Analyze competitor pricing and feature changes with Google Gemini

by Qasim ✓ · 25 views · created 2026-08-20 · Market Research, AI Summarization

What this workflow does

This AI workflow has 13 nodes and runs manually, when you click “Execute workflow” (plus 1 other trigger). Along the way it connects Google Gemini Chat Model.

How it runs

Trigger: Manually, when you click “Execute workflow” (plus 1 other trigger).

1. Set Competitor Data Fields (Edit Fields (Set)): sets 4 fields: competitor_name, competitor_url, previous_snapshot…
2. Prepare Data for Analysis (Code): runs custom JavaScript code
3. Market Intelligence AI Agent (Basic LLM Chain): sends a prompt to an LLM, with model: Google Gemini Analysis Model; output parser: Parse Structured Intelligence
4. Route by Threat Assessment (Switch): routes items into 3 branches
5. Format Founder Urgency Alert (Code): runs custom JavaScript code
6. Format Product Update Digest (Code): runs custom JavaScript code
7. Log Minor Changes (Edit Fields (Set)): sets 2 fields: alert_type, status
8. Merge: merges the data from its input branches
9. Finalize Intelligence Log (Code): runs custom JavaScript code

Services it uses

Google Gemini Chat Model

Before you upgrade to n8n 3.0

Nodes used (9)

• Manual Triggern8n-nodes-base.manualTrigger
• Edit Fields (Set)n8n-nodes-base.set
• Coden8n-nodes-base.code
• Schedule Triggern8n-nodes-base.scheduleTrigger
• Basic LLM Chain@n8n/n8n-nodes-langchain.chainLlm
• Google Gemini Chat Model@n8n/n8n-nodes-langchain.lmChatGoogleGemini
• Structured Output Parser@n8n/n8n-nodes-langchain.outputParserStructured
• Switchn8n-nodes-base.switch
• Mergen8n-nodes-base.merge

From the author

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…

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