User Analytics

User analytics provide deep insights into how different user types interact with YeboLearn. Understanding user segments, behaviors, and journeys enables personalized experiences and targeted interventions.

User Segmentation Framework

Primary Segmentation: By Role

User Distribution:

Role	Total Users	Active Weekly	Activity Rate	Avg Sessions/Week
Teachers	2,320	1,860	80%	8.5
Students	14,850	9,380	63%	4.2
Administrators	285	228	80%	3.1
Parents	8,450	1,520	18%	1.8
Total	25,905	12,988	50%	4.9

Role-Specific Insights:

• Teachers: Highest engagement, power users, primary decision-makers
• Students: Large volume, moderate engagement, end beneficiaries
• Administrators: High engagement, infrequent but strategic usage
• Parents: Low engagement, opportunity for growth

Secondary Segmentation: By Engagement Level

Engagement Tiers (Schools):

Tier	Schools	Definition	Retention	ARPU	Priority
Power Users	18 (12%)	8+ features, daily usage	98%	$3,200	Maintain excellence
High Engagement	45 (31%)	5-7 features, 4+ days/week	94%	$2,100	Expand capabilities
Medium Engagement	52 (36%)	3-4 features, 2-3 days/week	88%	$1,650	Drive feature discovery
Low Engagement	22 (15%)	1-2 features, <2 days/week	68%	$1,100	Activation campaigns
At-Risk	8 (6%)	Declining usage	42%	$850	Urgent intervention

Engagement Score Calculation:

Engagement Score =
  (Features used × 10) +
  (Weekly logins × 5) +
  (AI feature uses × 3) +
  (Collaboration actions × 8) +
  (Content created × 2)

Power User Example:
  (12 features × 10) + (20 logins × 5) + (45 AI uses × 3) +
  (15 collab × 8) + (85 content × 2)
  = 120 + 100 + 135 + 120 + 170 = 645 points

Tertiary Segmentation: By School Characteristics

By School Size:

Size Category	Schools	Avg Students	ARPU	Churn Rate	Preferred Tier
Small (<100)	48	68	$833	6.2%	Essentials
Medium (100-300)	85	185	$1,800	2.4%	Professional
Large (300+)	12	520	$4,500	1.2%	Enterprise

By School Type:

Type	Schools	Avg ARPU	Tech Adoption	Feature Usage
Private Independent	68	$2,200	High	8.2 features
Private Religious	42	$1,600	Medium	6.5 features
Public Progressive	28	$1,800	Medium	7.1 features
Charter/Model C	7	$1,900	High	7.8 features

By Geographic Region:

Region	Schools	Growth Rate	Avg ARPU	Competitive Intensity
Gauteng	58	61%	$1,850	High
Western Cape	38	58%	$1,720	Medium
KwaZulu-Natal	24	50%	$1,580	Low
Eastern Cape	15	67%	$1,450	Low
Other	10	67%	$1,550	Low

User Personas

Persona 1: Sarah - Progressive Teacher (Primary Persona)

Demographics:

• Age: 32
• Role: Grade 6 Teacher
• Experience: 8 years teaching
• Tech Savviness: High
• School Type: Private Independent

Goals:

• Reduce lesson planning time
• Personalize learning for students
• Track student progress effectively
• Collaborate with colleagues

Pain Points:

• Too much time on administrative tasks
• Difficulty differentiating instruction
• Limited resources for diverse learners
• Inconsistent student engagement

YeboLearn Usage Pattern:

• Logs in: 12 times/week (daily + weekends)
• Features used: 9 features regularly
• Top features: AI Lesson Planner, Quiz Generator, Auto-Grading
• Session duration: 28 minutes avg
• AI usage: 35 requests/week

Engagement Level: Power User

Value Delivered:

• Saves 12 hours/week on planning and grading
• Creates more engaging, differentiated lessons
• Better insights into student performance
• Professional development through feature exploration

Quote: "YeboLearn has transformed how I teach. I spend less time on busywork and more time with my students."

Persona 2: David - Tech-Skeptical Teacher

Demographics:

• Age: 48
• Role: High School Math Teacher
• Experience: 22 years teaching
• Tech Savviness: Low-Medium
• School Type: Public Progressive

Goals:

• Maintain teaching quality
• Reduce grading burden
• Meet curriculum requirements
• Avoid complexity

Pain Points:

• Overwhelmed by new technology
• Skeptical of AI accuracy
• Limited time to learn new tools
• Pressure from administration to adopt tech

YeboLearn Usage Pattern:

• Logs in: 4 times/week
• Features used: 3 features (Auto-Grading, Resource Library, Progress Tracking)
• Session duration: 18 minutes avg
• AI usage: 5 requests/week (growing slowly)

Engagement Level: Medium Engagement

Value Delivered:

• Easier grading with minimal learning curve
• Access to quality math resources
• Simple student tracking
• Builds confidence with gradual AI adoption

Quote: "I was skeptical, but the auto-grading actually works. It's saved me hours every week."

Onboarding Needs: Simplified workflow, step-by-step guidance, reassurance about AI accuracy

Persona 3: Jessica - School Administrator

Demographics:

• Age: 42
• Role: Deputy Principal
• Experience: 15 years in education (5 as admin)
• Tech Savviness: Medium
• School Type: Private Independent

Goals:

• Monitor school-wide performance
• Ensure curriculum compliance
• Support teacher effectiveness
• Justify technology investments to board

Pain Points:

• Limited visibility into classroom activities
• Difficulty tracking curriculum coverage
• Hard to identify struggling students early
• ROI justification for edtech tools

YeboLearn Usage Pattern:

• Logs in: 3 times/week
• Features used: Student Analytics, Curriculum Alignment, Progress Tracking
• Session duration: 32 minutes avg
• Focus: Reporting and oversight, not creation

Engagement Level: High Engagement (different usage pattern)

Value Delivered:

• School-wide performance dashboards
• Curriculum coverage verification
• Early warning system for at-risk students
• Clear ROI metrics for board presentations

Quote: "YeboLearn gives me the data I need to support our teachers and prove our investment is working."

Persona 4: Thabo - Student (Secondary User)

Demographics:

• Age: 14
• Grade: 9
• Tech Savviness: High (digital native)
• Device: Shared tablet at school

Goals:

• Understand lessons better
• Get good grades
• Learn at own pace
• Access materials anytime

Pain Points:

• Some subjects are confusing
• Limited access to teacher outside class
• Forgets homework deadlines
• Wants more practice materials

YeboLearn Usage Pattern:

• Logs in: 5 times/week (mostly during school hours)
• Features accessed: Assigned quizzes, resources, progress tracking
• Session duration: 15 minutes avg
• Mobile usage: 60% (tablet/phone)

Engagement Level: Medium (depends on teacher's usage)

Value Delivered:

• Self-paced quiz practice
• Access to extra resources
• Visibility into own progress
• Instant feedback on assignments

Quote: "I like that I can see my grades right away and practice more if I need to."

User Behavior Patterns

Teacher Behavior Patterns

Weekly Activity Pattern:

Monday:    ████████████████░░░░ 80% (week planning)
Tuesday:   ███████████████░░░░░ 75% (teaching)
Wednesday: ██████████████░░░░░░ 70% (mid-week)
Thursday:  █████████████░░░░░░░ 65% (teaching)
Friday:    ████████░░░░░░░░░░░░ 40% (wind down)
Saturday:  ██████░░░░░░░░░░░░░░ 30% (optional planning)
Sunday:    ███████████░░░░░░░░░ 55% (next week prep)

Daily Activity Pattern (UTC+2):

6am-8am:   ███████░░░ Morning prep (planning at home)
8am-10am:  █████████████ Peak usage (teaching hours)
10am-12pm: ███████████░ High usage (continued teaching)
12pm-2pm:  ████░░░░░░░ Lunch dip
2pm-4pm:   ██████████░ Afternoon classes
4pm-6pm:   ████████░░░ After-school grading
6pm-8pm:   ████░░░░░░░ Evening planning
8pm+:      ██░░░░░░░░░ Minimal usage

Feature Usage Sequence (Most Common):

1. Login → Dashboard (100%)
2. Dashboard → AI Lesson Planner (42%)
3. Lesson Planner → Quiz Generator (35%)
4. Quiz Generator → Save/Share (28%)
5. Return later → Auto-Grading (65%)

Session Types:

• Quick Check (5 min): Check student submissions, review grades
• Planning Session (25 min): Create lessons, build quizzes
• Grading Session (15 min): Review and grade assignments
• Deep Work (45+ min): Comprehensive lesson planning, resource curation

Student Behavior Patterns

Weekly Activity Pattern:

Monday:    ███████████░░░░░░░░░ 55% (new week motivation)
Tuesday:   ████████████░░░░░░░░ 60% (active learning)
Wednesday: █████████████░░░░░░░ 65% (peak engagement)
Thursday:  ████████████░░░░░░░░ 60% (continued work)
Friday:    ███████░░░░░░░░░░░░░ 35% (weekend anticipation)
Saturday:  ██░░░░░░░░░░░░░░░░░░ 10% (minimal)
Sunday:    ████░░░░░░░░░░░░░░░░ 20% (homework catch-up)

Daily Activity Pattern:

8am-10am:  ████░░░░░░░ Early class time
10am-12pm: ██████░░░░░ Mid-morning classes
12pm-2pm:  ███████████ Peak usage (lunch, free periods)
2pm-4pm:   █████████████ Afternoon classes (peak)
4pm-6pm:   ████████░░░ After school homework
6pm+:      ███░░░░░░░░ Evening work (declining)

Feature Interaction:

• Primarily passive: Complete assigned quizzes, view materials
• Limited creation: Rarely create content
• Mobile-heavy: 60% of sessions on mobile devices
• Short sessions: 15 minutes average vs 24 for teachers

Administrator Behavior Patterns

Usage Frequency: 3 times/week (strategic, not daily)

Typical Session:

1. Login → Dashboard overview
2. Review school-wide metrics
3. Drill into specific classes/teachers
4. Export reports
5. Check curriculum alignment
6. Logout

Peak Times: Monday mornings (week planning), Thursday afternoons (weekly review)

Report Types Accessed:

• Student performance summaries: 68%
• Curriculum coverage reports: 52%
• Teacher usage statistics: 38%
• Parent engagement metrics: 22%

User Journey Analysis

Teacher Journey: Signup to Power User

Journey Stages:

Stage 1: Signup (Day 0)
→ 100% of new teachers
Action: Create account, basic setup

Stage 2: Onboarding (Days 1-7)
→ 95% complete onboarding
Actions: Import classes, invite students, explore features
Drop-off: 5% never complete setup

Stage 3: First Value (Days 8-14)
→ 85% reach first value moment
Actions: Create first lesson, generate first quiz, grade first assignment
Drop-off: 10% don't find initial value

Stage 4: Regular Usage (Days 15-60)
→ 72% become regular weekly users
Actions: Use 3-5 features regularly, establish routine
Drop-off: 13% stop using regularly

Stage 5: Feature Expansion (Days 61-120)
→ 48% adopt additional features
Actions: Try new features, integrate more into workflow
Drop-off: 24% plateau at basic features

Stage 6: Power User (Days 121+)
→ 18% become power users
Actions: 8+ features, daily usage, advocate to colleagues
Retention: 98% annual retention

Conversion Rates:

• Signup → Regular User: 72%
• Regular User → Feature Expander: 67%
• Feature Expander → Power User: 38%
• Overall Signup → Power User: 18%

Journey Optimization Opportunities:

1. Onboarding → First Value: Reduce time from 8 days to 5 days (target)
2. First Value → Regular Usage: Increase conversion from 85% to 90%
3. Regular → Power User: Double conversion from 18% to 36%

Student Journey: Invitation to Active Learner

Journey Stages:

Stage 1: Invitation (Day 0)
→ 100% of students invited
Action: Teacher sends invite via email/platform

Stage 2: Account Activation (Days 1-3)
→ 88% activate account
Action: Click invite, set password, login
Drop-off: 12% never activate

Stage 3: First Assignment (Days 4-7)
→ 82% complete first assignment
Action: Access quiz/material, complete, submit
Drop-off: 6% login but don't complete work

Stage 4: Regular Participation (Days 8-30)
→ 68% participate weekly
Action: Complete 2+ assignments/week
Drop-off: 14% sporadic participation

Stage 5: Active Learner (Day 31+)
→ 63% become active learners
Action: Consistent weekly engagement, self-directed learning
Retention: 92% continue through semester

Activation Challenges:

• 12% of students never activate (email delivery, tech access issues)
• 6% login once but don't complete assignments (confusion, motivation)
• 14% sporadic participation (inconsistent teacher usage, tech barriers)

Student Activation Tactics:

• SMS reminders in addition to email (for low email access)
• Simplified mobile interface (many students use phones)
• Gamification elements (points, badges for engagement)
• Teacher training on consistent assignment cadence

Cohort Analysis

User Retention Cohorts

Teacher Retention (by signup month):

Cohort	Month 0	Month 1	Month 3	Month 6	Month 12
Jan 2025	100%	92%	88%	85%	82%
Apr 2025	100%	94%	90%	87%	-
Jul 2025	100%	95%	91%	-	-
Oct 2025	100%	96%	-	-	-

Improvement Trend: Recent cohorts have better retention (onboarding improvements)

Student Retention (semester-based):

Cohort	Week 1	Week 4	Week 8	Week 12	Semester End
Term 1 2025	100%	88%	78%	72%	68%
Term 2 2025	100%	90%	82%	76%	72%
Term 3 2025	100%	92%	85%	80%	75%

Improvement Trend: Student retention improving (better teacher training, mobile experience)

Feature Adoption Cohorts

AI Lesson Planner Adoption (by school signup date):

School Cohort	Day 7	Day 30	Day 60	Day 90	Current
Q1 2025 Schools	42%	68%	78%	82%	88%
Q2 2025 Schools	58%	75%	84%	88%	90%
Q3 2025 Schools	65%	82%	88%	90%	92%
Q4 2025 Schools	72%	86%	-	-	88%

Insights:

• Newer schools adopt AI Lesson Planner faster (improved onboarding)
• Day 7 adoption increased from 42% to 72% (71% improvement)
• Mature schools continue to adopt over time (long tail adoption)

Revenue Cohorts

Cohort LTV Analysis (12-month cohorts):

Signup Cohort	Schools	Starting ARPU	Current ARPU	Revenue Growth	Churn
Q1 2024	28	$1,450	$2,100	+45%	14%
Q2 2024	36	$1,520	$2,050	+35%	12%
Q3 2024	42	$1,580	$1,950	+23%	10%
Q4 2024	54	$1,650	$1,850	+12%	8%

Insights:

• ARPU grows significantly over customer lifetime (upgrades, expansion)
• Churn decreases with improved onboarding and product
• Newer cohorts start at higher ARPU (better tier fit, pricing improvements)

User Segmentation Strategies

Personalization by Segment

Power Users:

• Early access to beta features
• Invite to advisory board
• Premium support (priority queue)
• Case study opportunities
• Referral program incentives

High Engagement:

• Feature discovery prompts (try new features)
• Upgrade messaging (Enterprise features)
• Collaboration opportunities (connect with power users)
• Advanced training webinars

Medium Engagement:

• Regular feature tips and best practices
• Success stories from similar schools
• Onboarding refresher campaigns
• Usage reports (show value delivered)

Low Engagement:

• Simplified workflows
• One-on-one training sessions
• Feature highlight campaigns
• "Quick wins" focused messaging

At-Risk:

• Urgent CSM outreach
• Executive-level conversations
• Custom onboarding plans
• Win-back offers

Targeted Interventions

New User Onboarding (Days 1-30):

• Day 1: Welcome email + setup guide
• Day 3: First feature tutorial
• Day 7: Check-in email (completed steps)
• Day 14: Feature discovery prompt
• Day 30: Success review + next steps

Engagement Boosting (Low→Medium):

• Highlight unused features relevant to role
• Share peer success stories
• Offer personalized training
• Set achievable usage goals

Expansion Campaigns (Medium→High):

• Introduce advanced features
• Cross-feature workflows
• Power user community access
• Advanced certification program

Retention Campaigns (At-Risk):

• Personal outreach within 24 hours
• Identify and address specific pain points
• Offer extended support
• Custom training plan
• Executive check-in

User Analytics Dashboard

Key Metrics by Segment:

Segment	Users	WAU	Engagement Score	Retention	ARPU
Power Users (Schools)	18	18 (100%)	645	98%	$3,200
High Engagement	45	42 (93%)	385	94%	$2,100
Medium Engagement	52	39 (75%)	215	88%	$1,650
Low Engagement	22	12 (55%)	95	68%	$1,100
At-Risk	8	3 (38%)	35	42%	$850

User Growth Trends:

• Power Users: Growing 2-3 schools/quarter
• High Engagement: Growing 8-10 schools/quarter
• Medium Engagement: Stable (churn = new adds)
• Low Engagement: Shrinking (moving up or churning)
• At-Risk: 5-8 schools at any time (revolving)

Next Steps

• Product Analytics - Overall product analytics framework
• Feature Analytics - Feature-specific performance
• Product Dashboards - Real-time user monitoring
• Growth Metrics - Acquisition and activation metrics