One-Star Attack Detection for Local Businesses

The Problem

A restaurant's Google rating drops from 4.8 to 3.9 overnight. Ten one-star reviews from brand-new accounts, identical phrasing, posted between 2 a.m. and 5 a.m. Morning coffee is when a regular mentions the drop. By then customers book elsewhere. Platform appeals take weeks. Revenue bleeds in hours.

Enterprise ORM suites (Podium ~$399/month, Chatmeter, Birdeye) bury alerts inside marketing dashboards built for multi-location brands. ReviewPush and Reputology offer real-time alerts from roughly $39–$49/month but still optimize for "every new review," not coordinated attack patterns. Native Google/Yelp emails are easy to miss. Single-location owners need one job: SMS when a rating is under attack, with evidence and a 10-minute response playbook.

The Solution

Ratingwire monitors Google and Yelp listings for review velocity, account age proxies, and sentiment shocks. When patterns break — cluster of new accounts, sentiment crash, 3× review speed — an SMS fires within minutes with dispute templates and suggested replies. No enterprise dashboard required.

How it works:

1. Link listing + phone — Connect Google Business Profile / Yelp; verify SMS number.
2. Baseline learning — First two weeks learn normal review velocity for that location.
3. Anomaly detect — Score spikes: volume, one-star clustering, text similarity, off-hours bursts.
4. Instant SMS — Alert with links, evidence bullets, and copy-paste dispute/response templates.
5. Incident log — Timestamped record for platform appeals and agency handoff.

Weekend MVP: polling Google/Yelp data sources + Twilio SMS + threshold rules. Tune false positives with 10 restaurants before opening signup.

Market Research

• Online reputation management is a multi-billion-dollar mature market; search for reputation services shows high CPC and commercial intent (Ideabrowser #8946).
• 90%+ of consumers use reviews in purchase decisions in widely cited surveys — rating drops have immediate local SEO and conversion impact.
• Community: r/smallbusiness and ORM Facebook groups complain about fake review attacks and overpriced suites.
• Regulatory attention on fake reviews increases value of documented incident evidence.

Competitive Landscape

• Podium — Full local messaging + reviews suite; often ~$399/month. Overkill for alert-only needs.
• ReviewPush — Real-time alerts from ~$39/month; general monitoring, not attack-specific.
• Reputology — Multi-location aggregation from ~$49/month; enterprise-leaning.
• Reviewflowz / ReviewBot — Leaner SMB tools and micro-SaaS notifiers; still mostly "new review" alerts.
• Native Google/Yelp notifications — Free; no anomaly detection or SMS urgency layer.

Your Opportunity

Own single-location attack detection at $10–$20/month — insurance pricing. White-label to local marketing agencies. Data from labeled incidents becomes the detection moat.

Business Model

• Basic — $10/month/location Google + Yelp SMS alerts.
• Pro — $20/month advanced patterns + extra platforms.
• Add-ons — $5–$15/platform.
• Agency white-label — volume pricing + markup room.

Unit Economics (illustrative)

• Twilio SMS pennies per alert; polling infra dominates cost
• Path: 2,000 locations × $12 ARPU = $24K MRR

Recommended Tech Stack

• Next.js + Vercel — onboarding + billing.
• Worker (Fly/Railway) — poll listings, run anomaly rules.
• Twilio — SMS alerts.
• Postgres — locations, reviews, incidents, baselines.
• Stripe — per-location subscriptions.
• Optional NLP — embedding similarity for copy-paste attack clusters.

AI Prompts to Build This

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

1. Ingest + Baseline

Build Ratingwire worker: every 15 minutes fetch latest reviews for a location. Store review_id, rating, text, created_at. Maintain rolling 14-day baseline of reviews_per_day and avg_rating.

2. Attack Rules

Trigger alert if: (reviews in 6h >= 3x baseline) AND (share of 1-star >= 70%) OR (avg_rating drop >= 0.4 in 24h). Deduplicate alerts for 12h. Include top review excerpts in payload.

3. SMS Playbook

On alert, send Twilio SMS with rating delta, count of new 1-stars, and link to /incidents/[id] showing dispute template and suggested public reply. Require STOP opt-out.

False positives kill this product. A normal bad-dinner rush of three honest one-stars must not look like an attack. Tunable sensitivity, quiet hours, and a "this was fine" button that trains the model are mandatory before paid launch. Lead with restaurants and salons — high review volume and clear revenue sensitivity — then expand to dentists and home services.

Agency channel: white-label SMS that says "via Your Agency Review Defense." Agencies already sell reputation retainers; giving them an attack detector increases perceived responsiveness without building ML. Compliance: SMS opt-in, Google/Yelp API ToS, and careful storage of review text. Market with incident postmortems ("How a taco shop caught a 12-review bomb at 3 a.m.") rather than feature matrices against Podium.

Price annually at a discount ($100/year) for owners who hate monthly cards. Churn will cluster after quiet months; counter with a monthly "all clear" SMS so the product stays visible when attacks do not.

Sources

• Ideabrowser #8946 competitive analysis
• Best review monitoring tools roundups
• Reviewflowz on review monitoring software
• Chatmeter review management overview