Use the n8n Data Tables feature to store, retrieve, and analyze survey results — then let OpenAI automatically recommend the most relevant course for each respondent.
This workflow demonstrates how to use n8n’s built-in Data Tables to create an internal recommendation system powered by AI.
It:
Survey Responses
Courses
course
: the course titlereasoning
: why it was selectedTrigger: Form submission (manual or public link)
Perfect for educators, training managers, or anyone wanting to use n8n Data Tables as a lightweight internal database — ideal for AI-driven recommendations, onboarding workflows, or content personalization.
This workflow uses two Data Tables — both created directly inside n8n.
Survey Responses
Columns:
Name
Q1
— Where did you learn about n8n?Q2
— What is your experience with n8n?Q3
— What kind of automations do you need help with?To create:
Courses
Columns:
Course
Description
To create:
This Courses Data Table is where you’ll store all available learning paths or programs for the AI to compare against survey inputs.
Node | Purpose | n8n Feature |
---|---|---|
Form Trigger | Collect survey responses | Forms |
Data Table (Upsert) | Stores results in Survey Responses |
Data Tables |
Data Table (Get) | Retrieves Courses |
Data Tables |
Aggregate + Set | Combines and formats table data | Core nodes |
OpenAI Chat Model (LangChain Agent) | Analyzes responses and courses | AI |
Structured Output Parser | Returns structured JSON output | LangChain |
This workflow shows how n8n’s Data Tables can act as your internal database:
All user data and course content are stored securely and natively in n8n Cloud or Self-Hosted environments.
Need help customizing this (e.g., expanding Data Tables, connecting multiple surveys, or automating follow-ups)?