Growth Metrics
YeboLearn's growth metrics track customer acquisition, activation, retention, and expansion. These metrics inform go-to-market strategy, sales optimization, and product-led growth initiatives.
Acquisition Metrics
School Acquisition Rate
Definition: Net new paying schools added per month
Current Performance: 12-15 new schools per month (averaging 13.5)
Target: 25+ new schools per month by Q2 2026
Monthly Acquisition Trends:
| Month | New Schools | Churned Schools | Net Growth | Growth Rate |
|---|---|---|---|---|
| Aug 2025 | 14 | 6 | +8 | +6.0% |
| Sep 2025 | 12 | 5 | +7 | +5.1% |
| Oct 2025 | 15 | 4 | +11 | +7.9% |
| Nov 2025 | 13 | 3 | +10 | +7.0% |
| Avg Q4 | 13.5 | 4.5 | +9 | +6.5% |
Quarterly Comparison:
| Quarter | New Schools | Avg/Month | QoQ Growth |
|---|---|---|---|
| Q1 2025 | 28 | 9.3 | - |
| Q2 2025 | 36 | 12.0 | +28.6% |
| Q3 2025 | 42 | 14.0 | +16.7% |
| Q4 2025 | 54 | 18.0 | +28.6% |
Target for 2026: 300 new schools annually (25/month average)
Acquisition by Channel
Channel Performance (Last 90 Days):
| Channel | New Schools | % of Total | CAC | LTV:CAC | Conversion Rate |
|---|---|---|---|---|---|
| LinkedIn Outbound | 18 | 36% | $2,100 | 20.2:1 | 4.2% |
| Email Campaigns | 15 | 30% | $1,200 | 35.4:1 | 7.8% |
| WhatsApp Marketing | 8 | 16% | $1,600 | 26.6:1 | 5.5% |
| Referrals | 6 | 12% | $400 | 106:1 | 38% |
| Inbound (Website) | 3 | 6% | $800 | 53.1:1 | 12% |
| Total | 50 | 100% | $1,620 | 26.2:1 | 6.8% |
Channel Insights:
- Referrals: Highest efficiency, lowest CAC, highest conversion
- Email: Best balance of volume and efficiency
- LinkedIn: Highest volume, acceptable efficiency
- Inbound: Low volume but high quality leads
Channel Investment Strategy:
- Maximize: Referral program (incentivize existing customers)
- Scale: Email campaigns (proven efficiency)
- Optimize: LinkedIn (improve targeting to reduce CAC)
- Test: Inbound content marketing (increase volume)
Acquisition by Region
Geographic Distribution (Active Schools):
| Region | Schools | % of Total | New in Q4 | Growth Rate |
|---|---|---|---|---|
| Gauteng | 58 | 40% | 22 | +61% |
| Western Cape | 38 | 26% | 14 | +58% |
| KwaZulu-Natal | 24 | 17% | 8 | +50% |
| Eastern Cape | 15 | 10% | 6 | +67% |
| Other Provinces | 10 | 7% | 4 | +67% |
| Total | 145 | 100% | 54 | 59% |
Regional Opportunity:
- Gauteng: Largest market, maintain dominance
- Western Cape: Strong growth, increase investment
- KZN: Underserved, opportunity for expansion
- Eastern Cape: High growth rate, emerging market
Acquisition by School Type
School Type Breakdown:
| School Type | Schools | Avg Students | Avg MRR | LTV | CAC Efficiency |
|---|---|---|---|---|---|
| Private Independent | 68 | 420 | $2,200 | $78,500 | Excellent |
| Private Religious | 42 | 280 | $1,600 | $57,100 | Good |
| Public (Progressive) | 28 | 680 | $1,800 | $64,300 | Good |
| Charter/Model C | 7 | 520 | $1,900 | $67,800 | Excellent |
| Total | 145 | 450 | $1,703 | $47,429 | Good |
Target Market Prioritization:
- Primary: Private Independent (best economics, fastest sales cycle)
- Secondary: Charter/Model C (good economics, growing segment)
- Opportunistic: Progressive Public schools (longer sales, good retention)
Pipeline Velocity
Definition: Speed at which deals move through sales pipeline
Current Performance: 38 days average (from lead to closed-won)
Target: 30-45 days (currently within target range)
Sales Cycle by Stage:
| Stage | Avg Days | % of Cycle | Target | Status |
|---|---|---|---|---|
| Lead → Qualified | 5 days | 13% | 3-7 days | Good |
| Qualified → Demo | 8 days | 21% | 5-10 days | Good |
| Demo → Proposal | 12 days | 32% | 10-15 days | Good |
| Proposal → Negotiation | 7 days | 18% | 5-10 days | Good |
| Negotiation → Closed | 6 days | 16% | 3-7 days | Good |
| Total Cycle | 38 days | 100% | 30-45 days | On Target |
Velocity by Deal Size:
| Tier | Avg Deal Value | Sales Cycle | Win Rate |
|---|---|---|---|
| Enterprise ($4,500/mo) | $54,000 ARR | 62 days | 35% |
| Professional ($1,800/mo) | $21,600 ARR | 35 days | 48% |
| Essentials ($833/mo) | $10,000 ARR | 22 days | 62% |
Insight: Longer sales cycles for Enterprise justified by higher deal value and win rate
Pipeline Coverage
Definition: Ratio of pipeline value to quarterly revenue target
Current Performance: 3.2x pipeline coverage
Target: 3-4x coverage (healthy pipeline)
Q1 2026 Pipeline (as of Nov 30):
| Stage | Opportunities | Total Value | Weighted Value | Close Probability |
|---|---|---|---|---|
| Qualified | 45 | $1,280,000 | $256,000 | 20% |
| Demo Completed | 32 | $890,000 | $356,000 | 40% |
| Proposal Sent | 18 | $520,000 | $312,000 | 60% |
| Negotiation | 12 | $380,000 | $304,000 | 80% |
| Total Pipeline | 107 | $3,070,000 | $1,228,000 | 40% |
Q1 Target: $390,000 new ARR Pipeline Coverage: $3,070,000 / $390,000 = 7.9x (unweighted), 3.2x (weighted)
Status: Healthy pipeline, exceeds target coverage
Activation Metrics
Time to Value (TTV)
Definition: Days from signup to achieving first meaningful outcome
Current Performance: 8.5 days average
Target: <14 days (75%+ of schools activated within 2 weeks)
First Value Milestones:
| Milestone | Avg Days | % Achieving | Impact on Retention |
|---|---|---|---|
| First login | 0.5 days | 98% | Baseline |
| First feature used | 2.1 days | 92% | +15% retention |
| First lesson created | 4.8 days | 85% | +28% retention |
| First quiz generated | 6.2 days | 78% | +35% retention |
| 5+ features used | 8.5 days | 75% | +52% retention |
| First AI feature used | 3.5 days | 88% | +42% retention |
"Activated" Definition: School reaches 5+ features used within 14 days
Activation Rate:
| Month | New Schools | Activated (14d) | Activation Rate |
|---|---|---|---|
| Aug 2025 | 14 | 9 | 64% |
| Sep 2025 | 12 | 9 | 75% |
| Oct 2025 | 15 | 12 | 80% |
| Nov 2025 | 13 | 11 | 85% |
Target: 75%+ activation rate (currently exceeding)
Onboarding Completion Rate
Definition: Percentage of schools completing onboarding checklist
Current Performance: 72% complete onboarding within 30 days
Target: 80%+ onboarding completion
Onboarding Checklist (8 steps):
| Step | % Completed | Avg Days | Completion Impact |
|---|---|---|---|
| 1. Account setup | 100% | 0.2 | Required |
| 2. Import students/classes | 95% | 1.5 | High |
| 3. Invite teachers | 88% | 2.8 | High |
| 4. Create first lesson | 85% | 4.8 | Critical |
| 5. Try AI feature | 82% | 3.5 | Critical |
| 6. Generate first quiz | 78% | 6.2 | Medium |
| 7. Set up grading | 74% | 7.5 | Medium |
| 8. Complete training | 72% | 12.0 | Low priority |
Completion vs Retention:
- 0-3 steps: 42% annual retention
- 4-5 steps: 68% annual retention
- 6-7 steps: 86% annual retention
- 8 steps: 94% annual retention
Improvement Initiatives:
- Add in-app guidance for steps 6-8
- Send automated reminders at days 7, 14, and 21
- Assign Customer Success Manager at day 10 if <5 steps complete
First Week Engagement
Definition: User activity in first 7 days after school signup
Key Metrics (Average per new school):
| Metric | Current | Target | Impact |
|---|---|---|---|
| Teacher logins (first week) | 4.2 | 5+ | High |
| Features tried | 6.8 | 7+ | Critical |
| Lessons created | 3.5 | 5+ | High |
| AI features used | 8.2 | 10+ | High |
| Students invited | 85% of school | 90%+ | Medium |
| Total engagement hours | 12.4 | 15+ | Critical |
First Week Cohorts:
| Engagement Level | Schools | % of New | 90-Day Retention |
|---|---|---|---|
| High (15+ hours) | 18 | 35% | 94% |
| Medium (8-15 hours) | 22 | 42% | 78% |
| Low (3-8 hours) | 8 | 15% | 52% |
| Very Low (❤️ hours) | 4 | 8% | 28% |
Target: Move "Low" schools to "Medium" through proactive CSM outreach
Feature Discovery in First 30 Days
Average Features Discovered: 8.4 features (out of 15+ available)
Target: 10+ features discovered in first 30 days
Discovery Pattern:
| Week | Cumulative Features | New This Week |
|---|---|---|
| Week 1 | 5.2 | 5.2 |
| Week 2 | 7.1 | 1.9 |
| Week 3 | 8.0 | 0.9 |
| Week 4 | 8.4 | 0.4 |
Insight: Feature discovery slows significantly after week 2. Need better ongoing education.
Retention Metrics
School Retention Cohorts
12-Month Retention by Signup Cohort:
| Signup Month | Starting Schools | 3mo | 6mo | 9mo | 12mo | Annual Retention |
|---|---|---|---|---|---|---|
| Nov 2023 | 12 | 12 | 11 | 11 | 10 | 83% |
| Feb 2024 | 18 | 17 | 16 | 16 | 16 | 89% |
| May 2024 | 22 | 22 | 21 | 20 | 19 | 86% |
| Aug 2024 | 28 | 27 | 26 | 25 | 25 | 89% |
| Nov 2024 | 18 | 18 | 17 | 17 | - | 94% (9mo) |
| Feb 2025 | 22 | 22 | 21 | - | - | 95% (6mo) |
| May 2025 | 28 | 28 | - | - | - | 100% (3mo) |
| Aug 2025 | 32 | 31 | - | - | - | 97% (3mo) |
Overall 12-Month Retention: 88%
Target: 88%+ annual retention (currently at target)
Retention Improvement Trend: Recent cohorts showing stronger retention (better onboarding, product improvements)
Retention by Tier
Annual Retention Rates:
| Tier | Annual Retention | Median Tenure | Churn Reasons |
|---|---|---|---|
| Enterprise | 98% | 28 months | Budget (rare) |
| Professional | 91% | 22 months | Budget, features |
| Essentials | 76% | 14 months | Budget, competition |
| Blended | 88% | 21 months | Mixed |
Insight: Clear correlation between tier and retention. Focus on upgrading Essentials to Professional.
Cohort Retention Curves
Retention Decay Pattern:
| Month | Expected Retention | Actual Retention | Variance |
|---|---|---|---|
| Month 1 | 100% | 100% | - |
| Month 3 | 97% | 98% | +1% |
| Month 6 | 92% | 94% | +2% |
| Month 9 | 89% | 91% | +2% |
| Month 12 | 86% | 88% | +2% |
| Month 18 | 82% | 85% | +3% |
| Month 24 | 78% | 81% | +3% |
YeboLearn consistently outperforms expected retention by 2-3%
Key Retention Drivers:
- Feature adoption (5+ features = 91% retention)
- AI usage (weekly AI users = 94% retention)
- Multi-teacher adoption (3+ teachers = 96% retention)
- Student engagement (high student usage = 93% retention)
Churn Risk Indicators
Early Warning Signals:
| Risk Indicator | Weight | Current Schools at Risk |
|---|---|---|
| ❤️ features used in 30 days | High | 8 schools |
| Zero AI usage in 14 days | High | 12 schools |
| <50% expected usage | Medium | 15 schools |
| Single teacher using platform | Medium | 18 schools |
| No logins in 7 days | Critical | 5 schools |
| Support tickets unresolved >7 days | High | 3 schools |
| Total At-Risk | - | 28 schools (19%) |
Churn Prevention Actions:
- Critical risk (no logins 7+ days): CSM outreach within 24 hours
- High risk: Schedule check-in call, offer training session
- Medium risk: Automated email with tips, feature highlights
Churn Prevention Success Rate: 65% (prevented churn in 13 of 20 at-risk schools in Q3)
Expansion Metrics
Expansion Revenue
Definition: Additional revenue from existing customers (upgrades, add-ons)
Current Performance: $7,200 expansion MRR per month
Target: 30% of new MRR from expansion (currently at 40% - exceeding)
Expansion Revenue Composition:
| Expansion Type | Monthly MRR | % of Total | Schools |
|---|---|---|---|
| Tier upgrades (Ess→Pro) | $2,800 | 39% | 3 schools |
| Tier upgrades (Pro→Ent) | $3,600 | 50% | 2 schools |
| Student count increases | $600 | 8% | 8 schools |
| Add-on features | $200 | 3% | 4 schools |
| Total Expansion | $7,200 | 100% | 17 schools |
Expansion Rate: 11.7% of customer base generates expansion MRR monthly
Upsell Conversion Rate
Definition: Percentage of schools upgrading tiers
Essentials → Professional:
- Eligible schools: 48 Essentials customers
- Upgraded in Q4: 8 schools
- Quarterly conversion rate: 17%
- Target: 15%+ quarterly (exceeding)
Professional → Enterprise:
- Eligible schools: 85 Professional customers
- Upgraded in Q4: 6 schools
- Quarterly conversion rate: 7%
- Target: 5%+ quarterly (exceeding)
Upsell Triggers:
| Trigger | Conversion Rate | Time to Upsell |
|---|---|---|
| Student count >100 (Ess) | 45% | 4.2 months |
| Student count >300 (Pro) | 38% | 5.8 months |
| Using 8+ features | 32% | 3.5 months |
| Heavy AI usage (50+/week) | 28% | 2.8 months |
| Multiple teacher adoption | 25% | 4.0 months |
| Request for enterprise features | 72% | 1.2 months |
Strategic Focus: Proactively reach out when schools hit trigger conditions
Net Revenue Retention (NRR)
Definition: Revenue retained from cohort including expansion and churn
Current Performance: 118% NRR (last 12 months)
Target: 110%+ NRR (currently exceeding)
NRR Breakdown by Cohort:
| Cohort | Starting MRR | Retained MRR | Expansion | Churn | NRR |
|---|---|---|---|---|---|
| Nov 2023 | $18,500 | $15,200 | +$3,800 | -$6,100 | 103% |
| Feb 2024 | $28,500 | $25,400 | +$8,200 | -$11,300 | 118% |
| May 2024 | $35,200 | $31,800 | +$9,600 | -$13,000 | 120% |
| Aug 2024 | $42,800 | $39,200 | +$11,400 | -$14,900 | 118% |
| Average | - | - | - | - | 118% |
NRR >110% indicates strong product-market fit and expansion opportunity
Cross-Sell Success
Definition: Adoption of additional features by existing customers
Average Features at Signup: 3.2 features
Average Features at 12 Months: 7.8 features (+4.6 features)
Feature Expansion Pattern:
| Month | Avg Features Used | Feature Growth |
|---|---|---|
| Month 1 | 3.2 | Baseline |
| Month 3 | 5.1 | +1.9 |
| Month 6 | 6.4 | +1.3 |
| Month 9 | 7.2 | +0.8 |
| Month 12 | 7.8 | +0.6 |
Cross-Sell Opportunities:
| Current Usage | Next Best Feature | Adoption Rate | Upsell Potential |
|---|---|---|---|
| Lesson Planner only | Quiz Generator | 68% | Medium ($0) |
| Quiz Generator only | Auto-Grading | 72% | High ($600/mo) |
| Basic features | AI features | 58% | High ($800/mo) |
| 5-7 features | Parent Portal | 42% | Medium ($200/mo) |
| No analytics | Student Analytics | 38% | High ($400/mo) |
Viral Growth Metrics
Viral Coefficient (K-Factor)
Definition: Average number of new customers each customer refers
Current Performance: K = 0.42
Target: K > 0.5 (self-sustaining growth requires K > 1)
Viral Coefficient Calculation:
Referral invites per customer: 2.8 invites
Conversion rate of referrals: 15%
K = 2.8 × 0.15 = 0.42Interpretation: Each customer brings 0.42 new customers through referrals
To achieve K = 1.0:
- Increase invites to 5 per customer (at 15% conversion), OR
- Increase conversion to 36% (at 2.8 invites), OR
- Balanced approach: 3.5 invites at 28% conversion
Referral Program Performance
Active Referral Program: Refer a school, get $500 credit + 1 month free
Referral Statistics (Last 90 Days):
| Metric | Value |
|---|---|
| Schools in referral program | 82 (57%) |
| Total referrals sent | 230 invites |
| Referrals converted | 6 schools |
| Conversion rate | 2.6% |
| Avg referrals per participating school | 2.8 |
| CAC for referred schools | $400 |
Referral Sources:
| Source Type | Referrals | Conversions | Conversion Rate |
|---|---|---|---|
| Direct peer (same district) | 85 | 4 | 4.7% |
| Conference/event introduction | 42 | 1 | 2.4% |
| Email invitation | 68 | 1 | 1.5% |
| Social media mention | 35 | 0 | 0% |
Highest converting referrals: Peer-to-peer within same district
Referral Program Improvements:
- Increase incentive for referrer ($500 → $750)
- Add incentive for referred school (1 month → 2 months free)
- Create "refer your district" campaign with group discounts
- Build in-app referral flow (currently email-based)
Word-of-Mouth Attribution
Estimated WOM Influence: 38% of new schools cite peer recommendation as factor
Attribution Source (New Schools Survey):
| Source | Schools | % of Total |
|---|---|---|
| Peer recommendation | 19 | 38% |
| Online search | 12 | 24% |
| LinkedIn ad | 9 | 18% |
| Email outreach | 7 | 14% |
| Conference/event | 3 | 6% |
Net Promoter Score (NPS): 58 (Excellent for B2B SaaS)
NPS Breakdown:
- Promoters (9-10): 68%
- Passives (7-8): 22%
- Detractors (0-6): 10%
NPS by Tier:
- Enterprise: 72 (Exceptional)
- Professional: 61 (Excellent)
- Essentials: 42 (Good)
User-Generated Content
Organic Content Creation:
| Platform | Monthly Mentions | Sentiment | Reach |
|---|---|---|---|
| Twitter/X | 42 | 85% positive | 18,500 |
| 28 | 92% positive | 24,000 | |
| Facebook Groups | 15 | 78% positive | 8,200 |
| Teacher forums | 12 | 88% positive | 5,400 |
Case Studies Published: 8 schools (5.5% of customer base)
Video Testimonials: 4 schools
Target: 10% of customers creating content/testimonials by Q4 2026
Growth Targets (2026)
Annual Goals:
| Metric | Current | Q2 2026 | Q4 2026 | Growth Required |
|---|---|---|---|---|
| Monthly New Schools | 13.5 | 20 | 25 | +85% |
| Activation Rate | 80% | 82% | 85% | +5 pts |
| 12-Month Retention | 88% | 89% | 90% | +2 pts |
| Expansion Rate | 12% | 14% | 15% | +3 pts |
| NRR | 118% | 120% | 125% | +7 pts |
| Viral Coefficient | 0.42 | 0.60 | 0.80 | +90% |
| Pipeline Coverage | 3.2x | 3.5x | 4.0x | +25% |
Strategic Initiatives to Achieve Targets:
- Acquisition: Scale LinkedIn and email campaigns, launch partner program
- Activation: Improve onboarding, add AI-powered setup wizard
- Retention: Proactive CSM for at-risk accounts, feature education campaigns
- Expansion: Automated upsell prompts, usage-based upgrade recommendations
- Viral: Enhanced referral program, community building, case study production
Monitoring and Alerts
Growth Health Alerts
Critical (Immediate Review):
- New school acquisitions <8 in any month
- Activation rate <70% for 2+ consecutive weeks
- Churn rate >5% in single month
- Pipeline coverage <2.5x
Warning (Review Within 24 Hours):
- Acquisition trending <10 schools/month
- Activation rate declining 5+ points month-over-month
- 10+ schools showing churn risk signals
- Pipeline velocity >50 days
Opportunity (Weekly Review):
- 5+ schools meeting upsell criteria
- Referral conversion rate >5% (capitalize)
- Feature adoption spike indicating expansion opportunity
- Geographic expansion opportunity (high inbound from new region)
Next Steps
- Business Metrics - Revenue, profitability, and financial health
- Product Metrics - Engagement and feature adoption
- Sales Analytics - Pipeline and conversion deep-dive
- Marketing Analytics - Channel performance and attribution