You've written great documentation. But is it working? Are developers finding what they need? Are they successful after reading? Documentation analytics helps you answer these questions with data, not guesses.

Why Measure Documentation?#

Without metrics, you're flying blind:

Which pages need improvement? Guessing wastes effort
Is the new guide helping? No way to know
Where are developers struggling? Invisible pain points
What content should we prioritize? Unclear ROI

Data transforms documentation from art into science.

The Documentation Metrics Hierarchy#

Not all metrics are equal. Here's how to think about them:

Text

                    ┌─────────────────┐
                    │   Outcomes      │  ← Business impact
                    │  (Hardest to    │     Support tickets, adoption
                    │   measure)      │
                    └────────┬────────┘
                             │
                    ┌────────▼────────┐
                    │   Behavior      │  ← User actions
                    │  (Shows intent) │     Clicks, scrolls, copies
                    └────────┬────────┘
                             │
                    ┌────────▼────────┐
                    │   Engagement    │  ← Attention
                    │  (Basic signal) │     Page views, time on page
                    └────────┬────────┘
                             │
                    ┌────────▼────────┐
                    │    Traffic      │  ← Raw numbers
                    │  (Vanity)       │     Total visits
                    └─────────────────┘

Focus your energy from top to bottom.

Essential Metrics to Track#

1. Search Behavior#

What developers search for reveals what they need:

JavaScript

// Track search queries
analytics.track('docs_search', {
  query: searchQuery,
  results_count: results.length,
  clicked_result: clickedIndex, // null if no click
  time_to_click: timeMs
});

Key metrics:

Top searches: What do people look for most?
Zero-result searches: What's missing from your docs?
Search refinements: When do people rephrase their query?
Click position: Do they find answers in top results?

Actionable insights:

Finding	Action
"authentication" top search	Feature prominently on homepage
"rate limit" zero results	Add rate limiting documentation
Most click 3rd+ result	Improve search ranking or titles
Many refinements for "deploy"	Content doesn't match expectations

2. Page Performance#

Not all pages perform equally:

JavaScript

// Track page engagement
analytics.track('docs_page_view', {
  page: window.location.pathname,
  referrer: document.referrer,
  scroll_depth: 0
});
 
// Track scroll depth
window.addEventListener('scroll', throttle(() => {
  const depth = calculateScrollDepth();
  analytics.track('docs_scroll', {
    page: window.location.pathname,
    depth: depth // 25%, 50%, 75%, 100%
  });
}, 1000));

Key metrics:

Bounce rate: Leave without engaging
Scroll depth: How much content is consumed
Time on page: Engagement duration
Exit pages: Where do journeys end?

Interpreting the data:

3. User Journeys#

How do developers navigate your docs?

JavaScript

// Track navigation paths
analytics.track('docs_navigation', {
  from: previousPage,
  to: currentPage,
  method: 'link' | 'search' | 'sidebar' | 'breadcrumb'
});

Key metrics:

Common paths: How do users typically navigate?
Dead ends: Pages with high exit rates
Loop detection: Do users go back and forth?
Time to destination: How long to find key pages?

Example insight:

Text

Common path to "API Reference":
Homepage → Getting Started → API Reference (32%)
Homepage → Concepts → API Reference (28%)
Search → API Reference (25%)
Direct link (15%)

If 25% come from search, make API Reference more discoverable in navigation.

4. Code Interaction#

Track how developers interact with code examples:

JavaScript

// Track code copies
document.querySelectorAll('pre code').forEach(block => {
  block.addEventListener('copy', () => {
    analytics.track('docs_code_copy', {
      page: window.location.pathname,
      language: block.className,
      snippet_id: block.dataset.id
    });
  });
});
 
// Track code tab switches
tabSwitcher.on('switch', (language) => {
  analytics.track('docs_code_language', {
    page: window.location.pathname,
    selected: language,
    available: ['javascript', 'python', 'curl']
  });
});

Key metrics:

Copy rate: Which code is most useful?
Language preferences: What do your users write?
Tab switching: Do users need multiple languages?

5. Feedback Signals#

Direct user feedback complements behavioral data:

JavaScript

// "Was this helpful?" widget
const trackFeedback = (helpful, pageId) => {
  analytics.track('docs_feedback', {
    page: pageId,
    helpful: helpful,
    timestamp: Date.now()
  });
};
 
// Open feedback form
const trackDetailedFeedback = (feedback) => {
  analytics.track('docs_feedback_detailed', {
    page: window.location.pathname,
    rating: feedback.rating,
    category: feedback.category,
    comment: feedback.comment
  });
};

Key metrics:

Helpfulness score: % positive ratings per page
Feedback volume: Which pages get most feedback?
Sentiment analysis: Common themes in comments

Building a Documentation Dashboard#

Essential Dashboard Views#

1. Overview

Text

┌─────────────────────────────────────────────────────────────┐
│ Documentation Health Score: 78/100                    ↑ 3%  │
├─────────────────────────────────────────────────────────────┤
│ Weekly Visitors    │ Avg. Helpfulness  │ Search Success     │
│ 12,450 ↑ 8%       │ 82% ↑ 2%          │ 76% → 0%          │
├─────────────────────────────────────────────────────────────┤
│ Pages Needing Attention                                     │
│ • /docs/auth - Low helpfulness (45%)                       │
│ • /docs/webhooks - High exit rate (78%)                    │
│ • /docs/errors - Zero search results linking here          │
└─────────────────────────────────────────────────────────────┘

2. Search Analytics

Text

┌─────────────────────────────────────────────────────────────┐
│ Top Searches This Week                                      │
│ 1. authentication (234)                                     │
│ 2. rate limits (189)                                        │
│ 3. webhook (156)                                            │
│ 4. pagination (98)                                          │
│ 5. typescript (87)                                          │
├─────────────────────────────────────────────────────────────┤
│ Zero-Result Searches (Content Gaps!)                        │
│ 1. "graphql" (45) - Consider adding GraphQL docs            │
│ 2. "python sdk" (32) - SDK page not indexed properly       │
│ 3. "batch requests" (28) - Need to document batch API      │
└─────────────────────────────────────────────────────────────┘

3. Page Performance

Text

┌─────────────────────────────────────────────────────────────┐
│ Best Performing Pages                                       │
│ Page                  │ Views  │ Helpful │ Scroll  │ Time  │
│ Quick Start           │ 4,521  │ 94%    │ 85%     │ 4:30  │
│ API Reference         │ 3,892  │ 88%    │ 62%     │ 2:15  │
│ Installation          │ 2,456  │ 91%    │ 78%     │ 2:45  │
├─────────────────────────────────────────────────────────────┤
│ Needs Improvement                                           │
│ Page                  │ Views  │ Helpful │ Scroll  │ Time  │
│ Advanced Config       │ 892    │ 45%    │ 32%     │ 0:45  │
│ Troubleshooting       │ 1,204  │ 52%    │ 41%     │ 1:20  │
│ Migration Guide       │ 654    │ 48%    │ 28%     │ 0:55  │
└─────────────────────────────────────────────────────────────┘

Setting Up Analytics#

Option 1: Google Analytics 4

HTML

<!-- Basic GA4 setup -->
<script async src="https://www.googletagmanager.com/gtag/js?id=G-XXXXX"></script>
<script>
  window.dataLayer = window.dataLayer || [];
  function gtag(){dataLayer.push(arguments);}
  gtag('js', new Date());
  gtag('config', 'G-XXXXX');
</script>

Custom events:

JavaScript

// Track documentation-specific events
gtag('event', 'docs_search', {
  search_term: query,
  results_count: count
});
 
gtag('event', 'docs_feedback', {
  page_path: location.pathname,
  rating: 'helpful' | 'not_helpful'
});

Option 2: Plausible (Privacy-focused)

HTML

<script defer data-domain="docs.yoursite.com"
  src="https://plausible.io/js/script.js"></script>

Custom events:

JavaScript

plausible('CodeCopy', { props: { page: location.pathname }});
plausible('Search', { props: { query: searchQuery }});

Option 3: Custom Solution

TypeScript

// Lightweight custom analytics
class DocsAnalytics {
  private queue: Event[] = [];
  private endpoint = '/api/analytics';
 
  track(event: string, properties: Record<string, any>) {
    this.queue.push({
      event,
      properties,
      timestamp: Date.now(),
      page: window.location.pathname,
      sessionId: this.getSessionId()
    });
 
    this.flush();
  }
 
  private async flush() {
    if (this.queue.length === 0) return;
 
    const events = [...this.queue];
    this.queue = [];
 
    await fetch(this.endpoint, {
      method: 'POST',
      body: JSON.stringify(events),
      headers: { 'Content-Type': 'application/json' }
    });
  }
}

Connecting Docs to Business Outcomes#

The ultimate metrics connect documentation to business value:

Support Ticket Deflection#

SQL

-- Measure support impact
SELECT
  topic,
  tickets_before_docs,
  tickets_after_docs,
  (tickets_before_docs - tickets_after_docs) as deflected,
  deflected / tickets_before_docs * 100 as deflection_rate
FROM support_metrics
WHERE docs_published IS NOT NULL
ORDER BY deflection_rate DESC;

Topic	Before	After	Deflected	Rate
Authentication	120/mo	45/mo	75	62%
Rate Limits	80/mo	25/mo	55	69%
Webhooks	95/mo	60/mo	35	37%

Time to First API Call#

Track how documentation impacts developer success:

JavaScript

// Track developer journey milestones
analytics.track('developer_milestone', {
  milestone: 'first_api_call',
  time_since_signup: timeDelta,
  docs_pages_viewed: pagesViewed,
  last_doc_page: lastDocPage
});

Correlate with documentation engagement:

Text

Developers who read "Quick Start":
  - Avg time to first API call: 23 minutes
  - Success rate: 89%
 
Developers who skipped docs:
  - Avg time to first API call: 2.4 hours
  - Success rate: 54%

Conversion Attribution#

JavaScript

// Track docs influence on signups
if (referrer.includes('/docs/')) {
  analytics.track('signup', {
    docs_influenced: true,
    last_doc_page: referrer,
    pages_viewed: sessionPageCount
  });
}

Using Data to Improve Docs#

The Improvement Loop#

Text

     ┌──────────────────────────────────────────┐
     │                                          │
     ▼                                          │
┌─────────┐    ┌─────────┐    ┌─────────┐    ┌──┴──────┐
│ Measure │ ─▶ │ Analyze │ ─▶ │ Improve │ ─▶ │ Verify  │
└─────────┘    └─────────┘    └─────────┘    └─────────┘

Case Study: Improving a Struggling Page#

Initial metrics (Authentication page):

Helpfulness: 45%
Scroll depth: 32%
Time on page: 45 seconds
High exit rate: 68%

Analysis:

Most users leave after first section
Zero-result searches for "OAuth"
Negative feedback mentions "outdated examples"

Improvements made:

Added OAuth section (addressing search gap)
Updated all code examples to latest SDK
Added troubleshooting section
Restructured for scannability

Post-improvement metrics:

Helpfulness: 78% (+33%)
Scroll depth: 71% (+39%)
Time on page: 3:15 (+430%)
Exit rate: 34% (-34%)

Prioritization Framework#

Score pages to prioritize improvements:

Text

Priority Score = (Traffic × Impact Potential × Effort Inverse)
 
Where:
- Traffic: Page views / total views
- Impact Potential: 100 - Helpfulness %
- Effort Inverse: 1 / estimated hours to fix

Page	Traffic	Impact	Effort	Score	Priority
Auth	15%	55	0.5	4.1	1
Webhooks	8%	48	0.33	1.3	2
Config	3%	55	0.25	0.4	3

Privacy Considerations#

Respect user privacy while gathering insights:

JavaScript

// Privacy-respecting analytics
const analytics = {
  track(event, properties) {
    // Don't track if user opted out
    if (localStorage.getItem('analytics_optout')) return;
 
    // Anonymize user data
    const data = {
      event,
      ...properties,
      // No PII - use hashed session ID
      sessionId: this.getAnonymousSessionId(),
      // Generalize location
      country: this.getCountryOnly(),
      // No exact timestamps
      hourOfDay: new Date().getHours()
    };
 
    this.send(data);
  }
};

Best practices:

Offer clear opt-out mechanism
Don't collect PII
Aggregate data for reporting
Comply with GDPR/CCPA
Document what you collect

Conclusion#

Documentation analytics transforms guesswork into informed decisions. Start with these steps:

Set up basic tracking - Page views, search, feedback
Build a simple dashboard - Top pages, problem pages, searches
Establish baselines - Know where you're starting
Identify one improvement - Pick lowest-performing high-traffic page
Measure the impact - Did changes improve metrics?
Iterate - Continuous improvement cycle

Remember: metrics inform decisions, they don't make them. Combine data with user feedback, support team insights, and your own expertise to create documentation that truly serves developers.

Want built-in documentation analytics? Dokly includes comprehensive analytics dashboards, search tracking, and feedback collection out of the box—so you can focus on improving your docs, not building analytics infrastructure.

Dokly

Documentation Analytics: Metrics That Actually Matter

Why Measure Documentation?#

The Documentation Metrics Hierarchy#

Essential Metrics to Track#

1. Search Behavior#

2. Page Performance#

3. User Journeys#

4. Code Interaction#

5. Feedback Signals#

Building a Documentation Dashboard#

Essential Dashboard Views#

Setting Up Analytics#

Connecting Docs to Business Outcomes#

Support Ticket Deflection#

Time to First API Call#

Conversion Attribution#

Using Data to Improve Docs#

The Improvement Loop#

Case Study: Improving a Struggling Page#

Prioritization Framework#

Privacy Considerations#

Conclusion#

Dokly

Ready to build better docs?