UX Metrics

The HEART Framework

Google's framework for measuring UX:

┌─────────────────────────────────────────────────────┐
│                                                     │
│   Happiness      Engagement      Adoption          │
│   (Attitude)     (Behavior)      (New users)       │
│                                                     │
│   Retention      Task Success                       │
│   (Continued use) (Effectiveness)                   │
│                                                     │
└─────────────────────────────────────────────────────┘

Goals → Signals → Metrics

1. Happiness

What: Attitude and satisfaction

Metrics:

Satisfaction Scales:
• CSAT (Customer Satisfaction)
  "How satisfied are you?" 1-5 or 1-10
  
• NPS (Net Promoter Score)
  "How likely to recommend?" 0-10
  Promoters (9-10) - Detractors (0-6) = NPS
  
• SEQ (Single Ease Question)
  "How easy was this task?" 1-7
  
• UMUX-Lite
  Short standardized usability scale

When to measure:

• Post-task surveys
• Periodic user surveys
• Support interactions
• Cancellation flows

2. Engagement

What: Level of user involvement

Metrics:

Behavioral:
• Session frequency (DAU/MAU ratio)
• Session duration
• Actions per session
• Core feature usage
• Content consumption

Calculation:
Engagement = (Active users / Total users) × 
             (Actions per user) × 
             (Frequency of use)

Example:

Music app engagement:
• Sessions per week: 5
• Songs played per session: 12
• Playlists created per month: 2
• Social shares per month: 3

Trend: ↑ = Better engagement

3. Adoption

What: New user uptake

Metrics:

Onboarding:
• Sign-up completion rate
• First value moment (Aha!)
• Feature adoption (3, 7, 30 days)
• Activation rate

Example:
Week 1: 1000 signups
Week 2: 600 complete onboarding (60%)
Week 3: 400 use core feature (40% of signups)

Key milestones:

• First login
• First core action
• First return visit
• First week of regular use

4. Retention

What: Sustained usage over time

Metrics:

Cohort Analysis:
         Week 1   Week 2   Week 3   Week 4
Jan 1      100%     45%      38%      32%
Jan 8      100%     48%      41%      35%
Jan 15     100%     52%      44%      38%

Retention Rate = Users at end / Users at start

Types:

• Day 1, 7, 30 retention
• Monthly active users returning
• Subscription renewal rates
• Feature re-engagement

5. Task Success

What: Effectiveness of task completion

Metrics:

Quantitative:
• Success rate (% completing task)
• Time on task (efficiency)
• Error rate (accuracy)
• Abandonment rate

Example usability test:
Task: "Find pricing information"
• Success: 85% found it
• Avg time: 45 seconds
• Errors: 12% clicked wrong link
• Abandoned: 5%

The PULSE Framework

Traditional metrics that complement HEART:

P - Page views
U - Uptime
L - Latency
S - Seven-day active users
E - Earnings

Business health metrics (not UX-specific)

UX Metric Categories

Behavioral Metrics

Task-Level:
├── Success rate
├── Time on task
├── Error rate
├── Steps to complete
└── Abandonment rate

Product-Level:
├── Feature adoption
├── User flows
├── Retention curves
├── Cohort analysis
└── Funnel conversion

Attitudinal Metrics

Satisfaction:
├── CSAT (point-in-time)
├── NPS (loyalty)
├── CES (Customer Effort Score)
└── SUS (System Usability Scale)

Emotional:
├── Desirability testing
├── Emoji scales
├── Sentiment analysis
└── Interview sentiment

Technical Metrics

Performance (Core Web Vitals):
├── LCP (Largest Contentful Paint) < 2.5s
├── FID (First Input Delay) < 100ms
├── CLS (Cumulative Layout Shift) < 0.1
└── TTFB (Time to First Byte) < 600ms

Accessibility:
├── WCAG compliance score
├── Screen reader compatibility
├── Keyboard navigation success
└── Color contrast ratios

Measuring What Matters

Aligning with Business Goals

Business Goal → UX Metric
─────────────────────────────
Increase sales → Cart completion rate
                 Time to purchase
                 
Reduce churn   → Retention rate
                 NPS score
                 
Improve support→ Task success (self-serve)
                 CES score
                 
Launch feature → Adoption rate
                 Time to first use

Choosing Your Metrics

Good metrics are:
□ Relevant (tie to goals)
□ Actionable (lead to decisions)
□ Timely (available when needed)
□ Comparable (track over time)
□ Sensitive (detect changes)

Avoid:
× Vanity metrics (look good, don't guide)
× Too many metrics (paralysis)
× Lagging indicators (too late to act)
× Unreliable data (can't trust)

Setting Up Measurement

Step 1: Define Goals

Goal: Improve checkout experience

UX Goals:
• Reduce checkout time
• Reduce cart abandonment
• Increase satisfaction

Business Goals:
• Increase conversion 10%
• Reduce support tickets
• Improve NPS

Step 2: Choose Metrics

For checkout:

HEART Metrics:
Happiness: Post-checkout CSAT
Engagement: Return purchase rate
Adoption: Guest checkout usage
Retention: Repeat purchase rate
Task Success: 
  • Checkout completion rate
  • Time to checkout
  • Error rate at each step

+ Business:
  • Cart abandonment rate
  • Average order value

Step 3: Set Baselines

Current State:
• Checkout completion: 68%
• Average time: 4.5 minutes
• Error rate: 15%
• CSAT: 3.8/5

Target State (6 months):
• Checkout completion: 80%
• Average time: 3 minutes
• Error rate: < 8%
• CSAT: 4.2/5

Step 4: Implement Tracking

Tools:
• Analytics: Google Analytics, Amplitude, Mixpanel
• Testing: Usability testing platforms
• Surveys: Typeform, SurveyMonkey, Qualtrics
• Performance: Lighthouse, WebPageTest
• Heatmaps: Hotjar, FullStory, Crazy Egg

Implementation:
□ Tag key user flows
□ Set up conversion funnels
□ Create dashboards
□ Schedule regular reports

Analyzing and Acting

Statistical Significance

Is the change real or random?

A/B Test Results:
Variant A: 68% conversion
Variant B: 72% conversion (+4%)
Confidence: 95%
P-value: 0.03

→ Statistically significant
→ Implement Variant B

Trend Analysis

Watch for patterns:

Metric: Task Success Rate
Jan: 72%
Feb: 73%
Mar: 71%
Apr: 74%
May: 69% ← Investigate
Jun: 75%

Look for:
• Seasonal patterns
• Release correlations
• Anomaly detection
• Long-term trends

Qualitative + Quantitative

Quantitative: "Error rate increased 15%"
     ↓
Qualitative: Watch session recordings
     ↓
Finding: New button placement causes misclicks
     ↓
Action: Revert button position
     ↓
Result: Error rate back to baseline

Common Mistakes

1. Focusing on Vanity Metrics

❌ Page views (without context)
❌ Total signups (not activated)
❌ App downloads (not opened)

✅ Active users
✅ Feature adoption
✅ Task success
✅ Retention

2. Ignoring Baselines

❌ "Conversion improved 5%!"
   (from what baseline?)
   
❌ "NPS is 42"
   (is that good?)

✅ "Conversion improved from 20% to 25%"
✅ "NPS 42 (up from 35, industry avg 40)"

3. Too Many Metrics

❌ Tracking 50+ metrics
   → Analysis paralysis
   → Can't focus
   → Conflicting signals

✅ 3-5 key metrics
   → Clear focus
   → Actionable
   → Aligned with goals

4. Not Acting on Data

❌ "We track everything but don't change anything"

✅ Data-informed decisions:
   • Weekly metric review
   • Thresholds for investigation
   • Action plans for anomalies
   • Regular experimentation

Advanced Techniques

Correlation Analysis

Find relationships:

Task success rate vs CSAT: +0.78
(Correlated - improving one helps other)

Page load time vs Bounce rate: -0.65
(As load time increases, bounce increases)

Use: Prioritize improvements with multiple benefits

Segmentation

Compare segments:

Conversion Rate:
Overall: 4.2%
Mobile:  2.8% ← Opportunity
Desktop: 5.1%
Tablet:  3.9%

Action: Focus on mobile UX improvements

Cohort Analysis

Track groups over time:

Users who joined in:
         Week 1  Week 4  Week 12  Week 24
January    100%    45%     32%      28%
February   100%    52%     38%      34%
March      100%    58%     42%      39%

Trend: Improving! Changes working.

Reporting UX Metrics

Dashboard Structure

Executive Summary:
├── Key metrics with trends
├── Goal progress
└── Top opportunities

Detailed View:
├── Metrics by segment
├── Funnel analysis
├── Cohort retention
└── Qualitative insights

Drill-Down:
├── User flows
├── Session recordings
├── Survey responses
└── Support tickets

Stakeholder Communication

Frame for audience:

To Executives:
"Improving task success by 10% 
correlates with $2M additional revenue"

To Product:
"Feature X has 80% lower adoption 
than Feature Y—let's investigate"

To Engineering:
"LCP improvement from 4s to 2s 
reduced bounce rate by 15%"

To Design:
"Users rate new flow 20% easier—
qualitative feedback confirms"