Unit Economics: The AI Advantage in Every Metric
Executive Summary: 5:1 LTV:CAC with Zero Competition
Game-Changing Reality: YeboLearn's AI monopoly doesn't just improve unit economics—it completely redefines them. While traditional EdTech struggles with 2:1 LTV:CAC ratios, YeboLearn achieves 5:1+ through AI-driven conversion, retention, and expansion.
Customer Acquisition Cost (CAC) Breakdown
CAC by Channel and Tier
| Channel | Cost per Lead | Lead → Demo | Demo → Trial | Trial → Customer | CAC | % of Acquisition |
|---|---|---|---|---|---|---|
| Direct Sales | R500 | 60% | 80% | 70% | R1,488 | 40% |
| Partner Referrals | R100 | 80% | 85% | 75% | R196 | 30% |
| Inbound (AI SEO) | R50 | 70% | 82% | 72% | R137 | 20% |
| Word of Mouth | R0 | 90% | 90% | 80% | R0 | 10% |
| Blended CAC | R200 | 72% | 83% | 73% | R630 | 100% |
CAC by School Size
| School Size | Students | Sales Effort | Marketing Cost | Total CAC | CAC per Student |
|---|---|---|---|---|---|
| Small (100-200) | 150 | R3,000 | R1,500 | R4,500 | R30 |
| Medium (200-400) | 300 | R5,000 | R2,500 | R7,500 | R25 |
| Large (400+) | 500 | R8,000 | R4,000 | R12,000 | R24 |
| Weighted Average | 250 | R5,000 | R2,500 | R7,500 | R30 |
AI Impact on CAC Reduction
| Metric | Traditional EdTech | YeboLearn (AI-First) | Improvement |
|---|---|---|---|
| Demo Booking Rate | 20% | 60% | 3x |
| Demo → Trial Conversion | 40% | 80% | 2x |
| Trial → Paid Conversion | 25% | 70% | 2.8x |
| Sales Cycle (Days) | 90 | 30 | 3x faster |
| Sales Touches Required | 12 | 4 | 3x fewer |
| Total CAC | R25,000 | R7,500 | 3.3x lower |
Why AI Crushes CAC:
- Self-Selling Product: AI demo shows instant ROI (20 hours saved/week)
- Zero Competition: No comparison shopping when you're the only AI option
- Viral Referrals: Schools brag about having AI (status symbol)
- Shorter Cycle: Decision makers see value immediately
- Higher Intent: Inbound leads specifically seeking AI solution
Lifetime Value (LTV) Calculation
LTV Components by Tier
| Tier | Monthly Rev/Student | Gross Margin | Lifespan (Months) | LTV per Student | Students/School | LTV per School |
|---|---|---|---|---|---|---|
| Essentials | R133 | 75% | 36 | R3,591 | 150 | R538,650 |
| Professional | R200 | 78% | 48 | R7,488 | 300 | R2,246,400 |
| Enterprise | R300 | 82% | 60 | R14,760 | 500 | R7,380,000 |
| Blended | R215 | 78% | 48 | R8,265 | 250 | R2,066,250 |
Retention Curves by Cohort
| Month | Traditional Platform | YeboLearn Essentials | YeboLearn Professional | YeboLearn Enterprise |
|---|---|---|---|---|
| 0 | 100% | 100% | 100% | 100% |
| 6 | 85% | 92% | 95% | 97% |
| 12 | 72% | 85% | 90% | 94% |
| 24 | 52% | 72% | 81% | 89% |
| 36 | 37% | 61% | 73% | 85% |
| 48 | 26% | 52% | 66% | 81% |
| 60 | 18% | 44% | 59% | 77% |
AI-Driven Retention Factors:
- Data Lock-in: Years of student performance data in AI models
- Workflow Integration: AI touches every daily process
- Parent Dependency: Parents expect AI communication
- Switching Costs: Would lose all AI automation benefits
- Network Effects: Inter-school AI benchmarking
Expansion Revenue Impact on LTV
| Year | Base MRR | Expansion MRR | Total MRR | Expansion % | Cumulative LTV Increase |
|---|---|---|---|---|---|
| Year 1 | R200 | R0 | R200 | 0% | 0% |
| Year 2 | R200 | R30 | R230 | 15% | 15% |
| Year 3 | R200 | R50 | R250 | 25% | 40% |
| Year 4 | R200 | R70 | R270 | 35% | 75% |
| Year 5 | R200 | R90 | R290 | 45% | 120% |
Expansion Drivers:
- Tier upgrades (30% of schools/year)
- Add-on modules (AI counseling, AI athletics)
- Student growth (5-10% annually)
- Multi-campus expansion
- Parent premium features
LTV:CAC Ratios
Core Metrics by Segment
| Segment | LTV | CAC | LTV:CAC Ratio | Payback (Months) | 3-Year ROI |
|---|---|---|---|---|---|
| Small Schools | R538,650 | R4,500 | 119:1 | 1.0 | 11,870% |
| Medium Schools | R2,246,400 | R7,500 | 299:1 | 0.8 | 29,850% |
| Large Schools | R7,380,000 | R12,000 | 615:1 | 0.6 | 61,400% |
| Blended Average | R2,066,250 | R7,500 | 275:1 | 0.8 | 27,450% |
Comparative Analysis
| Company | Industry | LTV:CAC | Payback | Notes |
|---|---|---|---|---|
| Traditional EdTech | Education | 2:1 | 18 months | High churn, commoditized |
| PowerSchool | School Management | 3:1 | 12 months | Legacy, no AI |
| Zoom | Video/Education | 5:1 | 12 months | Best-in-class SaaS |
| YeboLearn | AI EdTech | 275:1 | 0.8 months | AI monopoly advantage |
Gross Margin Analysis
Margin by Component
| Cost Component | % of Revenue | Traditional EdTech | YeboLearn | Savings |
|---|---|---|---|---|
| Infrastructure (AWS) | 8% | 20% | 8% | 60% reduction |
| AI/ML Compute | 5% | N/A | 5% | Worth every rand |
| Customer Support | 4% | 15% | 4% | AI reduces tickets 73% |
| Payment Processing | 3% | 3% | 3% | Standard |
| Third-party APIs | 2% | 5% | 2% | Fewer integrations needed |
| Total COGS | 22% | 43% | 22% | 49% reduction |
| Gross Margin | 78% | 57% | 78% | 37% improvement |
Gross Margin by Tier
| Tier | Revenue/Student | COGS/Student | Gross Margin % | Gross Profit/Student |
|---|---|---|---|---|
| Essentials | R1,600/year | R400 | 75% | R1,200 |
| Professional | R2,400/year | R528 | 78% | R1,872 |
| Enterprise | R3,600/year | R648 | 82% | R2,952 |
AI Efficiency Gains:
- 73% reduction in support tickets (AI handles routine queries)
- 60% reduction in infrastructure (efficient AI models)
- 80% reduction in onboarding costs (AI automation)
- 90% reduction in training costs (AI self-service)
Payback Period Analysis
Payback by Acquisition Channel
| Channel | CAC | Month 1 Revenue | Gross Margin | Payback Period |
|---|---|---|---|---|
| Direct Sales | R1,488 | R1,800 | 78% | 1.1 months |
| Partner Referrals | R196 | R1,800 | 78% | 0.14 months |
| Inbound | R137 | R1,800 | 78% | 0.10 months |
| Word of Mouth | R0 | R1,800 | 78% | Immediate |
| Blended | R630 | R1,800 | 78% | 0.45 months |
Payback Period Evolution
| Quarter | Average CAC | Average Revenue | Payback Period | Industry Benchmark |
|---|---|---|---|---|
| Q1 2025 | R850 | R1,500 | 0.73 months | 18 months |
| Q2 2025 | R750 | R1,650 | 0.58 months | 18 months |
| Q3 2025 | R650 | R1,800 | 0.46 months | 18 months |
| Q4 2025 | R550 | R1,950 | 0.36 months | 18 months |
Cohort Economics
Monthly Cohort Performance
| Cohort | Size | Month 1 Rev | Month 6 Rev | Month 12 Rev | Month 24 Rev | Total LTV |
|---|---|---|---|---|---|---|
| Jan 2025 | 3 schools | R90,000 | R93,600 | R97,344 | R104,850 | R2,453,400 |
| Apr 2025 | 6 schools | R180,000 | R189,000 | R198,450 | R217,899 | R4,906,800 |
| Jul 2025 | 10 schools | R300,000 | R318,000 | R337,080 | R377,850 | R8,178,000 |
| Oct 2025 | 11 schools | R330,000 | R352,000 | R375,760 | R423,982 | R8,995,800 |
Cohort Insights:
- Later cohorts have higher LTV (better product)
- Expansion revenue accelerates over time
- Churn decreases as AI features deepen
- Word-of-mouth reduces acquisition costs
Unit Economics Sensitivity Analysis
Impact of Key Variables
| Variable | Base Case | -20% Impact | +20% Impact | LTV:CAC Change |
|---|---|---|---|---|
| Churn Rate (6%) | 275:1 | 220:1 (-20%) | 330:1 (+20%) | ±20% |
| Gross Margin (78%) | 275:1 | 247:1 (-10%) | 302:1 (+10%) | ±10% |
| CAC (R7,500) | 275:1 | 344:1 (+25%) | 229:1 (-17%) | +25%/-17% |
| Expansion Rate (25%) | 275:1 | 248:1 (-10%) | 312:1 (+13%) | -10%/+13% |
Path to Profitability
Monthly Profit Timeline
| Month | Revenue | COGS (22%) | OpEx | EBITDA | EBITDA Margin |
|---|---|---|---|---|---|
| Month 1 | R900,000 | R198,000 | R850,000 | -R148,000 | -16% |
| Month 3 | R3,600,000 | R792,000 | R1,200,000 | R1,608,000 | 45% |
| Month 6 | R9,900,000 | R2,178,000 | R2,000,000 | R5,722,000 | 58% |
| Month 9 | R20,100,000 | R4,422,000 | R3,000,000 | R12,678,000 | 63% |
| Month 12 | R30,000,000 | R6,600,000 | R4,000,000 | R19,400,000 | 65% |
Profitability Drivers:
- Gross margins improve with scale (78% → 82%)
- OpEx grows slower than revenue (40% → 13%)
- CAC decreases with brand strength
- Expansion revenue has 90%+ margins
Investment Efficiency Metrics
Capital Efficiency Ratios
| Metric | YeboLearn | SaaS Benchmark | Top Decile | Multiple |
|---|---|---|---|---|
| ARR per R1 invested | R4.62 | R0.80 | R1.50 | 5.8x benchmark |
| Months to cash flow positive | 3 | 24 | 18 | 8x faster |
| Revenue per employee | R1,500,000 | R350,000 | R650,000 | 4.3x benchmark |
| Magic Number | 3.8 | 0.75 | 1.5 | 5x benchmark |
| Rule of 40 Score | 143 | 25 | 60 | 5.7x benchmark |
Conclusion: Unit Economics That Break the Model
YeboLearn's unit economics aren't just good—they're unprecedented in EdTech. A 275:1 LTV:CAC ratio with sub-1 month payback periods doesn't happen in competitive markets. It only happens when you have a monopoly on transformative technology.
The AI Monopoly Math:
- Customer Acquisition: 3x lower CAC due to zero competition
- Lifetime Value: 5x higher LTV due to AI lock-in
- Gross Margins: 78% vs 57% industry average
- Combined Effect: 15x better unit economics
Bottom Line: These aren't sustainable long-term metrics—they're land-grab metrics. In 18 months when competitors have AI, these ratios will normalize to merely excellent (20:1). But by then, YeboLearn will have 200+ schools, R120M ARR, and an insurmountable data advantage.
The Window is Now: Every school acquired at 275:1 LTV:CAC is worth R2M+ in enterprise value. There will never be another opportunity like this in African EdTech.