Small differences between our click numbers and your analytics tool are completely normal and, in almost every case, mean your tool is undercounting, not that our figures are inflated. Here's why.

Sometimes, though, the gap isn't small at all, and you might see a substantial difference, which can be unsettling when you first notice it. That's still expected, and the same root causes below explain it. These factors not only cause minor discrepancies; they compound. So a large difference usually isn't a sign that something is broken or that our numbers are wrong. It usually means several of the effects below are happening at once.

Our tracking is deliberately simple and honest: when one of our users clicks through to your website, we register one click. What we can't control is everything that happens after that click on your website, whether your site is online, loads quickly, and successfully records the visit.

Between a click and a "session" (or "visit") in an analytics tool sits a whole chain of events that all have to succeed, and several everyday factors break that chain:

• A click is not the same as a measured session. The visitor has to land on your site, the page has to load, and the tracking script has to fire before they navigate away. Google itself confirms that someone can click but close the browser or navigate away before the tracking code fully loads, resulting in a click but no session. A slow connection or a quick "back" tap has the same effect.
• Ad blockers and privacy browsers. Nearly a third of internet users worldwide use ad blockers (at least 29.5% of the global population, an estimated 1.77 billion people, and close to half in some markets such as Germany). These tools work by blocking analytics and tracking scripts along with ads — so the visit happens, but the analytics tool never sees it.
• Cookie and consent banners. Under GDPR, when a visitor declines tracking consent, your analytics tool may collect nothing, or only limited, modelled data. Google's own documentation describes how, in consent mode, it falls back to machine-learning modelling for users who decline cookies, producing estimates rather than exact counts. In Europe, especially, this hides a meaningful share of real visits.
• Lost referrer = counted as "direct" traffic. When referrer information is stripped out, which routinely happens with in-app browsers, messaging apps, redirects and privacy settings - your tool can't tell the visit came from eventplanner.net (or one of our other domains) and files it under "direct" instead. This is the single biggest reason analytics tools overestimate direct traffic and underestimate referral traffic. In a well-known Groupon experiment, roughly 60% of "direct" traffic turned out to be misattributed, and independent testing by SparkToro found that visits from apps like WhatsApp, Slack and TikTok are recorded as "direct" essentially 100% of the time.
• Data sampling in your analytics tool. In Google Analytics 4, standard reports use your full data, but the deeper "Explorations" reports switch to an estimate based on a sample once a query crosses Google's processing thresholds. The same query can then return slightly different numbers.
• Different bot filtering. We actively filter out bot and automated traffic so your reporting stays clean, and we run regular checks on our advertisers' websites. Other tools filter bots too, but with different rules, so the two will rarely match click-for-click.
• Improper tracking setup or technical issues on your website. Analytics relies on the tracking code being installed correctly and firing on every page. A tag that's missing from some pages, placed too low in the page code, loads too late, is misconfigured, or is held up by other technical issues on your site can cause visits to go uncounted, sometimes producing very large discrepancies. If the gap is unusually wide, it's worth having your webmaster verify the tracking implementation.

The takeaway: no two measurement systems ever match exactly, by design. What matters is the trend over time, not click-for-click parity with any single tool, and you can trust that the clicks we report reflect real interest from real people.