Why I Quit Google Analytics (And Built Something Better)

The Breaking Point

Last month, I ran a PageSpeed Insights test on my blog. The results made me angry:

Performance Score: 67/100
Largest Contentful Paint: 3.2s
Total Blocking Time: 890ms

The culprit? Google Analytics and its 44KB of JavaScript.

But performance was just the beginning. The real issues ran deeper.

Why Google Analytics Had to Go

1. Privacy Nightmare

My blog about mental health and personal development was sending every visitor's data to Google:

IP addresses
Device fingerprints
Browsing behavior
Cross-site tracking

How could I write about trust while betraying my readers' privacy?

2. GDPR Compliance Headache

Cookie banners. Privacy policies. Data processing agreements.

I spent more time on compliance than writing. One wrong setting and I'd face fines up to €20 million.

3. Useless Metrics

Google Analytics told me:

Bounce rate: 71.3%
Average session duration: 1:34
Pages per session: 1.43

But it couldn't answer:

Which posts actually helped people?
How far did readers scroll?
What made them engage?

4. Ad Tech Bloat

GA4 is built for advertisers, not bloggers. Features I never used:

Audience segments
Attribution modeling
E-commerce tracking
Google Ads integration
200+ dimensions and metrics

The Alternative: Build vs Buy

I evaluated privacy-focused alternatives:

| Service | Cost/month | Pros | Cons | |---------|------------|------|------| | Plausible | $9 | Simple, privacy-first | Another subscription | | Fathom | $14 | Great UX | Limited custom events | | Umami | $0 (self-host) | Open source | Hosting complexity | | Simple Analytics | $19 | EU-based | Expensive for blogs |

Then I realized: I could build exactly what I need in a weekend.

What I Built Instead

A lightweight analytics system that:

No cookies: Uses SHA-256 hashed visitor IDs
Real engagement: Tracks scroll depth and read time
Fast: 2KB script, no external requests
Free: Uses Vercel KV (10K requests/day free)
Simple: ~300 lines of code total

The Results

After switching from Google Analytics:

PageSpeed score: 98/100 (+31 points)
LCP: 0.8s (-2.4s)
Zero cookie banners
Better insights: I know which content resonates

Code Snippets

Here's the core tracking hook:

export function usePageView() {
  useEffect(() => {
    const trackView = async () => {
      await fetch('/api/analytics/track', {
        method: 'POST',
        headers: { 'Content-Type': 'application/json' },
        body: JSON.stringify({
          path: window.location.pathname,
          referrer: document.referrer
        })
      })
    }
    
    trackView()
  }, [])
}

And the privacy-preserving visitor ID:

// No cookies, resets daily
const visitorId = crypto
  .createHash('sha256')
  .update(ip + userAgent + new Date().toDateString())
  .digest('hex')

What You Can Do Today

Option 1: Switch to Privacy-First Analytics

Plausible - Simple and affordable
Fathom - Great for content sites
Umami - Self-hosted option

Option 2: Build Your Own

My implementation is open source: View the code

Requirements:

Next.js or similar framework
Any database (or Vercel KV)
2-4 hours of coding

Option 3: Go Analytics-Free

Radical idea: Do you really need analytics?

If you're not actively using the data to improve content, you're just collecting it for vanity.

The Bigger Picture

Quitting Google Analytics is about more than performance or privacy. It's about:

Owning your infrastructure - No dependency on big tech
Respecting your readers - Privacy as a feature
Focus on what matters - Engagement over page views
Learning by building - Best way to understand analytics

One Month Later

Since ditching Google Analytics:

Site loads 3x faster
Zero privacy concerns
More meaningful metrics
Readers thank me for respecting privacy
I actually check my analytics (because they're useful)

Your Move

Google Analytics is the default choice, but defaults aren't always right.

Ask yourself:

What metrics actually help you improve?
Is reader privacy worth 44KB of JavaScript?
Could you build something better?

Sometimes the best solution isn't the most popular one. Sometimes it's the one you build yourself.

Want to build your own analytics? Check out my detailed technical guide or grab the source code on GitHub.

What's your experience with analytics? Let me know on Twitter or Reddit.