GhostScore

Score student reliability to filter out ghosts before they book

Score: 7.9/10UKMedium BuildReady to Spawn
Brand Colors

The Opportunity

Problem

Operators of student-focused restaurant reservation apps face high churn rates as students frequently ghost bookings, causing restaurants to refuse payment for unreliable leads.

Solution

GhostScore builds a reliability score for each student based on past bookings and app data. Low-score students get extra scrutiny or blocks, ensuring high-quality leads for restaurants. Operators see score-based filtering in their dashboard to boost payment acceptance.

Target Audience

Owners and operators of student-focused restaurant reservation apps

Differentiator

ML-powered scoring unique to student behaviors like class schedules and group bookings

Brand Voice

professional

Features

Student Scoring

must-have15h

Auto-generate 0-100 reliability score

Risk Filters

must-have10h

Block or flag low-score bookings

Score Dashboard

must-have12h

Visualize scores and trends

API Integration

must-have14h

Real-time score queries for your app

Score Updates

must-have10h

Recalculate scores on new data

Export Reports

nice-to-have5h

CSV/PDF score summaries

Custom Weights

nice-to-have6h

Adjust scoring factors

Alert Notifications

nice-to-have4h

Email on score drops

Total Build Time: 76 hours

Database Schema

users

ColumnTypeNullable
iduuidNo
emailtextNo
api_keytextNo

Relationships:

  • one-to-many with students

students

ColumnTypeNullable
iduuidNo
phonetextYes
scoreintNo
factorsjsonbYes
user_iduuidNo

Relationships:

  • belongs to users
  • one-to-many with bookings

bookings

ColumnTypeNullable
iduuidNo
student_iduuidNo
score_at_bookintNo
showed_upboolNo
user_iduuidNo

Relationships:

  • belongs to students and users

score_logs

ColumnTypeNullable
iduuidNo
student_iduuidNo
old_scoreintNo
new_scoreintNo

Relationships:

  • belongs to students

API Endpoints

GET
/api/students/:phone/score

Get real-time score

🔒 Auth Required
POST
/api/bookings

Log booking outcome for scoring

🔒 Auth Required
POST
/api/recalc-scores

Batch update scores

🔒 Auth Required
GET
/api/dashboard

User metrics

🔒 Auth Required

Tech Stack

Frontend
Next.js 14 + Tailwind + shadcn/ui
Backend
Next.js API routes + Supabase Edge Functions
Database
Supabase Postgres
Auth
Supabase Auth
Payments
Stripe
Hosting
Vercel
Additional Tools
Vercel AI for simple ML scoring

Build Timeline

Week 1: DB and auth

18h
  • Schema
  • Auth

Week 2: Scoring engine

25h
  • Score calc logic
  • API

Week 3: Dashboard

22h
  • Charts
  • Filters

Week 4: Integrations

20h
  • Data sync
  • Testing

Week 5: Polish + payments

15h
  • Reports
  • Stripe
Total Timeline: 5 weeks • 100 hours

Pricing Tiers

Free

$0/mo

No custom weights

  • 500 students
  • Basic scores

Starter

$8/mo
  • 5k students
  • Custom factors

Pro

$49/mo
  • Unlimited
  • Alerts, exports

Revenue Projections

MonthUsersConversionMRRARR
Month 12512%$24$288
Month 612018%$216$2,592

Unit Economics

$18
CAC
$300
LTV
4%
Churn
88%
Margin
LTV:CAC Ratio: 16.7xExcellent!

Landing Page Copy

Score Students, Secure Payments

GhostScore predicts no-shows with data-driven reliability ratings for your bookings.

Feature Highlights

AI student scores
Pre-filter risky bookings
Improve lead quality 70%
Easy API integration

Social Proof (Placeholders)

"'Scores saved our restaurant partnerships' – DineU"

First Three Customers

Post in student app operator Slack groups and Twitter searches for 'student no-show'. Offer free setup call and 60-day trial. Target 3 from top results.

Launch Channels

Product Huntr/indiehackersLinkedIn SaaS groups

SEO Keywords

student reliability scoringpredict restaurant no-showsbooking risk filter saas

Competitive Analysis

Tock Predict

tock.com/predict
$99/mo
Strength

Advanced ML

Weakness

Not student-specific

Our Advantage

Niche scoring at 1/10th price

🏰 Moat Strategy

Accumulating proprietary student booking data for better scores

⏰ Why Now?

Explosion of AI tools making scoring feasible for solos

Risks & Mitigation

technicalhigh severity

Scoring accuracy

Mitigation

Start rule-based, iterate with data

marketmedium severity

Data privacy concerns

Mitigation

GDPR compliant anon scores

Validation Roadmap

pre-build4 days

Survey 10 operators on scoring interest

Success: 70% yes

mvp10 days

Manual score beta

Success: Payment uplift

Pivot Options

  • General no-show predictor
  • Student CRM

Quick Stats

Build Time
100h
Target MRR (6 mo)
$400
Market Size
$40.0M
Features
8
Database Tables
4
API Endpoints
4