Mine user complaints and generate insight reports with Olostep, Gemini and Google Docs

AI Complaint Mining & Insight Extraction

This n8n template automates complaint mining from unstructured text sources and turns raw user feedback into clear, actionable insights.
It uses AI to identify recurring complaints, pain points, and themes, helping teams understand what users are unhappy about and why.

Who’s it for
Product managers identifying recurring user pain points
Customer support and success teams
Founders validating product-market fit issues
UX researchers analyzing qualitative feedback
Anyone dealing with large volumes of complaints or negative feedback

How it works / What it does
Trigger
The workflow starts with a manual trigger, form submission, or imported text source containing user complaints.

Data Preparation
Raw complaint text is cleaned, normalized, and split into individual complaint entries.
Ensures consistent input for AI processing.

AI Complaint Analysis
An AI model analyzes each complaint to identify:
Core issue
Complaint category
Emotional tone
Severity or urgency

Pattern Detection
Complaints are grouped by similarity to uncover recurring issues and themes.
Highlights the most frequent and impactful problems.

Insight Extraction
AI summarizes key insights such as:
Top recurring complaints
Root causes
Suggested improvement areas

Structured Output
Results are converted into structured data fields.
Ready to be stored, visualized, or shared with stakeholders.

Storage & Reporting
Extracted complaints and insights are saved to a table or sheet for easy review and analysis.

This workflow transforms unstructured complaint data into a clear feedback loop you can act on.

How to set up
Import the template into your n8n workspace.
Connect your AI model credentials (OpenAI or Gemini).
Define your input source (text, form, or file).
Connect your storage destination (Google Sheets, Data Table, or database).
Run the workflow to start mining complaints automatically.

Requirements
n8n account (cloud or self-hosted)
AI model provider (OpenAI or Gemini)
Storage destination (Google Sheets, Data Table, or database)

How to customize the workflow
Adjust complaint categories and severity scoring.
Add sentiment analysis or emotion classification.
Connect a vector database to track complaints over time.
Trigger alerts when critical issues are detected.
Generate dashboards or weekly complaint summaries automatically.

👉 This template helps you turn complaints into insights — and insights into product improvements.