7-day click, 1-day view, data-driven: what each setting actually changes.
Someone changed an attribution setting, the reported numbers moved, and nobody can explain whether performance actually changed.
4 min read
An attribution window is a rule about time: how long after somebody sees or clicks an ad may that ad still claim credit for a purchase. It sounds like a reporting preference. It is not — on Meta it also determines what the delivery system optimizes toward, which makes it a campaign decision wearing a reporting costume.
This is a short, practical explanation of what each common setting means and what happens when you change it.
The settings you will actually encounter
| Setting | What it claims | Effect on reported numbers |
|---|---|---|
| 1-day click | Purchases within 24 hours of clicking | Most conservative. Roughly matches last-click store reporting. |
| 7-day click | Purchases within a week of clicking | The honest middle. Captures considered purchases without crediting passive impressions. |
| 7-day click, 1-day view | The above, plus purchases within a day of merely seeing the ad | Meta's default. Typically the largest single source of over-reporting. |
| Data-driven (Google) | Credit distributed across touchpoints by modeled contribution | Google's default. Spreads credit rather than giving it all to the last click. |
The word doing the work in row three is seeing. A view-through conversion requires no interaction whatsoever. The shopper scrolled past. Meta counts it if a purchase follows within the window.
Why changing the window changes actual performance, not just the report
This trips up experienced marketers. On Meta, the attribution setting is not only how conversions are counted for you — it is also how they are counted for the delivery system while it learns.
Set an ad set to 7-day click only, and the system learns from click-driven purchases. It will find people who click and buy. Set it to include 1-day view, and the system also learns from people who saw and bought, which pushes delivery toward cheaper impression-heavy placements and broader audiences.
Neither is wrong. But it means changing the window mid-flight resets what the campaign is chasing, and the numbers on either side of the change are not comparable. Treat it as a structural change with a learning period, not as a toggle.
Matching the window to your purchase cycle
The right window is the one that covers how long your customers actually take to decide. Most brands never check this, and use the default on a purchase cycle it does not fit.
Your store already knows the answer. Look at time from first session to purchase for new customers. If the median is under a day, a 1-day or 7-day click window describes reality and a longer one mostly adds noise. If the median is five days, a 1-day click window will systematically under-credit your prospecting and make it look worse than it is.
- Impulse categories — snacks, low-price accessories, fast fashion under $30: short cycle, short window
- Considered categories — supplements, skincare regimens, home goods, anything over about $80: multi-day cycle, 7-day click is the honest minimum
- High-consideration — furniture, electronics, premium apparel: cycle often exceeds a week, and no window will describe it well; lean on blended efficiency instead
The Google side: data-driven attribution
Google Ads defaults to data-driven attribution, which distributes credit across the touchpoints in a conversion path based on modeled contribution rather than handing it all to one interaction.
This is generally an improvement over last-click, and it is why a Google Ads conversion count can include fractional values — 0.4 of a conversion attributed to one keyword and 0.6 to another. It also means Google Ads conversions rarely reconcile cleanly to store orders, for the same structural reason Meta's do not.
The practical implication for ecommerce: do not compare a Meta ROAS to a Google ROAS and conclude one channel is better. They are computed under different rules. Compare each to its own history, and compare the channels to each other only through blended efficiency or a spend test.
Common questions
What does 7-day click, 1-day view mean?
The ad claims credit for a purchase made within seven days of a click, or within one day of the shopper simply seeing the ad without clicking. It is Meta's default and the view-through part is usually the biggest single cause of over-reporting.
Will changing my attribution window hurt performance?
It can, temporarily. On Meta the setting also governs what the delivery system optimizes toward, so a change restarts learning. Expect an unsettled period and avoid changing it during a peak trading window.
Which attribution window should an ecommerce brand use?
Match it to your median time from first visit to purchase, which your store analytics already report. Under a day suggests short windows; a multi-day cycle needs at least 7-day click, or prospecting will look worse than it is.
Why does Google Ads show fractional conversions?
Data-driven attribution splits credit across several touchpoints, so a single sale can be recorded as parts of a conversion across multiple keywords or campaigns.
Can I turn off view-through conversions?
You can choose an attribution setting that excludes them. Do it deliberately and expect reported volume to fall — the sales did not disappear, the credit rule changed.
How Glimmio handles this
Glimmio labels every performance figure with the platform that reported it and the time it was last synced, so a number is never read out of context.
Because the platform reads your accounts through official connections rather than a separate tracking script, it sees the same attribution settings your team sees — and flags when a change to one of them explains a change in reported results.
- Manual approval by default — nothing runs unattended
- New campaigns and ads are always created paused
- 7-day recovery window on eligible changes
- 48 permissions across 13 roles, scoped per client account
Go deeper on this
The product pages and setup guides that cover what this article describes.
Searches this answers
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