📊 Analyze competitor Instagram engagement with Bright Data and GPT-5.5

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💡 Pro Tip — Heads up — if this workflow’s Instagram scraping breaks (it happens whenever Meta updates their frontend), ScraperNode is a community node that handles profiles, posts, reels, and comments without any HTML parsing.

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Description

Analyze competitor Instagram engagement by scraping profiles with Bright Data and scoring them with GPT-5.5.

This workflow reads competitor Instagram URLs from a Google Sheet, scrapes their profile data using the Bright Data Instagram Profiles dataset, validates the API response, then sends the data to GPT-5.5 for engagement scoring. Each competitor is scored on follower growth, engagement rate quality, content consistency, and audience authenticity (0-25 each, total 0-100). High-scoring competitors trigger email alerts.

How it works:

  1. Schedule trigger runs the workflow daily.
  2. Reads competitor URLs from the ‘competitor_accounts’ sheet.
  3. Sends each URL to Bright Data’s Instagram Profiles API.
  4. Validates the API response (handles async/error cases).
  5. GPT-5.5 analyzes profile metrics and scores engagement quality.
  6. Parses the structured JSON response.
  7. Filters by AI confidence (>= 0.7 threshold).
  8. Routes high scorers (engagement_score >= 75) to ‘top_performers’ with Gmail alert.
  9. Routes normal results to ‘engagement_analysis’.
  10. Low confidence results go to ‘low_confidence_engagement’ for review.

Setup:

Requirements:

Notes:

🔗 Nodes Used

Google Sheets, HTTP Request, Gmail, Schedule Trigger, AI Agent, OpenAI Chat Model

📥 Import

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

📖 Importing guide · 🔑 Credential setup