ReviewRadar - Automated Multi-Platform Review Intelligence for Local Businesses
Local business owners are flying blind across Google, Yelp, TripAdvisor, and Facebook reviews while their reputation quietly burns. ReviewRadar aggregates every new review across all platforms, classifies sentiment by topic, and sends a weekly digest with the three things you must fix this week. No more copy-pasting from four tabs at midnight.
Difficulty
intermediate
Category
NLP & Text AI
Market Demand
High
Revenue Score
7/10
Platform
Web App
Vibe Code Friendly
No
Hackathon Score
6/10
Validated by Real Pain
— seeded from real developer complaints
Restaurant owners on r/restaurantowners frequently describe spending 45-60 minutes every week manually checking multiple review platforms with no way to spot recurring themes or trending issues until their rating has already dropped.
What is it?
Local business owners — especially solo restaurant owners, salon managers, and gym operators — spend hours manually checking four review platforms every week with zero structured insight. ReviewRadar pulls new reviews via the Google Business API, Yelp Fusion API, and web scraping fallbacks, then runs NLP classification to bucket complaints by theme (staff, cleanliness, wait time, price). The weekly digest email shows trending issues before they become 2-star avalanches. Fully buildable today because Google Business Profile API is stable, Yelp Fusion is public, and sentiment classification via Claude or HuggingFace zero-shot is one API call.
Why now?
Google Business Profile API opened stable OAuth review access in late 2024, and HuggingFace zero-shot classification is now cheap enough at $0.002/call to make per-review classification economically viable for small operators.
- ▸Multi-platform review aggregation from Google, Yelp, and Facebook via official APIs and scraping fallbacks.
- ▸Zero-shot NLP topic classifier buckets reviews into staff, wait time, cleanliness, and price themes.
- ▸Weekly email digest with ranked issues and reply suggestions for top negative reviews.
- ▸Sentiment trend chart showing 30-day trajectory per topic so owners spot decay early.
Target Audience
Independent local business owners — restaurants, gyms, salons — roughly 4M in the US alone managing reputation manually.
Example Use Case
Maria runs a 60-seat Italian restaurant, gets a Friday digest showing 8 of her last 12 reviews mentioned slow service during dinner rush, fixes staffing on weekends, and her average rating climbs from 3.9 to 4.3 in six weeks.
User Stories
- ▸As a solo restaurant owner, I want to see all my reviews from Google and Yelp in one place, so that I stop spending 45 minutes per week across four tabs.
- ▸As a gym manager, I want a weekly email showing my top recurring complaints ranked by frequency, so that I can fix the right thing first.
- ▸As a salon owner, I want to know if my average sentiment is trending down before it hits my star rating, so that I can act before losing bookings.
Acceptance Criteria
Review Aggregation: done when new Google and Yelp reviews appear in dashboard within 6 hours of posting. Classification: done when every review is tagged with at least one topic label and a sentiment score. Digest Email: done when weekly email renders correctly in Gmail with ranked topics and review counts. Stripe Billing: done when checkout flow completes and user gains access to paid dashboard features.
Is it worth building?
$29/month x 60 users = $1,740 MRR at month 3. $29/month x 300 users = $8,700 MRR at month 8. Math assumes 5% conversion from free trial via cold email to local business owners.
Unit Economics
CAC: $18 via cold email at 4% conversion on $0.45/email. LTV: $348 (12 months at $29/month). Payback: 1 month. Gross margin: 88%.
Business Model
SaaS subscription
Monetization Path
7-day free trial, then $29/month for one location. $79/month multi-location plan unlocks at 3+ venues.
Revenue Timeline
First dollar: week 3 via beta upgrade. $1k MRR: month 3. $5k MRR: month 7.
Estimated Monthly Cost
HuggingFace Inference API: $20, Vercel: $20, Supabase: $25, Resend: $10, Stripe fees: $25. Total: ~$100/month at launch.
Profit Potential
Full-time viable at $5k–$10k MRR with a lean stack.
Scalability
High — add Trustpilot, G2, and Booking.com scrapers in V2. Multi-location franchise plans at $199/month are a natural upsell.
Success Metrics
Week 2: 10 beta businesses onboarded. Month 2: 40 paid. Month 3: less than 10% monthly churn.
Launch & Validation Plan
DM 30 restaurant owners in a local Facebook group offering free 60-day access in exchange for a 20-minute feedback call before writing a line of code.
Customer Acquisition Strategy
First customer: join 3 local restaurant owner Facebook groups, offer free setup and 60-day access to first 5 respondents. Ongoing: cold email sequences via Apollo.io targeting single-location restaurants with sub-4.2 Google ratings, plus ProductHunt launch.
What's the competition?
Competition Level
Medium
Similar Products
Birdeye ($300+/month, enterprise-only), Podium ($249+/month, overkill for solos), Grade.us ($110/month, no NLP topic clustering) — none built for the $29/month solo owner with automated topic intelligence.
Competitive Advantage
Competitors like Birdeye and Podium cost $300+/month and target enterprise chains. ReviewRadar is priced for the solo owner who runs the grill and the inbox.
Regulatory Risks
GDPR applies if storing EU customer review data. Yelp ToS restricts bulk scraping — use Fusion API only. Google Business Profile API requires OAuth per business owner.
What's the roadmap?
Feature Roadmap
V1 (launch): Google and Yelp aggregation, topic classifier, weekly digest email, single location. V2 (month 2-3): Facebook reviews, reply suggestion templates, sentiment trend charts. V3 (month 4+): multi-location dashboard, franchise plan, Slack alerts.
Milestone Plan
Phase 1 (Week 1-2): API integrations and classifier live, 5 beta businesses onboarded. Phase 2 (Week 3-4): Stripe billing, digest email, landing page live. Phase 3 (Month 2): 30 paid users, Facebook review integration shipped.
How do you build it?
Tech Stack
Next.js, HuggingFace Inference API for zero-shot classification, Google Business Profile API, Yelp Fusion API, Supabase, Resend for digest emails, Stripe — build with Cursor for backend, v0 for dashboard UI.
Suggested Frameworks
HuggingFace Transformers, LangChain, FastAPI
Time to Ship
2 weeks
Required Skills
Google Business Profile API auth, HuggingFace zero-shot classification, cron jobs for polling, Resend email templating.
Resources
HuggingFace zero-shot classification docs, Google Business Profile API docs, Yelp Fusion API docs, Resend quickstart.
MVP Scope
pages/index.tsx (landing), pages/dashboard.tsx (review feed), pages/digest-preview.tsx, lib/google-api.ts, lib/yelp-api.ts, lib/classifier.ts (HuggingFace zero-shot), lib/digest-builder.ts, cron/poll-reviews.ts, supabase/schema.sql, resend/weekly-digest-template.tsx.
Core User Journey
Sign up -> connect Google Business profile -> receive first classified digest email in 7 days -> upgrade to paid.
Architecture Pattern
Cron job polls Google and Yelp APIs every 6h -> new reviews saved to Supabase -> HuggingFace classifier tags each review -> weekly cron builds digest -> Resend fires email -> dashboard reads from Supabase.
Data Model
User has many Locations. Location has many Reviews. Review has one Classification with topic and sentiment score. Location has many DigestReports.
Integration Points
Google Business Profile API for reviews, Yelp Fusion API for reviews, HuggingFace Inference API for classification, Supabase for storage, Resend for email, Stripe for billing.
V1 Scope Boundaries
V1 excludes: review reply automation, mobile app, TripAdvisor integration, white-label, franchise dashboards.
Success Definition
A solo restaurant owner who found the product themselves completes onboarding, receives their first digest, and upgrades without founder involvement.
Challenges
The hardest non-technical problem is convincing local business owners to pay monthly for insights they think they can do manually. Cold email to owner-operated restaurants converts poorly — partner with local business associations or POS vendors for warm distribution.
Avoid These Pitfalls
Do not build multi-location before 10 paying single-location customers. Do not attempt Yelp scraping before exhausting the Fusion API — ToS violations can kill the product. Finding first 10 paying customers takes 3x longer than building the product.
Security Requirements
Supabase Auth with Google OAuth. RLS enabled on all tables scoped to user ID. Rate limiting 60 req/min per IP. OAuth tokens encrypted at rest. GDPR: data deletion endpoint on account close.
Infrastructure Plan
Vercel for Next.js frontend and API routes. Supabase for Postgres and auth. Vercel Cron for polling jobs. Resend for transactional email. Sentry for error tracking. GitHub Actions for CI.
Performance Targets
Launch: 50 DAU, 500 req/day. API response under 400ms. Dashboard load under 2s. No real-time needed — batch polling every 6h is sufficient.
Go-Live Checklist
- ☐Security audit complete
- ☐Stripe payment tested end-to-end
- ☐Sentry error tracking live
- ☐Vercel Analytics configured
- ☐Custom domain with SSL
- ☐Privacy policy and terms published
- ☐5 beta owners signed off
- ☐Rollback plan documented
- ☐ProductHunt and local FB group posts drafted.
How to build it, step by step
1. Run npx create-next-app@latest review-radar --typescript. 2. Install @supabase/supabase-js, resend, stripe, axios. 3. Create Supabase schema for users, locations, reviews, classifications. 4. Build lib/google-api.ts to fetch reviews via OAuth. 5. Build lib/yelp-api.ts using Yelp Fusion key. 6. Build lib/classifier.ts calling HuggingFace zero-shot with 5 topic labels. 7. Build cron/poll-reviews.ts as a Vercel cron job running every 6h. 8. Build lib/digest-builder.ts to group last 7 days by topic and rank issues. 9. Build Resend email template with ranked issues and reply suggestions. 10. Deploy to Vercel, add Stripe checkout for $29/month plan.
Generated
April 13, 2026
Model
claude-sonnet-4-6
Disclaimer: Ideas on this site are AI-generated and may contain inaccuracies. Revenue estimates, market demand figures, and financial projections are illustrative assumptions only — not financial advice. Do your own research before making any business or investment decisions. Technology availability, pricing, and market conditions change rapidly; always verify details independently.