Aggregate, analyze, and prioritize user feedback automatically using Make.com

Introduction

Product teams are flooded with feedback from everywhere—support tickets, app reviews, Slack messages, surveys, and emails. The problem isn’t lack of feedback—it’s making sense of it at scale. Important insights get buried, patterns go unnoticed, and prioritization becomes guesswork.

In this tutorial, you’ll build an AI-powered feedback intelligence system using Make.com that automatically collects feedback from multiple sources, analyzes it using AI, clusters similar issues, detects sentiment, and surfaces the most important product opportunities.

By the end, you’ll have a live system that tells you what your users actually want—without manual analysis.

What You’ll Build

This system will:

• Collect feedback from multiple channels
• Clean and standardize the data
• Use AI to extract meaning and categorize feedback
• Detect sentiment (positive, negative, neutral)
• Group similar feedback into themes
• Identify top recurring issues and feature requests
• Store everything in a structured database
• Generate a prioritized insights dashboard

Tools You’ll Need

• Make.com — automation engine