Amazon Attribution Timeframes: What you need to know

If you have been running PPC advertising on Amazon for a while, you have probably noticed one thing: you check the ACoS from three days ago in your Ads console. The next day, you check again, but suddenly the ACoS for the same day has changed and a sale has been added. But how is it possible that it still changes after such a long time?

Time can pass between an ad click and a purchase. This conversion delay means that Amazon may attribute later purchases to an earlier ad interaction. Report delivery can take additional time.

Do not judge campaign efficiency solely from conversion data that is still incomplete. An ACOS that looks high today can fall after additional purchases are attributed.

The attribution window limits how long a later purchase can be attributed to an earlier ad interaction. A purchase today can, for example, relate to a click from three days ago.

The Attribution Model of Amazon

For seller Sponsored Products, Amazon uses a last-click model. Other campaigns can also include eligible ad views depending on the ad format and billing method. The current Amazon Ads attribution rules distinguish these cases.

In the click-based example below, the purchase is attributed to the last eligible ad click and reported against that click date in the campaign report.

A customer can add a product to the cart and order later. The following example shows why the purchase date and reporting date can differ.

A customer can click an ad today and buy several days later. When comparing days, check whether the report can already include those later purchases.

Example:

A customer clicks on a PPC ad on Monday and adds the product to the shopping cart, where it remains for the time being. On Friday, the customer completes the purchase. Therefore, the purchase takes place on Friday but is attributed to the PPC campaign for Monday.

For this Sponsored Products example, the last eligible ad click receives the attribution when several eligible clicks occurred. Do not apply this simplified explanation unchanged to campaigns that support view attribution.

Alongside the time until purchase, the attribution window determines how long a purchase remains eligible for attribution.

What are the Amazon attribution windows?

Basically, the attribution window describes the time period during which a purchase can be attributed to a campaign click.

Example:

Attribution window of 7 days means: If the customer clicks today and makes a purchase anytime within the next 7 days, the purchase will be attributed to today's click. If the purchase occurs on the 10th day, it will no longer be attributed.

With a 30-day attribution window, the purchase on day ten would still be attributed to the original click.

A longer analysis window can include additional later purchases. Compare metrics with the same definition, or explicitly account for the difference.

For standard click-based metrics, these ad formats use the following windows:

• Sponsored Products for sellers: 7 days

• Sponsored Products for vendors: 14 days

• Sponsored Brands and Display: 14 days for click-attributed purchases

For Sponsored Products, some reports and analytics tools provide additional analysis windows. In sellerfox, you can compare the following windows:

• 1 day and 7 days

• 14 days and 30 days

Sponsored Brands and Display campaigns billed on viewable impressions can also attribute purchases to ad views. Since January 2026, Amazon has used an updated view-attribution model for certain placements. Check whether a metric includes purchases from clicks, views or both.

Campaign reports show attributed purchases against the ad interaction date. The actual purchase can happen later; this also applies to Sponsored Brands.

How you can use different attribution windows for your analysis

Comparable, completed analysis windows for Sponsored Products show how many attributed purchases happen earlier or later after a click.

If attributed purchases for 1D, 7D, 14D and 30D are approximately equal, almost all recorded purchases fall within the shortest window. This describes attributed purchases, not the behavior of every customer.

However, if you see that more purchases are attributed to 7D than to 1D, it indicates that many customers make their purchases between the 2nd and 7th day after clicking.

This is especially important for products where the customer does not buy directly, but takes longer to make their purchasing decision.

Are there differences between sellers and vendors?

Yes. Sponsored Products uses a standard window of 7 days for sellers and 14 days for vendors. Check both the campaign type and advertiser type before comparing reports.

A completed window alone does not guarantee that the report is fully available. Additional delays and later adjustments can change the reported values.

What you need to consider when optimizing

You now know the difference between an attribution window and the time until purchase. For analysis, the key question is which later purchases could still be missing from the selected report.

If you select the last seven days in the Ads console, later attributed purchases may still be missing. Treat those conversion values as provisional.

For completed comparisons, choose an end date whose attribution window has already closed and allow for report delivery time. A longer range, such as the last 30 days, still contains recent incomplete days.

Do not base bid changes solely on provisional conversion values. Budget limits or unusual spending can still require a prompt review.

Which attribution window should I use?

A shorter window provides data sooner but leaves out later purchases. First compare completed windows and decide how relevant the additional purchases are to your assessment. The following figures are illustrative examples, not a fixed optimization rule.

Example 1:

Revenue by attribution periods:

• 1D ... 1,000€

• 7 days ... 1,100€

• 14 days ... 1,150 euros

• 30 days ... 1,200 euros

In this example, about 83% of 30-day revenue falls within the 1-day window: €1,000 / €1,200. The shorter window shows most revenue sooner but leaves out about 17%. An ACOS based on that window is therefore not directly comparable with the 30-day ACOS.

Example 2:

Revenue by attribution windows:

• 1D ... 300€

• 7 days ... 1,900€

• 14 days ... 2,000€

• 30 days ... 2,000€

Here, 15% of 30-day revenue falls within the 1-day window and 95% within the 7-day window. The difference shows why an assessment after only one day would miss a large share of later purchases.

Faster PPC optimization through attribution time period analysis

Shorter windows can support an earlier provisional assessment. Selecting an analysis window does not change Amazon's attribution rules.

Even with a 1-day window, wait until the window has closed and the data is available. Also check how much later purchases usually change the assessment.

Past completed periods can provide a basis for estimating sales that have not yet been attributed. The result is a forecast, not a final ACOS.

Example:

Suppose the observed period has €800 in revenue within the 1-day window. In comparable completed periods, this amount represented 80% of the later total.

The estimate is then €800 / 0.8 = €1,000. You increase observed revenue by 25% to account for the missing 20% of the estimated total.

With €200 in ad spend, observed ACOS would be 25% and forecast ACOS would be 20%. The forecast is only accurate if the assumed purchase behavior holds for the new period.

This approach is already a kind of "predictive bidding" strategy and requires a lot of expertise. Of course, it is always associated with the risk that the assumed revenue may ultimately not be correct, leading to incorrect bid optimization. But with this example, we simply want to show you what is possible.

For Sponsored Products, sellerfox lets you compare metrics with 1-, 7-, 14- and 30-day windows. A useful comparison requires completed periods with available data.

Conclusion

Today you learned about the Amazon attribution windows and their importance for optimizing your campaigns. If you do not consider them, you will make decisions based on the wrong foundation. A mistake that could cost you important revenue.

Use sellerfox to analyze advertising and product metrics together and investigate changes. Try sellerfox free for 30 days and assess the analysis with your own data.