Templates / Forecast demand, optimize pricing, and engage customers with GPT‑4.1, Postgres, email, and Slack

Forecast demand, optimize pricing, and engage customers with GPT‑4.1, Postgres, email, and Slack

Ready for 3.0

by Cheng Siong Chin ✓ · 163 views · created 2026-01-18 · CRM, AI Summarization

Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.

What this workflow does

This AI workflow has 31 nodes and runs when an HTTP POST request hits its webhook URL. Along the way it connects OpenAI Chat Model, Postgres and Slack.

How it runs

Trigger: When an HTTP POST request hits its webhook URL.

  1. Workflow Configuration (Edit Fields (Set)): sets 7 fields: lowStockThreshold, negativeSentimentThreshold, highDemandThreshold…
  2. Route by Data Type (Switch): routes items into 4 branches
  3. Normalize Orders (Edit Fields (Set)): sets 7 fields: orderId, customerId, orderDate…
  4. Normalize Reviews (Edit Fields (Set)): sets 7 fields: reviewId, productId, customerId…
  5. Normalize Inventory (Edit Fields (Set)): sets 7 fields: productId, productName, currentStock…
  6. Normalize Social Media (Edit Fields (Set)): sets 7 fields: postId, platform, content…
  7. Validate Orders (Filter): keeps only the items that match a condition
  8. Validate Reviews (Filter): keeps only the items that match a condition
  9. Validate Inventory (Filter): keeps only the items that match a condition
  10. Validate Social Media (Filter): keeps only the items that match a condition

…plus 16 more steps. See the full node list below.

Services it uses

OpenAI Chat ModelPostgresSlack

Before you upgrade to n8n 3.0

Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.

Nodes used (15)

From the author

How It Works This workflow automates inventory management and customer engagement for e-commerce businesses and retail operations managing multiple product categories. It solves the critical challenge of maintaining optimal stock levels while personalizing…

Excerpt from Cheng Siong Chin's description on n8n.io.

View the original on n8n.io → Check your own copy

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