Product Dashboards
YeboLearn's dashboard ecosystem provides real-time visibility into platform performance, user behavior, and business metrics. Dashboards are designed for different audiences and use cases, from executive summaries to operational monitoring.
Dashboard Architecture
Dashboard Stack
Data Sources → Segment → BigQuery → BI Tools → Dashboards
↓
Mixpanel (Product)
Metabase (Business)
Custom (Operations)Update Frequencies:
- Real-time: Critical operational metrics (uptime, errors, active users)
- 5-minute: Product usage, feature adoption
- Hourly: Business metrics, revenue tracking
- Daily: Cohort analysis, retention metrics
- Weekly: Executive summaries, trend analysis
Access Control
Dashboard Access Levels:
| Level | Access | Dashboards | Users |
|---|---|---|---|
| Executive | All dashboards | 15+ | CEO, CFO, CPO, CRO, Board |
| Department Head | Department + shared | 8-12 | VPs, Directors |
| Manager | Team + shared | 5-8 | Managers, Leads |
| Team Member | Relevant only | 2-4 | ICs, Analysts |
| Read-Only | Selected public | 1-2 | External advisors |
Executive Dashboards
CEO Dashboard (Daily Review)
Purpose: Single-page view of company health
Update Frequency: Real-time for critical metrics, hourly for others
Sections:
1. North Star Metric
┌─────────────────────────────────────────────────┐
│ Active Learning Hours per School │
│ │
│ Current Month: 385 hours/school │
│ Target: 800 hours/school │
│ Progress: 48% ████████░░░░░░░░░░ [Below Target]│
│ │
│ Trend (last 6 months): │
│ Jun Jul Aug Sep Oct Nov │
│ 320→ 340→ 358→ 368→ 375→ 385 │
│ │
│ Growth: +20% since June │
└─────────────────────────────────────────────────┘2. Business Health (Traffic Light)
┌──────────────────────────────────────────┐
│ Metric Status Trend │
│─────────────────────────────────────────│
│ MRR Growth 🟢 Good ↗ │
│ Net Churn 🟢 Good ↘ │
│ DAS 🟢 Good ↗ │
│ Platform Uptime 🟢 Good → │
│ NRR 🟢 Good ↗ │
│ LTV:CAC 🟢 Good → │
│ Rule of 40 🟢 Good ↗ │
└──────────────────────────────────────────┘3. Key Metrics (Current vs Target)
| Metric | Current | Target | Status | Variance |
|---|---|---|---|---|
| MRR | $247K | $250K | 🟡 | -1.2% |
| Active Schools | 145 | 150 | 🟡 | -3.3% |
| DAS % | 75% | 75% | 🟢 | 0% |
| Net Churn | -2.3% | <5% | 🟢 | +58% better |
| New Schools (MTD) | 13 | 15 | 🟡 | -13% |
4. Weekly Highlights
- Wins: 2 Enterprise upgrades ($9,000 MRR), 99.94% uptime maintained
- Concerns: New school acquisition below target, need marketing push
- Actions: Launch November campaign, accelerate 3 high-value deals
Key Features:
- One-click drill-down to detailed reports
- Automated alerts for red/yellow metrics
- Week-over-week and month-over-month comparisons
- Exportable to PDF for board meetings
CFO Dashboard (Financial Focus)
Purpose: Revenue, profitability, and unit economics tracking
Sections:
Revenue Metrics
Monthly Recurring Revenue (MRR)
┌─────────────────────────────────────────────┐
│ Current MRR: $247,000 │
│ vs Last Month: +$9,000 (+3.78%) │
│ vs Last Year: +$102,000 (+70%) │
│ │
│ MRR Movement (November): │
│ Starting MRR: $238,000 │
│ + New: +$18,000 │
│ + Expansion: +$7,200 │
│ - Contraction: -$3,600 │
│ - Churn: -$12,600 │
│ Ending MRR: $247,000 │
│ │
│ Annual Run Rate (ARR): $2.96M │
└─────────────────────────────────────────────┘
Revenue by Tier
Enterprise: $54,000 ████████████░░░░░░░ 21.9%
Professional:$153,000█████████████████████61.9%
Essentials: $40,000 ████████░░░░░░░░░░░ 16.2%Profitability Metrics
| Metric | Value | Target | Status |
|---|---|---|---|
| Gross Margin | 78% | >75% | 🟢 |
| CAC | $2,850 | <$3,000 | 🟢 |
| LTV | $42,500 | >$40,000 | 🟢 |
| LTV:CAC | 14.9:1 | >3:1 | 🟢 |
| CAC Payback | 2.1 mo | ❤️ mo | 🟢 |
| Magic Number | 0.85 | >0.75 | 🟢 |
Cash Flow Forecast (Next 12 Months)
Month Revenue Expenses Net CF Cumulative
Dec 2025 $285K $240K +$45K $45K
Jan 2026 $295K $248K +$47K $92K
Feb 2026 $308K $255K +$53K $145K
...
Nov 2026 $420K $335K +$85K $785KCPO Dashboard (Product Focus)
Purpose: Feature adoption, user engagement, and platform health
Sections:
Feature Adoption Heatmap
Feature Nov Oct Sep Trend
AI Lesson Planner 88% 87% 86% ↗
Smart Quiz Generator 81% 79% 76% ↗
Auto-Grading 77% 76% 75% ↗
Curriculum Alignment 73% 71% 68% ↗
Resource Library 68% 67% 65% ↗
Progress Tracking 66% 64% 63% ↗
Plagiarism Checker 61% 59% 56% ↗
Parent Portal 54% 52% 48% ↗
Student Analytics 50% 47% 42% ↗
Live Collaboration 47% 42% 35% ↗User Engagement
Daily Active Schools (DAS)
┌────────────────────────────────────────┐
│ Current: 109 schools (75% of base) │
│ │
│ Weekly Trend: │
│ Week 1: 106 (74%) │
│ Week 2: 108 (75%) ↗ │
│ Week 3: 109 (75%) → │
│ Week 4: 111 (77%) ↗ │
│ │
│ By Tier: │
│ Enterprise: 100% (12/12) 🟢 │
│ Professional: 85% (72/85) 🟢 │
│ Essentials: 52% (25/48) 🟡 │
└────────────────────────────────────────┘
Weekly Active Users (WAU): 11,240
Teachers: 1,860 (80% activity rate)
Students: 9,380 (63% activity rate)Platform Performance
| Metric | Current | Target | 24h Change |
|---|---|---|---|
| Uptime | 99.94% | 99.9% | 🟢 No change |
| Avg Load Time | 1.8s | <2.0s | 🟢 -0.1s |
| Error Rate | 0.12% | <0.5% | 🟢 No change |
| API Response | 280ms | <300ms | 🟢 -5ms |
CRO Dashboard (Sales & Revenue)
Purpose: Sales pipeline, conversion rates, and revenue growth
Sections:
Sales Pipeline
Pipeline Value: $3,070,000 (3.2x coverage)
Stage Opps Value Weighted Win Rate
Qualified 45 $1,280K $256K 20%
Demo Completed 32 $890K $356K 40%
Proposal Sent 18 $520K $312K 60%
Negotiation 12 $380K $304K 80%
─────────────────────────────────────────────────────
Total 107 $3,070K $1,228K 40%
Target Q1 2026: $390K ARR
Weighted pipeline: $1,228K (3.2x coverage) 🟢Conversion Funnel
Monthly Funnel (November)
Leads (inbound + outbound): 420 leads
↓ (30% qualify)
Qualified Opportunities: 126 opps
↓ (55% get demo)
Demo Completed: 69 demos
↓ (45% receive proposal)
Proposal Sent: 31 proposals
↓ (48% close)
Closed Won: 15 schools 🎯
Overall Conversion: 3.6% (lead → customer)
Target: 3.5% 🟢Rep Performance
| Rep | Pipeline | Closed (Nov) | Win Rate | Avg Deal |
|---|---|---|---|---|
| Sarah M. | $680K | 5 schools | 52% | $2,100/mo |
| David K. | $520K | 4 schools | 48% | $1,850/mo |
| Lisa P. | $450K | 3 schools | 42% | $1,600/mo |
| New Rep | $180K | 1 school | 28% | $900/mo |
Team Dashboards
Product Team Dashboard
Purpose: Feature performance, user feedback, and roadmap tracking
Daily View:
- Feature usage (daily active users per feature)
- New feature adoption curves
- Bug reports and error rates
- User feedback sentiment
- A/B test performance
Weekly View:
- Feature retention cohorts
- User journey completions
- Engagement score distributions
- Platform performance trends
Key Widgets:
Feature Launch Performance
Live Collaboration (Launched Sep 1)
Day 30 Adoption: 35% (target: 30%) 🟢
Day 60 Adoption: 47% (target: 40%) 🟢
Adoption Curve:
Week 1: 12% ███░░░░░░░
Week 2: 18% █████░░░░░
Week 4: 25% ███████░░░
Week 8: 35% ██████████
Week 12: 47% █████████████Bug Tracking
| Severity | Open | In Progress | Closed (7d) |
|---|---|---|---|
| Critical | 0 | 0 | 2 |
| High | 3 | 5 | 12 |
| Medium | 18 | 8 | 28 |
| Low | 42 | 6 | 35 |
Customer Success Dashboard
Purpose: Customer health, retention risk, and expansion opportunities
Account Health Scores:
Health Score Distribution
Healthy (80-100): 92 schools (63%) 🟢
Moderate (60-79): 31 schools (21%) 🟡
At-Risk (40-59): 14 schools (10%) 🟠
Critical (<40): 8 schools (6%) 🔴
Weekly Change:
Improved: 12 schools ↗
Declined: 8 schools ↘
Stable: 125 schools →At-Risk Accounts (Prioritized):
| School | Health Score | Risk Factors | Owner | Next Action |
|---|---|---|---|---|
| Springfield Academy | 28 | No login 12d, 1 feature | Jessica | Call scheduled |
| Oak Valley School | 35 | Usage -45%, support issues | Marcus | On-site visit |
| Riverside Prep | 42 | Single user, budget concern | Sarah | Renewal meeting |
Expansion Opportunities:
| School | Current Tier | Upsell Signal | Potential ARR | Probability |
|---|---|---|---|---|
| Maplewood High | Professional | 320 students | +$32,400 | 78% |
| Lincoln Academy | Professional | 12 features used | +$32,400 | 65% |
| Cedar Grove | Essentials | Heavy AI usage | +$11,600 | 52% |
Marketing Dashboard
Purpose: Campaign performance, lead generation, and attribution
Campaign Performance (Last 30 Days):
Channel Spend Leads CPL Conversions CPA
LinkedIn Ads $4,200 85 $49 6 $700
Email Campaigns $1,500 112 $13 5 $300
WhatsApp $800 48 $17 2 $400
Events/Webinars $2,200 38 $58 3 $733
Content/SEO $1,200 65 $18 2 $600
─────────────────────────────────────────────────────────
Total $9,900 348 $28 18 $550Lead Funnel:
Website Visitors: 12,450
↓ (8.5% engage)
Content Downloads: 1,058
↓ (33% convert)
Leads Generated: 348
↓ (36% qualify)
Marketing Qualified: 125
↓ (14% close)
New Customers: 18
Visitor → Customer: 0.14% conversionContent Performance:
| Content | Views | Leads | Conversion | Quality Score |
|---|---|---|---|---|
| "AI in Education" Guide | 2,450 | 85 | 3.5% | High |
| Webinar: Lesson Planning | 420 | 68 | 16% | Very High |
| Case Study: Maplewood | 1,280 | 42 | 3.3% | Medium |
| Blog: Auto-Grading Tips | 3,850 | 28 | 0.7% | Low |
Engineering Dashboard
Purpose: System health, performance, and incident tracking
System Health:
Platform Status: 🟢 All Systems Operational
Uptime (30d): 99.94%
Incidents: 1 (26 min downtime)
MTTR: 26 minutes
Error Budget Remaining: 98.4%
Performance Metrics:
API Response Time: 280ms (↓ 5ms vs yesterday)
Page Load Time: 1.8s (↓ 0.1s vs yesterday)
Database Queries: <100ms avg
CDN Hit Rate: 94%Real-Time Monitoring:
| Metric | Current | 5min Avg | 1hr Avg | Status |
|---|---|---|---|---|
| Active Users | 2,840 | 2,755 | 2,420 | 🟢 |
| Requests/sec | 485 | 472 | 428 | 🟢 |
| Error Rate | 0.08% | 0.10% | 0.12% | 🟢 |
| CPU Usage | 42% | 45% | 48% | 🟢 |
| Memory Usage | 68% | 67% | 65% | 🟢 |
Infrastructure Costs (Monthly):
AWS Compute: $18,500 (66%)
AWS Storage: $4,200 (15%)
CDN (Cloudflare):$2,800 (10%)
AI APIs: $18,500 (66% of total)
Third-party: $5,840 (21%)
─────────────────────────────────
Total: $28,000 COGSOperational Dashboards
Daily Operations Dashboard
Purpose: Real-time monitoring for on-call teams
Critical Metrics (Refreshes every 30 seconds):
🟢 Platform Status: Operational
🟢 API Status: Operational
🟢 Database: Operational
🟢 AI Services: Operational
Active Users (Right Now): 2,840
Requests (Last Minute): 8,720
Errors (Last Minute): 6 (0.07%)
Queue Depth: 42 jobs
Alert Status:
Critical: 0
Warning: 2 (High database CPU, High memory usage)
Info: 5Recent Activity (Last 15 minutes):
- 13:42 - High database CPU alert triggered (resolved)
- 13:35 - 500 new users logged in
- 13:28 - AI API rate limit warning
- 13:15 - Database backup completed successfully
Support Dashboard
Purpose: Customer support ticket tracking and SLA monitoring
Ticket Overview:
Open Tickets: 48
Critical (P1): 0 Target: <1 hour SLA: 🟢
High (P2): 3 Target: <4 hours SLA: 🟢
Medium (P3): 18 Target: <24 hours SLA: 🟢
Low (P4): 27 Target: <72 hours SLA: 🟢
Today's Activity:
New: 22 tickets
Resolved: 28 tickets
Backlog: -6 (improving)Top Issues (Last 7 Days):
| Issue | Count | Avg Resolution | Status |
|---|---|---|---|
| Login problems | 18 | 2.5 hours | Known bug fix in progress |
| Quiz Generator errors | 12 | 1.8 hours | Resolved |
| Slow loading | 8 | 3.2 hours | Investigating |
| Feature requests | 15 | N/A | Logged for PM review |
Support Satisfaction:
- CSAT Score: 4.6/5.0
- First Response Time: 18 minutes avg (target: <30 min)
- Time to Resolution: 4.2 hours avg (target: <24 hours)
Specialized Dashboards
AI Usage Dashboard
Purpose: Track AI feature usage, costs, and performance
AI Usage Overview:
Total AI Requests (November): 98,500
Daily Average: 3,283 requests
Growth vs October: +7.3%
Cost per Request: $0.188
Total AI Cost: $18,500/month
Revenue from AI users: $178,500/month
AI Cost as % of Revenue: 10.4% 🟢AI Feature Breakdown:
| Feature | Requests | Cost | Avg Latency | User Rating |
|---|---|---|---|---|
| Lesson Planner | 38,200 | $7,450 | 2.8s | 4.7/5 |
| Quiz Generator | 28,400 | $5,280 | 2.2s | 4.5/5 |
| Auto-Grading | 18,500 | $3,420 | 1.8s | 4.6/5 |
| Writing Assistant | 8,200 | $1,580 | 1.5s | 4.4/5 |
| Plagiarism Checker | 5,200 | $730 | 3.2s | 4.3/5 |
AI Quality Metrics:
- User Satisfaction: 4.5/5.0 (based on post-use ratings)
- Retry Rate: 8.2% (users regenerating output)
- Error Rate: 1.4%
- Timeout Rate: 0.3%
Mobile Usage Dashboard
Purpose: Track mobile web and app usage patterns
Mobile vs Desktop:
Platform Distribution:
Desktop: 58% ████████████████░░░░░░░░░░░░
Mobile: 28% ████████████░░░░░░░░░░░░░░░░
Tablet: 12% █████░░░░░░░░░░░░░░░░░░░░░░░
App: 2% █░░░░░░░░░░░░░░░░░░░░░░░░░░░Mobile Experience Metrics:
| Metric | Mobile Web | Desktop Web | Target |
|---|---|---|---|
| Load Time | 2.8s | 1.4s | ❤️.0s |
| Error Rate | 0.18% | 0.10% | <0.5% |
| Bounce Rate | 22% | 12% | <25% |
| Session Duration | 12 min | 24 min | >10 min |
Dashboard Best Practices
Design Principles
- Most Important First: Critical metrics at top of dashboard
- Visual Hierarchy: Size and color indicate importance
- Context Always: Show targets, benchmarks, and trends
- Actionable: Include next steps or drill-down options
- Fast Loading: Optimize for <2 second load times
Color Coding Standards
Status Indicators:
- 🟢 Green: At or above target (good performance)
- 🟡 Yellow: 5-15% below target (needs attention)
- 🟠 Orange: 15-25% below target (concerning)
- 🔴 Red: >25% below target or critical issue (immediate action)
Trend Indicators:
- ↗ Improving (desired direction)
- → Stable (no significant change)
- ↘ Declining (undesired direction)
Dashboard Maintenance
Weekly:
- Verify data accuracy
- Update targets as needed
- Add/remove metrics based on focus
- Check load times
Monthly:
- Review dashboard usage (which dashboards are viewed)
- Archive unused dashboards
- Gather feedback from users
- Update calculations or definitions
Quarterly:
- Redesign underperforming dashboards
- Add new dashboards for new initiatives
- Sunset deprecated metrics
- Train new users on dashboard access
Dashboard Access
Primary Tools:
- Metabase: https://analytics.yebolearn.internal/
- Mixpanel: https://mixpanel.com/yebolearn
- Custom Dashboards: https://dashboards.yebolearn.internal/
Mobile Access: All dashboards mobile-responsive, accessible via phone/tablet
API Access: Select metrics available via REST API for custom integrations
Next Steps
- Feature Analytics - Deep-dive into individual feature performance
- User Analytics - User segmentation and behavior analysis
- Business Analytics - Revenue and sales performance
- Executive Reports - Board-level reporting templates