Starter Kit
All Startup Ideas
SaaS ~12 hours to build

Customer Feedback Aggregator

Stop checking 5 different review sites every morning.

The Problem

Product teams are drowning in feedback scattered across G2, Capterra, Trustpilot, app stores, and social media. They either miss critical reviews, respond too late, or waste hours manually compiling insights. Negative reviews slip through, damaging reputation before anyone notices.

The Solution

A unified dashboard that pulls reviews from all major platforms, uses AI to identify sentiment and themes, and alerts you when something needs attention. Track your reputation score across platforms and respond without switching tabs.

How it works:

1

Connect platforms

G2, Capterra, app stores, etc.

2

AI analysis

Sentiment, themes, urgency scoring

3

Get alerts

Slack/email when reviews need response

Market Research

Review management is a growing market as online reputation becomes critical for B2B buying decisions. Existing tools are either enterprise-priced or too basic.

  • 95% of customers read online reviews before making a purchase (PowerReviews)
  • G2 alone has 2M+ reviews—B2B decision makers rely heavily on peer reviews
  • Competitors like ReviewTrackers charge $99+/month—room for affordable alternative

AI Prompts to Build This

Copy and paste these into Claude, Cursor, or your favorite AI tool.

1. Project Setup

Create a Next.js app for a Customer Feedback Aggregator. Features needed: - Dashboard showing reviews from multiple sources in a unified feed - Filter by platform, sentiment (positive/neutral/negative), date - Each review card shows: source platform, rating, date, text, sentiment badge - Sidebar with aggregated stats: average rating by platform, total reviews, sentiment breakdown - Settings page to add API keys/connections for different platforms Use Tailwind CSS and shadcn/ui components.

2. Core Feature

Create API integrations for: 1. G2 reviews via their API (requires partner access) or web scraping 2. App Store reviews using Apple's RSS feed 3. Google Play reviews using their scraping library For each review, use OpenAI to: - Analyze sentiment (positive/neutral/negative with score 0-100) - Extract key themes/topics mentioned - Flag reviews that need urgent response (complaints, bugs mentioned) Store reviews in a database with polling for new reviews every hour.

3. Notifications

Add notification system: - Slack webhook integration to post new reviews to a channel - Email digest option (daily/weekly summary) - Instant alerts for negative reviews (1-2 stars) - Weekly report showing: review count, avg rating change, common themes Include a settings page to configure notification preferences per user.

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