The web analytics glossary. Plain definitions of the terms that end up in a report, with the formula, a worked example, and an honest note on what each number cannot tell you.

What do web analytics terms actually mean?

Web analytics terms describe three different things: units of traffic such as pageviews, sessions and visitors, rates calculated from them such as bounce rate and conversion rate, and methods applied to them such as funnels and cohort analysis. Most confusion comes from tools defining the same word differently.

That last point is the reason this glossary exists. Bounce rate, session and unique visitor all mean subtly different things depending on which tool produced the number, and a report that mixes two definitions is worse than one that has neither. Every entry here states the definition it is using, and where tools disagree, it says so.

What is web analytics?

Web analytics is the collection, measurement and analysis of what happens on a website: who visits, where they came from, which pages they see, and what they do before they leave. Its purpose is to inform decisions about the site rather than simply to report traffic.

What is the difference between a pageview, a session and a visitor?

They are three counts of the same traffic at three levels of grouping. A pageview is one view of one page. A session groups a visitor's pageviews into a single visit, ending after 30 minutes of inactivity. A unique visitor is one person counted once in the reporting period, however many sessions they produced.

Which analytics metrics actually matter?

The ones tied to an outcome. Traffic volume on its own answers nothing, so instrument conversions first, then read acquisition and behaviour metrics as explanations for how conversions moved. Three metrics everyone agrees on beat forty nobody has read.

Do these metrics work without cookies?

Almost all of them. Everything scoped to a session works cookielessly: pageviews, sessions, sources, campaigns, funnels, engagement and revenue. What needs persistent identity is anything spanning days, such as retention, cohorts and DAU/MAU, which needs either an optional cookie mode with consent or your own user id.

Why do two analytics tools report different numbers for the same site?

Different session timeouts, different bot filtering, different handling of client-side navigation in single-page apps, and different exposure to adblocking. A gap of 10% to 20% between two tools on the same site is normal. Compare each tool against its own history rather than against the other.

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