Product Intelligence Dashboard

Winner, Most Popular Project (voted by all hackathon participants and viewers)

Analyzes customer feedback data alongside comparable SKUs from e-commerce marketplaces. Surfaces feature-level recommendations: what to add, improve, or remove, backed by sentiment scores and mention frequency.

What It Does

1. Customer Sentiment Analysis. Ingests customer reviews and breaks down sentiment by feature (sound quality, battery life, comfort, etc.)
2. Competitive Benchmarking. Compares your product's feature set against comparable SKUs to identify gaps and opportunities.
3. Feature Recommendations. Prioritized add/improve/remove recommendations backed by mention frequency, sentiment scores, and cost-impact estimates.
4. Trend Visualization. Interactive dashboard with peer comparison matrices, sentiment breakdowns, and priority filtering.

How It Works

Upload data files (customer reviews, competitor SKU data, search ranking data) and the dashboard cross-references everything to produce:

• Feature gap analysis: what competitors have that you don't
• Sentiment-weighted priorities: not just what customers mention, but how they feel about it
• Cost-impact estimates for each recommendation
• Confidence scores for statistical reliability

All processing happens client-side. No data leaves the browser.

The dashboard loads with realistic sample data (wireless earbuds category) so you can see the full experience without bringing your own files.

Stack

Next.js · TypeScript · Tailwind CSS · shadcn/ui · Recharts

Run Locally

pnpm install
pnpm dev

Open http://localhost:3000.

License

MIT