Conversions

About the Attribution Models

To learn about attribution and the Model Comparison Tool, read Attribution Modeling Overview.

When evaluating the effectiveness of your channels, use attribution models that reflect your advertising goals and business models. Regardless of the model(s) you use, test your assumptions by experimenting. Increase or decrease investment in a channel as guided by the model output, then observe your results in the data.

About the Models

Last Interaction Model icon The Last Interaction model attributes 100% of the conversion value to the last channel with which the customer interacted before buying or converting.
 
When it's useful: If your ads and campaigns are designed to attract people at the moment of purchase, or your business is primarily transactional with a sales cycle that does not involve a consideration phase, the Last Interaction model may be appropriate.

 

Icon for Last Non-Direct and last AdWords Click The Last Non-Direct Click model ignores direct traffic and attributes 100% of the conversion value to the last channel that the customer clicked through from before buying or converting. Google Analytics uses this model by default when attributing conversion value in non-Multi-Channel Funnels reports.
 
When it's useful:

Because the Last Non-Direct Click model is the default model used for non-Multi-Channel Funnels reports, it provides a useful benchmark to compare with results from other models.

In addition, if you consider direct traffic to be from customers who have already been won through a different channel, then you may wish to filter out direct traffic and focus on the last marketing activity before conversion.

 

Icon for Last Non-Direct and last AdWords Click The Last AdWords Click model attributes 100% of the conversion value to the most recent AdWords ad that the customer clicked before buying or converting.
 
When it's useful: If you want to identify and credit the AdWords ads that closed the most conversions, use the Last AdWords Click model.

 

First Interaction Model icon The First Interaction model attributes 100% of the conversion value to the first channel with which the customer interacted.
 
When it's useful: This model is appropriate if you run ads or campaigns to create initial awareness. For example, if your brand is not well known, you may place a premium on the keywords or channels that first exposed customers to the brand.

 

Linear Model icon The Linear model gives equal credit to each channel interaction on the way to conversion.
 
When it's useful: This model is useful if your campaigns are designed to maintain contact and awareness with the customer throughout the entire sales cycle. In this case, each touchpoint is equally important during the consideration process.

 

Time Decay Model icon If the sales cycle involves only a short consideration phase, the Time Decay model may be appropriate. This model is based on the concept of exponential decay and most heavily credits the touchpoints that occurred nearest to the time of conversion. The Time Decay model has a default half-life of 7 days, meaning that a touchpoint occurring 7 days prior to a conversion will receive 1/2 the credit of a touchpoint that occurs on the day of conversion. Similarly, a touchpoint occuring 14 days prior will receive 1/4 the credit of a day-of-conversion touchpoint. The exponential decay continues within your lookback window (default of 30 days).
 
When it's useful: If you run one-day or two-day promotion campaigns, you may wish to give more credit to interactions during the days of the promotion. In this case, interactions that occurred one week before have only a small value as compared to touchpoints near the conversion.

 

Position Based Model icon The Position Based model allows you to create a hybrid of the Last Interaction and First Interaction models. Instead of giving all the credit to either the first or last interaction, you can split the credit between them. One common scenario is to assign 40% credit each to the first interaction and last interaction, and assign 20% credit to the interactions in the middle.
 
When it's useful: If you most value touchpoints that introduced customers to your brand and final touchpoints that resulted in sales, use the Position Based model.

 

Custom Credit Rule Examples

When creating a custom model, you specify custom credit rules. Here are a few examples of rules you may wish to apply.

If you consider direct touchpoints as from customers who have already been won through another marketing effort, you may wish to decrease the value of the direct channel. To reduce by half the credit given to direct traffic that is the last touchpoint in a series of sessions:

Include Position in Path Exactly Matching last
and
Include Source Exactly Matching direct

credit 0.5 times other interactions in the conversion path

If you consider generic keyword sessions to be more valuable than brand keyword sessions, you will want to decrease the credit given to your brand keyword channel. This allows you to appropriately value the channels in the funnel that introduced the customer to your brand. To reduce by half the credit given to branded or navigational search terms anywhere in the path, specify keywords or use a regular expression to specify [brand terms]:

Include Keyword Containing [brand terms]

credit 0.5 times other interactions in the conversion path

To give no credit to sessions in the path that result in a bounce:

Include Bounce Sessions Exactly matching Yes

credit 0 times other interactions in the conversion path