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Attribution Modes, Attribution Windows and Conversion Lag
Attribution Modes, Attribution Windows and Conversion Lag

This article explains and discusses common questions with respect to attribution modes, attribution windows and conversion lag

Tim Schouten avatar
Written by Tim Schouten
Updated over 2 weeks ago

There is a lot of related terminology with respect to attribution models. This article will help you to understand exactly what these terms mean and how you can use them during analysis, to make sure you make the most of the options offered in the platform.

Attribution Modes

In Billy Grace, there are two different types of Attribution Modes, Session Date and Event Date. Both are explained below:

  • Session Date: in this mode, for every touchpoint that receives credit for an event, the credit is allocated to the day the touchpoint occurred.

Event Date: in this mode, for every touchpoint that receives credit, the credit is allocated to the day on which the event occurred.

This is best illustrated by an example of a customer journey and how the credit would be allocated between the different modes:

  • A visitor visits your website through a Meta ad (campaign A) on March 10

  • On March 14 the visitor comes back through a Google search ad (campaign B) and makes a purchase

Let's assume, that in this example the attribution model gives 90% (0.9) credit to the Meta ad and 10% (0.1) to the Google ad. Let's see how both Attribution Modes would handle reporting this conversion.

Session Date

If we assume this is the only event that occurred in the period, the Session Date report would like this:

Campaign

Date

Number of Events

Campaign A (Meta)

March 10

0.9

Campaign B (Google)

March 14

0.1

As you can see here, not all credit is allocated on the day the event occurred! Intuitively, you could imagine this as the credit being divided back to the days which caused the conversion.

Benefits of this Attribution Mode are:

  • The Session date Attribution Mode is best suited for judging marketing performance on a specific day using metrics related to spend (ROAS, CPA etc). This, as it allocates credit to the specific day on which it caused a click (and you also spend the amount to get that click!)

Drawbacks of the Session date Attribution Mode are:

  • For longer attribution windows, it is unclear how far back the conversion is being divided. A good example is the 'unlimited' attribution window - in this case part of the attribution might be given to a touchpoint as far as 6 months back! This effect enlarges any conversion lag effects in the reports (read more here)

Event Date

For this, the event date report would be:

Campaign

Date

Number of Events

Campaign A (Meta)

March 14

0.9

Campaign B (Google)

March 14

0.1

In the table above, all attribution for the specific event is given to the date the event occurred on. This means that campaign A can get credit on March 14, even though there might not have been any session through or spend for the campaign that day!

Benefits of the Event Date attribution mode are:

  • The attribution credit is always given on the date the event occurred. This helps in reporting and answering questions such as:

    • Of the events that occurred this month, how many have been caused by Meta?

    • What is the total number of events caused by paid channels this month?

  • As the credit is always given on the date the event occurred on, larger attribution windows are easier to interpret.

Drawbacks of the Event Date attribution mode are:

The attribution credit is not necessarily related to the spend you made on that day for your marketing channels. This makes metrics such as ROAS and CPA hard to interpret and prone to wrong budget decisions.

This is best exemplified by an example:

If in the above example, you spend

  • 100 euros on March 10 for campaign A

  • 1 euro on March 14 for campaign A

Session date - March 10 = (100/0,9) and March 14 = (1/0,1)
Event date - March 10 = 0 and March 14 = (100/0,9) + (1/0,1)

the Session Date CPA will be €111.11 (100 / 0.9), while the Event Date will be €1.11 (1 / 0.9)!

For this reason, metrics related to spend are best analyzed using the Session Date report.

Attribution Windows

Attribution windows are related to the period before an event during which you allow a touchpoint to claim attribution for an event. An example can illustrate this:

  • Customer has a touchpoint 1 for campaign A on March 3

  • Customer has touchpoint 2 for campaign B on March 11

  • Customer has a final touchpoint 2 for campaign C on March 14 before purchasing

With attribution window on unlimited, the credit is divided as 80% (0.8) for touchpoint 1 and 10% (0.1) for touchpoint 2 and 3. Different attribution windows would divide this as:

1-Day attribution window:

Touchpoint

In Window

Credit Allocated

Campaign A (1)

No

0

Campaign B (2)

No

0

Campaign C (3)

Yes

0.1 / 0.1 = 1

You see here that campaign C is the only touchpoint within the attribution window and thus gets all the credit.

7-day attribution window:

Touchpoint

In Window

Credit Allocated

Campaign A (1)

No

0

Campaign B (2)

Yes

0.1 / 0.2 = 0.5

Campaign C (3)

Yes

0.1 / 0.2 = 0.5

As you can see, campaign B and C are within the attribution window and thus the credit is split between them.

30-day (and unlimited) attribution window:

Touchpoint

In Window

Credit Allocated

Campaign A (1)

Yes

0.9 / 1 = 0.9

Campaign B (2)

Yes

0.1 / 1 = 0.1

Campaign C (3)

Yes

0.1 / 1 = 0.1

You see here that all touchpoints are within the attribution window, and thus the credit is split between them.

This image displays attribution windows visually:

Food for thought when selecting attribution windows:

  • If you select a short attribution window, you need to be aware of the fact that this might cut out essential parts of the customer journey that caused certain events to occur. Whether this is relevant for you, depends on the average journey length before a customer converts.

When selecting a longer attribution window with a date period such as 'last 7 days' or 'last 30 days', you could generally see a decline in results when using the Session Date. This is, because of conversion lag (read more about conversion lag here) and the fact that the touchpoint is being moved 'out of' the period you've selected.

In addition, the future conversions for which touchpoints can still get credit did not occur yet! Attribution windows determine how long a touchpoint remains eligible to receive credit for a conversion. Essentially, when you set an attribution window (for example, 30 days), any conversion occurring within that period after a touchpoint can be attributed to it.

How It Works with the 'Session Date' Attribution Mode

  • Open vs. Closed Windows:
    When using the 'Session Date' Attribution Mode, the attribution window stays "open" until the last date of your selected period plus the number of days in your attribution window has passed. Once this period has elapsed, the window is "closed," and no further conversions can be credited to touchpoints in that period.
    ​

  • Examples:

    • For a date range of 1–10 March:

      • 1-Day Attribution Window:
        The window closes on 11 March (10 March + 1 day). Touchpoints will only receive credit for conversions up to and including 11 March.

      • 7-Day Attribution Window:
        The window closes on 17 March (10 March + 7 days). Here, touchpoints can get credit for any conversion occurring until 17 March.

Choosing the Right Attribution Window

  • A shorter attribution window (e.g., 1-day) gives you faster insights but may cut off parts of the customer journey.

  • A longer attribution window (e.g., 30-day) provides a fuller picture but delays when the data is finalized.

  • An unlimited attribution window in "Session Date" mode never closes, which can make it harder to analyze finalized data.

Conversion lag

Conversion lag highlights the fact that conversions don't always happen immediately after a customer interacts with a marketing touchpoint. Some customers may take minutes, hours, days, or even weeks to convert.

What this means is that for more recent days, your ads might have had touchpoints which will receive credit at a later point, but have not done so yet. This might lead to the metrics of these ads (such as ROAS/ CPA/ Attributed Revenue) still increasing for days (or weeks/months!) after the day has passed, as customer are slowly converting.

This effect will be strongest for recent days, as simply put the most recent touchpoints have the highest likelihood of still converting and their attribution windows are not 'closed' yet. The effect of conversion lag also ties into that of closed/open attribution windows. Read more about that here.

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