AI Tool

AI Customer Feedback Analyzer

Personal Project

A Streamlit dashboard that pulls feedback together, categorizes issues, detects sentiment, and surfaces what matters most. PMs see exactly where to focus without reading every comment.

Python Streamlit Claude API Claude Code

How It Works

1
Upload customer feedback from any source (CSV export from surveys, tickets, reviews)
2
Claude analyzes each piece of feedback for sentiment and categorizes by theme
3
Dashboard displays priority-ranked insights with volume and sentiment trends
4
PMs see exactly where to focus without reading every comment

Product Decisions

Component Technology Purpose
Frontend Streamlit Interactive dashboard with filters and visualizations
Analysis Claude API Sentiment detection and theme categorization
Backend Python (Pandas) Data processing and aggregation
Development Claude Code Rapid prototyping and iteration

Built with Claude Code: Used Claude Code to build the Streamlit app, design the categorization prompt, and iterate on the dashboard layout. Focused my time on UX decisions while Claude Code handled implementation.

What I Learned

  • 💡 Instead of defining categories upfront, I let Claude identify themes from the data. It caught recurring issues I wouldn't have thought to look for.
  • 💡 I wanted PMs to have something to act on, so I made insights specific. For example, "23 users this week said the export button is hard to find" instead of just "negative sentiment detected."