Attribution windows (also called lookback windows) set how long after a click or view a conversion is still counted for that touch. A short window credits only fast decisions, and a long one credits interactions that may have had little to do with the outcome.
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Match it to your buying cycle
A product bought in a day suits a short window. A B2B SaaS deal that takes weeks or months needs a longer one, or most conversions will be credited elsewhere.
Compare like with like
Different tools use different windows by default, which is a leading reason their numbers disagree. Check each tool's setting before comparing reports.
Common mistakes
Comparing platforms on default windows
A mismatch in windows can explain the entire gap between two reports.
Frequently Asked Questions
GA4 offers lookback window settings for key events in its attribution settings. Check the current options in your property.
Keep reading
- Conversion window: A conversion window is how far back an analytics or ad tool looks for touchpoints to credit when a conversion happens, such as 30 or 90 days.
- Marketing Attribution: The practice of assigning credit for sign-ups, pipeline and revenue to the channels and touchpoints that led to them, including organic search.
- Data-driven attribution: Data-driven attribution uses a statistical model of converting and non-converting paths to share credit across touchpoints. It is GA4's default model.
- Last-click attribution: Last-click attribution gives all credit for a conversion to the final interaction before it, which tends to favor branded search and email.
- Assisted conversions: Assisted conversions count conversions where a channel appeared in the path but was not the final touch, showing its supporting role.
- Bot traffic: Bot traffic is automated visits that inflate analytics and skew conversion rates unless filtered out.
- Channel grouping: Channel grouping sorts traffic sources into buckets like Organic Search, Paid Search, Email and Referral using rules based on source, medium and campaign.
- Cohort analysis: Cohort analysis groups users by a shared starting point, such as sign-up week, and tracks how each group behaves over time.
