incident/event/general), and selects the most notable items.
  5. If there are notable posts, sends the short list to OpenAI to produce one-sentence, plain-language summaries for each item.
  6. Builds a Slack digest, appends every crawled post (notable or not) as rows in Google Sheets, and upserts each post ID into the Data Table to avoid re-crawling it next run.
  7. Posts either the digest or a “quiet day” message to Slack, and if the workflow errors it posts a failure alert to a separate Slack channel.

Setup

  1. Create a Bright Data Header Auth credential (HTTP Header Auth) named Authorization with the value Bearer <YOUR_BRIGHT_DATA_API_KEY>.
  2. Add an OpenAI (Chat) credential for the OpenAI model used in the workflow.
  3. Add a Slack credential, set the digest channel in Settings, and ensure the error-alert channel (default #alerts) exists or update it.
  4. Add a Google Sheets credential, replace the spreadsheet URL/ID, and ensure a sheet tab named “Competitor posts” exists with columns that match the appended fields.
  5. Create an n8n Data Table named x_post_watch with text columns post_id, handle, and seen_on, then update Settings (handles, days_back, thresholds) to your needs.

đź”— Nodes Used

Google Sheets, HTTP Request, Slack, Schedule Trigger, Basic LLM Chain, OpenAI Chat Model

đź“Ą Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup