About the default MCF attribution models
Analytics provides the following default attribution models in the Multi-Channel Funnels Model Comparison Tool. You can also create your own custom models in the tool.
Default attribution models
- 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.
- 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. 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.
- The Last Google Ads Click model attributes 100% of the conversion value to the most recent Google Ads ad that the customer clicked before buying or converting.
When it's useful: If you want to identify and credit the Google Ads ads that closed the most conversions, use the Last Google Ads Click model.
- 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.
- 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.
- 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 occurring 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.
- 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.