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Attribution models

Time-to-conversion distribution

The time-to-conversion distribution is the spread of elapsed times between an early interaction and the eventual conversion across a population. Reading it reveals how much of your conversion volume is fast versus slow, which is essential for choosing lookback windows, interpreting recent-period reports, and avoiding the mistake of judging campaigns before slow conversions land.

Verified against primary sources

What this means

Some conversions happen minutes after the first interaction; others take days or weeks. Plotting the elapsed time from first (or last) touch to conversion across many conversions gives the time-to-conversion distribution — typically right-skewed, with many quick conversions and a long tail of slow ones.

This shape tells you how patient your measurement must be. A business with a long tail cannot judge a campaign in its first days, because much of its eventual conversion volume has not yet arrived.

Why it drives window choices

Lookback and reporting windows should be informed by the distribution, not guessed. If conversions routinely take three weeks, a seven-day window discards real credit; if nearly all convert within a day, a 90-day window mostly adds noise and stale paths.

The distribution also explains conversion lag in recent reports: the latest days always look weak because their slow conversions are still pending. Google documents conversion-lag and path-length reports that expose this. The practical move is to read recent periods as provisional and let the tail mature before drawing conclusions.

How it appears in analytics and logs

A long tail in time-to-conversion means recent periods under-report; conversions for those interactions have not happened yet, not that the campaign failed.

Diagnostic use case

Inspect the time-to-conversion distribution to set lookback and reporting windows that capture slow conversions and to avoid under-counting recent campaigns.

What WebmasterID can help detect

WebmasterID's first-party timestamps on path touches and conversions let you build a time-to-conversion view without third-party identifiers.

Common mistakes

Privacy and accuracy notes

The distribution aggregates elapsed-time data across users, not individual identities. This page is educational, not legal advice.

Related pages

Sources and verification notes

Last reviewed 2026-06-24. Facts are checked against primary/official sources where available; uncertain specifics are marked “Data not yet verified” rather than guessed.