Web Analytics
Web analytics shows how people use your website, but modern tools often miss a large part of your traffic.
Web analytics is about understanding
Analytics tools collect data to answer questions like: Where do visitors come from? What do they do? What leads to conversions?
Pageviews
Total pages loaded
Visitors
Unique people visiting
Sessions
Interactions in a time window
Bounce rate
Left after one page
Conversions
Actions that matter
Traffic sources
Where visitors come from
But today, how this data is collected, and what is missing, varies significantly between tools. That difference defines modern web analytics.
The problem
100
visitors arrive
Tracked
60
Missing
40
How web analytics changed
Web analytics used to be simple. You added a script, and every visitor was tracked.
That model no longer works.
Today, consent banners, ad blockers, and browser restrictions mean 20-60% of visitors are missing from most analytics reports.
This is the consent analytics gap: the difference between actual traffic and what your tools report.
The 4 approaches to web analytics
Not all analytics tools work the same way. Each approach solves different problems with different tradeoffs.
Privacy-first analytics
Simple Analytics, Plausible, Fathom
Measures traffic without cookies or personal data. No consent banners needed. Increasingly preferred by teams that want complete traffic data without legal overhead.
Best for:
Websites that prioritize privacy, simplicity, and complete data.
Limitations:
No user-level tracking or deep attribution.
Traditional analytics
Google Analytics, Adobe Analytics
Tracks individual users across sessions using cookies. The original model for web analytics, now increasingly problematic due to consent requirements.
Best for:
Teams needing deep attribution for paid advertising.
Limitations:
Requires consent. Significant data loss. Complex setup (GA4).
Product analytics
Amplitude, Mixpanel, PostHog
Built for tracking individual user behavior inside applications: funnels, retention, feature adoption. Not designed for website analytics.
Best for:
Apps needing behavioral cohorts and product-led growth metrics.
Limitations:
Requires consent. Complex setup. Overkill for most websites.
Self-hosted analytics
Matomo, Umami
Open-source tools you run on your own servers. Full control, but you maintain everything, and most configurations still require consent.
Best for:
Teams with DevOps resources and strict data residency requirements.
Limitations:
High maintenance. Often still requires consent banners.
How analytics tools compare
Tools differ along simplicity and data completeness.
Privacy-first
No cookies, no PII
Middle ground
Configurable privacy
Tracking-heavy
Cookies, user tracking
Lightweight, privacy-first
Tracking-heavy analytics
Some privacy-first tools still rely on anonymized identifiers. Simple Analytics avoids tracking entirely.
How to choose the right approach
Start with your constraints, not features.
Privacy vs tracking depth
Tools that track individuals provide more granular data but require consent and lose traffic.
Learn moreSimplicity vs complexity
Enterprise tools offer deep customization but require setup and dedicated analysts.
Learn moreMarketing vs product
Website analytics focuses on traffic. Product analytics focuses on in-app behavior.
Compliance requirements
If you operate in the EU, tools without cookies remove most compliance overhead.
Learn moreIf you want simple, complete website analytics without consent banners, a privacy-first approach is usually the best fit.
A better approach
Modern web analytics
A better approach is emerging: measuring website traffic without requiring consent.
Instead of tracking individuals, these tools focus on aggregate data, reducing data loss and simplifying compliance.
100% traffic visibility
No data lost to consent
No cookies or consent banners
GDPR-compliant by design
Setup in a few minutes
One script, instant insights