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Product Metrics ​

YeboLearn's product metrics track how schools, teachers, and students engage with our platform. These metrics inform product decisions, prioritize roadmap items, and identify opportunities for improvement.

Engagement Metrics ​

Daily Active Schools (DAS) ​

Definition: Unique schools with at least one user login AND feature usage in a 24-hour period

Current Performance: 109 schools/day (75% of active customer base)

Target: 75%+ of total active schools (maintaining current level)

DAS Calculation:

Daily Active School criteria:
1. At least 1 teacher or student login
2. At least 1 feature interaction (not just dashboard view)
3. Activity timestamp within 24-hour UTC period

Excludes: API-only activity, automated tasks, admin-only logins

DAS Trends (Last 30 Days):

WeekDASActive SchoolsDAS %Week-over-Week
Week 1 (Nov 1-7)10614374%-
Week 2 (Nov 8-14)10814475%+1.9%
Week 3 (Nov 15-21)10914575%+0.9%
Week 4 (Nov 22-28)11114577%+1.8%
Average10914475%+1.5%

DAS by Day of Week:

DayAvg DAS% of SchoolsPattern
Monday11881%Highest (week planning)
Tuesday11579%High (full teaching)
Wednesday11277%High (mid-week)
Thursday11076%Moderate
Friday9868%Lower (week winding down)
Saturday4229%Low (weekend)
Sunday3826%Lowest (weekend prep)

Insights:

  • Strong weekday engagement (Monday-Thursday)
  • Weekend usage primarily from teachers planning next week
  • Opportunity: Increase Friday engagement with weekly recap features

DAS by Subscription Tier:

TierSchoolsAvg DASDAS %Engagement Level
Enterprise1212100%Exceptional
Professional857285%Strong
Essentials482552%Moderate
Total14510975%Good

Strategic Priority: Increase Essentials tier engagement through better onboarding and feature discovery

Weekly Active Users (WAU) ​

Definition: Unique teachers and students with platform interaction in 7-day period

Current Performance: 11,240 WAU (average across all schools)

Target: 10,000+ WAU, growing with customer acquisition

WAU Composition:

User TypeWeekly ActiveTotal UsersActivity Rate
Teachers1,8602,32080%
Students9,38014,85063%
Total11,24017,17065%

WAU Growth Trends:

MonthWAUTotal UsersActivity RateMoM Growth
Aug 20259,85015,20065%-
Sep 202510,42016,15065%+5.8%
Oct 202510,88016,80065%+4.4%
Nov 202511,24017,17065%+3.3%

Target: Maintain 65%+ activity rate while growing total users

Teacher vs Student Engagement Patterns:

MetricTeachersStudents
Avg sessions/week8.54.2
Avg time per session24 min18 min
Features used/week4.82.1
Peak usage time8am-10am2pm-4pm
Most used featureLesson PlannerQuiz Generator

Monthly Active Users (MAU) ​

Definition: Unique users with platform interaction in 30-day period

Current Performance: 13,680 MAU

Target: 80%+ of total registered users

MAU/WAU Ratio: 1.22 (indicates healthy weekly engagement)

  • Ratio >1.5: Low engagement, users only active occasionally
  • Ratio 1.2-1.5: Good engagement, users active multiple times per month
  • Ratio <1.2: Exceptional engagement, most users active weekly

Stickiness (DAU/MAU Ratio) ​

Definition: Daily Active Users / Monthly Active Users (measures habit formation)

Current Performance: 42% stickiness

Target: >40% (current performance is strong)

Stickiness Calculation:

Average DAU (monthly): 5,746 users
MAU: 13,680 users

Stickiness = (5,746 / 13,680) × 100 = 42%

Industry Benchmarks:

  • <20%: Low stickiness, users engage occasionally
  • 20-40%: Moderate stickiness, regular usage
  • 40%+: High stickiness, daily habit formed (YeboLearn is here)

Stickiness by User Type:

  • Teachers: 58% (use platform almost daily)
  • Students: 38% (use 2-3 times per week)

Feature Adoption Metrics ​

Overall Feature Adoption Rate ​

Definition: Percentage of schools using 5 or more features monthly

Current Performance: 87 schools (60% of active schools)

Target: 60%+ schools using ≥5 features

Feature Adoption Distribution:

Features UsedSchools% of TotalEngagement Level
1-2 features1812%Low (at-risk)
3-4 features4028%Moderate
5-7 features5236%Good
8-10 features2517%High
11+ features107%Power users

Correlation with Retention:

  • 1-2 features: 45% annual retention
  • 3-4 features: 72% annual retention
  • 5-7 features: 91% annual retention
  • 8+ features: 98% annual retention

Insight: Schools using 5+ features have 2x better retention

Feature Usage Breakdown ​

Top 10 Features by Adoption (30-day active usage):

FeatureSchools Using% AdoptionAvg Uses/WeekPower Users
1. AI Lesson Planner12888%12.485 schools
2. Smart Quiz Generator11881%8.772 schools
3. Auto-Grading11277%15.268 schools
4. Curriculum Alignment10673%6.358 schools
5. Resource Library9868%4.842 schools
6. Progress Tracking9566%18.665 schools
7. Plagiarism Checker8961%5.238 schools
8. Parent Portal7854%3.128 schools
9. Student Analytics7250%7.835 schools
10. Live Collaboration6847%2.922 schools

Power User Definition: Using feature 2x or more than average

Feature Launch Performance (Last 3 Launches):

FeatureLaunch Date30-Day Adoption60-Day AdoptionTargetStatus
Live CollaborationSep 1, 202535%47%40%Exceeded
Student AnalyticsJul 15, 202528%50%45%Exceeded
Parent PortalJun 1, 202542%54%50%Exceeded

Target: >40% adoption within 60 days of feature launch

AI Feature Usage Metrics ​

Definition: Percentage of schools using AI-powered features weekly

Current Performance: 102 schools (70% of active schools)

Target: 70%+ schools using AI features weekly

AI Feature Breakdown:

AI FeatureWeekly Users% of SchoolsAvg Uses/User/Week
AI Lesson Planner11881%3.8
Smart Quiz Generator10875%2.4
Auto-Grading9566%8.2
Plagiarism Checker7854%1.6
Writing Assistant7250%2.1
Content Recommendations6847%5.3
Any AI Feature10270%23.4

AI Usage Intensity (schools using AI features):

Intensity LevelSchools% of AI UsersAI Uses/Week
Light (1-10 uses)2827%5.2
Medium (11-25 uses)4544%17.8
Heavy (26-50 uses)2222%36.4
Power (51+ uses)77%72.6

AI Usage Growth:

MonthSchools Using AI% AdoptionTotal AI UsesMoM Growth
Aug 20258862%78,400-
Sep 20259465%85,200+8.7%
Oct 20259868%91,800+7.7%
Nov 202510270%98,500+7.3%

Target: 80% AI adoption by Q2 2026

Feature Engagement Score ​

Definition: Composite score measuring breadth and depth of feature usage

Calculation:

Feature Engagement Score =
  (# of features used × 10) +
  (total feature interactions / 10) +
  (AI feature usage × 5)

Example for a high-engagement school:
  (12 features × 10) + (840 interactions / 10) + (65 AI uses × 5)
  = 120 + 84 + 325 = 529 points

School Segmentation by Engagement Score:

SegmentScore RangeSchoolsAvg MRRRetention
Power Users400+18$3,20098%
High Engagement250-39945$2,10094%
Medium Engagement150-24952$1,65088%
Low Engagement50-14922$1,10068%
At-Risk<508$85042%

Strategic Action: Focus on moving "Low Engagement" schools to "Medium" (targeting 150+ score)

Platform Performance Metrics ​

Platform Uptime ​

Definition: Percentage of time platform is available and responsive

Current Performance: 99.94% uptime (last 30 days)

Target: 99.9%+ uptime (SLA commitment)

Uptime Tracking:

MonthUptime %Downtime (min)IncidentsMTTR
Aug 202599.89%48 min224 min
Sep 202599.96%17 min117 min
Oct 202599.92%35 min218 min
Nov 202599.94%26 min126 min

MTTR = Mean Time to Recovery

SLA Tiers:

  • Enterprise: 99.95% uptime guarantee (5 schools impacted by Nov incident)
  • Professional: 99.9% uptime target
  • Essentials: 99.5% uptime (best effort)

Incident Response:

  • <15 min: Excellent recovery
  • 15-30 min: Acceptable

  • 30 min: Needs improvement

Page Load Times ​

Definition: Time from request to fully loaded page

Current Performance: 1.8s average load time

Target: <2.0s average, ❤️.0s for 95th percentile

Load Time Distribution (November):

PercentileLoad TimeTargetStatus
50th (Median)1.4s<1.5sGood
75th2.1s<2.5sGood
95th2.9s❤️.0sGood
99th4.2s<5.0sGood

Load Time by Feature:

FeatureAvg Load95th PercentileStatus
Dashboard1.2s2.1sExcellent
Lesson Planner2.4s3.8sGood
Quiz Generator3.1s4.5sNeeds improvement
Resource Library1.8s2.6sGood
Student Analytics2.9s4.2sAcceptable

Action Item: Optimize Quiz Generator load time (target: <2.5s average)

API Response Times ​

Definition: Time for API to respond to requests

Current Performance: 280ms average response time

Target: <300ms average, <500ms for 95th percentile

API Performance:

Endpoint CategoryAvg Response95th PercentileRequests/Day
Authentication120ms185ms45,000
Content Retrieval220ms380ms128,000
AI Generation1,850ms3,200ms18,500
Data Analytics450ms680ms12,400
File Upload680ms1,100ms8,200

Note: AI generation endpoints have higher latency due to external API calls (OpenAI, etc)

Error Rates ​

Definition: Percentage of requests resulting in errors

Current Performance: 0.12% error rate

Target: <0.5% error rate

Error Breakdown (November):

Error TypeCount% of TotalImpact Level
5xx Server Errors1,24058%High
4xx Client Errors72034%Medium
Timeout Errors1808%High
Total Errors2,140100%-

Error Rate Trend:

WeekTotal RequestsErrorsError Rate
Week 14.2M5800.14%
Week 24.5M5200.12%
Week 34.4M4800.11%
Week 44.6M5600.12%

Top Error Sources:

  1. AI API timeouts (OpenAI rate limits) - 32% of errors
  2. Database connection pool exhaustion - 18% of errors
  3. File upload size limits exceeded - 12% of errors
  4. Invalid authentication tokens - 11% of errors

User Behavior Metrics ​

Session Duration ​

Definition: Average time users spend in platform per session

Current Performance:

  • Teachers: 24 minutes average
  • Students: 18 minutes average
  • Overall: 19.8 minutes average

Target: Maintain >15 minutes average (indicates meaningful engagement)

Session Duration by Feature:

FeatureAvg Session DurationSessions/WeekTotal Time/Week
Lesson Planner32 min4,8502,587 hours
Auto-Grading18 min6,2001,860 hours
Quiz Generator22 min3,8401,408 hours
Progress Tracking12 min5,1001,020 hours
Resource Library15 min2,900725 hours

Total Weekly Active Learning Hours: 12,840 hours across 145 schools = 88.6 hours/school/week

Monthly Average: 385 hours/school/month (target: 800 hours/school/month)

Opportunity: Increase session frequency and duration to reach target learning hours

Features Per Session ​

Definition: Average number of distinct features used in single session

Current Performance: 2.4 features per session

Target: >2.0 features per session (indicates feature discovery and cross-usage)

Session Patterns:

Features Used% of SessionsAvg DurationUser Satisfaction
1 feature42%12 min3.2/5
2 features31%18 min3.8/5
3 features18%26 min4.2/5
4+ features9%38 min4.6/5

Insight: Multi-feature sessions have higher satisfaction and longer duration

Feature Discovery Rate ​

Definition: Percentage of users discovering new features each month

Current Performance: 28% of users try a new feature monthly

Target: >25% monthly feature discovery

Discovery Methods:

Method% of DiscoveriesEffectiveness
In-app prompts42%High
Email campaigns25%Medium
Onboarding wizard18%High
User exploration12%Low
Support team3%Medium

Strategic Focus: Increase in-app feature prompts and improve onboarding wizard

Retention Metrics ​

User Retention Cohorts ​

7-Day Retention (users active 7 days after first session):

Signup MonthNew UsersDay 7 ActiveRetention %
Aug 20251,8401,28870%
Sep 20252,1201,59075%
Oct 20252,2801,78978%
Nov 20251,9201,53680%

30-Day Retention (users active 30 days after first session):

Signup MonthNew UsersDay 30 ActiveRetention %
Jul 20251,6801,02561%
Aug 20251,8401,19565%
Sep 20252,1201,42167%
Oct 20252,2801,57369%

Target: 75%+ 7-day retention, 65%+ 30-day retention

Feature-Specific Retention ​

Retention Rate by First Feature Used:

First Feature7-Day Retention30-Day Retention
AI Lesson Planner82%72%
Quiz Generator76%68%
Resource Library68%58%
Progress Tracking72%65%
Curriculum Alignment79%71%

Insight: Users starting with AI features have higher retention

Monitoring and Alerts ​

Product Health Alerts ​

Critical (Immediate Action):

  • Platform uptime <99.5% for >15 minutes
  • Error rate >1% for >5 minutes
  • DAS decline >15% day-over-day
  • Major feature completely unavailable

Warning (Review Within 2 Hours):

  • Load time >5s for 95th percentile
  • Error rate 0.5-1% sustained for >30 minutes
  • DAS decline 10-15% day-over-day
  • Feature adoption decline >10% week-over-week

Opportunity (Weekly Review):

  • Feature adoption increase >20% week-over-week
  • New feature usage pattern detected
  • Power user segment growth >10%
  • Session duration increase >15%

Product Metric Goals (2026) ​

MetricCurrentQ1 2026Q2 2026Q4 2026
DAS %75%77%80%82%
WAU11,24013,50016,00020,000
Feature Adoption (5+)60%65%70%75%
AI Usage Rate70%75%80%85%
Platform Uptime99.94%99.95%99.96%99.97%
Avg Session Duration19.8 min21 min23 min25 min
Features/Session2.42.62.83.0

Next Steps ​

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