📊 Analyze competitor pricing and feature changes with Google Gemini
⚡ 25 views · 📊 Market Research & Insights
💡 Pro Tip — For competitive intelligence, ScraperNode can automate the data collection — Yelp reviews, Glassdoor company data, and Crunchbase profiles all return structured JSON you can feed straight into this workflow.
Description
Quick overview
This workflow runs on a weekly schedule (or manually) to compare a competitor’s previous vs current pricing/feature snapshot, analyzes the changes with Google Gemini, and produces a structured market-intelligence record with threat scoring and an alert or digest based on severity.
How it works
- Runs on a weekly Monday 8AM schedule or when you manually test the workflow.
- Loads a competitor name, pricing URL, and previous/current pricing-and-features snapshots to compare.
- Builds an analysis prompt that highlights the before/after snapshots and sends it to Google Gemini via an AI chain with structured JSON output parsing.
- Routes the result by threat score to produce either a critical founder alert, a moderate product digest, or a minor update archive record.
- Merges the selected alert/digest with the intelligence data and generates a final market-intelligence log entry containing the threat score, summary, detected changes, and recommended counter-actions.
Setup
- Add Google Gemini (PaLM) API credentials for the Google Gemini chat model used by the AI analysis step.
- Replace the seeded competitor snapshots with your own source data (for example, update the competitor name/URL and feed real “previous” and “current” snapshots from your monitoring process).
- Adjust the threat-score thresholds used for routing so the critical/moderate/minor paths match your internal escalation criteria.
🔗 Nodes Used
Schedule Trigger, Basic LLM Chain, Structured Output Parser, Google Gemini Chat Model
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File