FocusForge.dev

Keep students playing longer with attention-optimized game mechanics

Score: 7.3/10MZHard BuildReady to Spawn
Brand Colors

The Opportunity

Problem

Developers struggle to generate sustainable revenue for browser-based educational games aimed at university students due to ad blockers and fleeting attention spans.

Solution

FocusForge analyzes play sessions and automatically suggests micro-rewards and difficulty adjustments that combat short attention spans. Creators embed a small SDK that returns real-time engagement scores and A/B test results. Revenue comes from a usage-based subscription that scales with active students.

Target Audience

Developers and creators of browser-based educational games targeted at university students

Differentiator

ML model trained exclusively on university student attention data

Brand Voice

supportive

Features

Session Heatmaps

must-have22h

Shows exactly where students drop off

Auto Reward Engine

must-have28h

Generates attention-grabbing events dynamically

A/B Testing

must-have18h

Compare mechanics across student cohorts

Engagement Score API

must-have12h

Real-time attention metric endpoint

Weekly Insights Email

must-have8h

Automated reports sent to creators

Difficulty Scaling

nice-to-have24h

Adaptive challenge adjustment

Cohort Comparison

nice-to-have15h

Compare different universities

Export Raw Data

nice-to-have10h

CSV download for research use

Total Build Time: 137 hours

Database Schema

sessions

ColumnTypeNullable
iduuidNo
game_iduuidNo
durationintNo
attention_scoreintNo

Relationships:

  • game_id references games(id)

recommendations

ColumnTypeNullable
iduuidNo
game_iduuidNo
suggestiontextNo

Relationships:

  • game_id references games(id)

games

ColumnTypeNullable
iduuidNo
creator_iduuidNo

Relationships:

  • creator_id references users(id)

API Endpoints

POST
/api/track-session

Record attention data

GET
/api/recommend

Return AI suggestions

🔒 Auth Required

Tech Stack

Frontend
Next.js 14 + Recharts
Backend
Next.js API routes + Python microservice
Database
Supabase Postgres
Auth
Supabase Auth
Payments
Stripe
Hosting
Vercel
Additional Tools
Vercel Edge FunctionsSimple ML model on Replicate

Build Timeline

Week 1: SDK and data ingestion

40h
  • Session tracking endpoint
  • Basic dashboard

Week 2: Attention scoring model

35h
  • Simple rule-based scorer
  • Heatmap UI

Week 3: Recommendations engine

30h
  • Suggestion API
  • Email reports

Week 4: A/B testing and payments

25h
  • Stripe integration
  • Public launch
Total Timeline: 4 weeks • 130 hours

Pricing Tiers

Free

$0/mo

1 game

  • 100 sessions/mo
  • Basic heatmap

Pro

$25/mo

Up to 10k sessions

  • Unlimited sessions
  • AI recommendations
  • A/B tests

Research

$79/mo

Unlimited

  • Raw data export
  • Cohort analysis
  • API access

Revenue Projections

MonthUsersConversionMRRARR
Month 12515%$94$1,128
Month 618022%$990$11,880

Unit Economics

$22
CAC
$280
LTV
5%
Churn
78%
Margin
LTV:CAC Ratio: 12.7xExcellent!

Landing Page Copy

Stop losing students after 90 seconds

Get AI-powered attention insights that keep university players engaged longer

Feature Highlights

See drop-off heatmaps instantly
Receive weekly improvement tips
Run A/B tests without code

Social Proof (Placeholders)

"Doubled average session time in one week - Leo T."

First Three Customers

Join educational game Discords and offer free 30-day Pro trial in exchange for honest feedback. Post in university teaching forums showing sample heatmap reports.

Launch Channels

ProductHuntr/edtechEducause

SEO Keywords

educational game analyticsstudent attention trackinggame engagement metrics

Competitive Analysis

GameAnalytics

gameanalytics.com
Free tier + paid
Strength

General game metrics

Weakness

No attention-specific models for students

Our Advantage

Specialized for short attention university audience

🏰 Moat Strategy

Proprietary attention dataset from university students

⏰ Why Now?

Attention spans in Gen Z have dropped below 8 seconds according to recent studies, making retention tools critical

Risks & Mitigation

technicalmedium severity

ML model accuracy low initially

Mitigation

Start with rule-based system then improve

Validation Roadmap

pre-build7 days

Collect 500 anonymous session logs from 5 games

Success: Identify clear drop-off patterns

Pivot Options

  • Sell as white-label university research tool
  • Add teacher classroom dashboards

Quick Stats

Build Time
130h
Target MRR (6 mo)
$990
Market Size
$29.0M
Features
8
Database Tables
3
API Endpoints
2