Ad blockers and your numbers
Some visitors run blockers that stop all analytics, including polite ones. Here is how much that matters, how to measure it honestly, and what we think about circumvention.
- Key takeaways
- Blockers stop all analytics; your undercount depends on audience (few % → 25%+ for dev crowds).
- Measure your own gap: compare a trusted server-side count to BobRay for one URL.
- We don't ship blocklist bypasses, blocked users expressed a preference we respect.
The real-world impact
Blocker usage is heavily audience-dependent: mainstream consumer sites typically lose a few percent of pageviews; developer-heavy audiences can lose a quarter or more. Everyone's analytics undercounts by this amount, comparisons between tools remain fair because all are affected similarly.
Estimate your own gap
- Pick a page with a server-side count you trust, an order confirmation, a signup success page.
- Compare a week of server events to BobRay pageviews for the same URL.
- The ratio is your audience's blocker rate; apply it mentally to totals, trends are unaffected.
Our stance on “bypasses”
Some vendors proxy their script through your own domain to dodge blocklists. We do not offer this. A visitor who installed a blocker expressed a preference, and a privacy-first tool that sneaks past it stops deserving the name. Your trend lines, conversion rates, and comparisons stay perfectly valid without it.
Common pitfalls
The mistakes we see most often on this topic, so you can skip them entirely.
- 'Fixing' the gap with a proxy bypass and calling it privacy-first.
- Comparing absolute counts across tools with different block exposure.
- Panicking at launch-day dips that are actually HN's blocker-heavy audience.
Quick reference
| Typical consumer gap | Low single digits % |
| Developer audiences | Can exceed 25% |
| Bypass offered | No, on principle |
| Trends affected | No, ratios hold |