Attribution Window
Definition
Attribution Window: An attribution window is the time period after an ad click or view during which a resulting conversion is still credited to that ad. Meta and Google use different defaults, which is the single most common reason their dashboards disagree about the same sale.
What an attribution window is
An attribution window defines how long after an interaction a conversion still "counts" for that interaction. If you set a 7-day click window, a purchase made six days after someone clicked your ad is credited to that ad; a purchase made eight days later is not. Windows come in two flavors — click-through (the user clicked) and view-through (the user only saw the ad) — and the choice of window length and type quietly determines how much ROAS a channel appears to earn.
Click-through vs view-through
- Click-through attribution credits a conversion to an ad the user actually clicked. It's the higher-confidence signal — clicking is an intentional act.
- View-through attribution credits a conversion to an ad the user merely saw (an impression, no click). It's far weaker evidence of causation and is the main reason platform ROAS can look inflated. A 1-day view window is much more conservative than a 7-day view window.
Rule of thumb: trust click windows, treat view-through credit with skepticism, and confirm with incrementality when a channel leans heavily on view-through.
Meta vs Google defaults (why they disagree)
The two platforms ship different defaults, so the same purchase can be credited differently in each:
- Meta: the standard setting is 7-day click + 1-day view for consented users under Aggregated Event Measurement; for unconsented iOS traffic the window narrows (1-day-click is the conservative iOS default). Meta's options and AEM constraints are documented in its attribution settings help.
- Google: defaults to a 30-day click window with data-driven attribution for most conversion actions. Google's window options are described in the Google Ads attribution documentation.
Because Google's default window is much longer than Meta's, Google has more days in which to claim a conversion — so comparing the two platforms' raw ROAS without normalizing the windows is an apples-to-oranges error.
Illustrative example
A customer sees a Meta ad, clicks a Google Search ad two days later, and buys on day five. Under Meta's 7-day click window, Meta credits the sale; under Google's 30-day click window, Google also credits it. Both dashboards show the conversion, so summing them double-counts the single purchase. This is exactly why blended ROAS — one revenue number against one spend number — is the honest cross-platform scorecard.
How to handle attribution windows well
- Normalize before comparing channels. Set comparable click windows (or compare each platform only to its own history), never raw default-vs-default.
- Prefer click over view. When in doubt, weight click-through credit and discount view-through.
- Match the window to your conversion lag. Considered purchases need longer windows; impulse buys don't (see conversion-lag windows by channel).
- Reconcile to blended MER across the same period to catch the double-counting windows create.
Common mistakes
- Comparing Meta and Google ROAS at their native defaults. Different windows make this meaningless.
- Lengthening the window to "improve" ROAS. A longer window almost always shows higher ROAS — but it's reclassifying, not creating, value.
- Forgetting view-through is in the number. A big chunk of "ROAS" can be 1-day view credit; know your split.
How Admaxxer handles attribution windows
Admaxxer lets you view conversions across consistent click windows and compare them side by side, so a longer platform default doesn't silently flatter one channel over another. By reconciling windowed platform numbers against blended MER on actual revenue, it surfaces exactly where Meta's and Google's windows are crediting the same sale — turning a confusing dashboard discrepancy into a clear, normalized comparison.
Related glossary terms
Continue exploring the DTC ad-analytics vocabulary — every term in this glossary cross-links to the next.
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Ad Frequency
Ad frequency is the average number of times each unique person in your target audience saw your ad during a…
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Average Order Value (AOV)
Average Order Value (AOV) is total revenue divided by the number of orders in a period. It is one of the…
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Blended ROAS
Blended ROAS is total revenue across all channels divided by total paid ad spend. By using one revenue number…
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CAPI Match Rate
CAPI match rate — surfaced by Meta as Event Match Quality (EMQ) — is how well Meta can tie your server-side…
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Cohort LTV
Cohort LTV (lifetime value) measures the cumulative revenue per customer within a specific acquisition cohort…
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First-Click Attribution
First-click attribution assigns 100% of a conversion's credit to the first marketing touchpoint a user had…
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Incrementality
Incrementality is the revenue a marketing channel actually caused — the conversions that would not have…
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Linear Attribution
Linear attribution splits a conversion's credit evenly across every marketing touchpoint in the user's…
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Marketing Efficiency Ratio (MER)
MER (Marketing Efficiency Ratio) is total revenue divided by total marketing spend across all paid channels.…
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Meta Ad-Set Learning Phase
The learning phase is the period during which Meta's delivery system is still gathering signal on a new or…
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Payback Period
Payback period is the number of days it takes for a customer's cumulative gross profit to equal the cost of…
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Performance Max
Performance Max (PMax) is Google Ads' goal-based campaign type that serves across all Google inventory —…
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Pixel-to-Conversion Discrepancy
The pixel-to-conversion discrepancy is the gap between orders reported by your storefront (Shopify,…
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ROAS (Return on Ad Spend)
ROAS (Return on Ad Spend) is revenue generated divided by the ad spend that generated it. It is the most…
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iOS 14.5 Attribution
iOS 14.5 (released April 2021) introduced App Tracking Transparency, requiring Apple users to explicitly opt…
Frequently Asked Questions
What is Meta's default attribution window?
For consented users under Aggregated Event Measurement, Meta's standard setting is 7-day click plus 1-day view. For unconsented iOS traffic the window narrows, with 1-day-click as the conservative iOS default. The window you choose directly affects how much ROAS Meta reports.
What is Google's default attribution window?
Google defaults to a 30-day click window with data-driven attribution for most conversion actions. Shorter windows are available but reduce the data volume the model learns from. Because 30 days is much longer than Meta's default, Google has more days to claim a conversion.
Why do Meta and Google report different conversions for the same sale?
Mostly because their default windows differ — Meta's is short (7-day click), Google's is long (30-day click) — so the same purchase can fall inside both windows and be credited in both dashboards. Summing them double-counts the sale, which is why blended ROAS is the honest cross-channel number.
What's the difference between click-through and view-through attribution?
Click-through credits a conversion to an ad the user actually clicked — a high-confidence, intentional signal. View-through credits a conversion to an ad the user only saw, with no click — much weaker evidence of causation and a common source of inflated platform ROAS. Trust click windows; treat view-through with skepticism.
Does a longer attribution window inflate ROAS?
Yes — any conversion inside the window is credited regardless of other touches, so a longer window almost always shows higher ROAS. It reclassifies value rather than creating it. The honest check is to compare against blended MER on actual revenue across the same period.
How do I compare ROAS across Meta and Google fairly?
Normalize the windows first — set comparable click windows or compare each platform only against its own history — and discount view-through credit. Then reconcile both against blended MER on real store revenue to catch any conversions both platforms are claiming.