Multi-Touch Attribution - Path Configurations

Path Configurations

Path configurations are used to customize the way each user’s path is constructed from individual sessions. By customizing how paths are constructed, ChannelMix allows you to target specific business questions with your attribution model - which is trained on these reconstructed paths. ChannelMix supports two types of configurations: path compression and the direct filter.

Path Compression

When path compression is enabled, sequences of identical interactions are compressed into a single interaction. The compressed interaction is set to have the same timestamp as the first of the compressed interactions. If a path has two compressible sequences of the same channel, they are compressed independently to leave two interactions occurring at the appropriate places in the paths.

This is best explained through an example. Imagine you have a user that comes to your website four times: Paid Social > Paid Social > Display > Paid Social. Path compression would remove the duplicates to create a path with three interactions: Paid Social > Display > Paid Social. 

By compressing paths, you allow the attribution model to focus on the interaction between channels. This gives you a much better understanding of how your marketing channels are working together to create conversions. Compression also works to reduce the effects of bot traffic to your site - which usually appears as long sequences of identical interactions occurring in a very short period of time. 

ChannelMix allows you to view your attribution models with path compression turned off as well. In this case, the model is able to learn about channels that users continually engage with along their path to conversion. This provides a more holistic view of all customer paths, but does put you at risk of influence from bots and the rogue user that just loves clicking on the same ad repeatedly. 

Direct Filter

The direct filter adjusts the way customer paths are reconstructed to ensure that direct is never the last interaction in a path. Instead, the last interaction prior to direct is used as the final interaction in the path and we ignore the subsequent direct interactions. This is the same methodology that is used in Google Analytics' Last Non-Direct Click attribution model, but in ChannelMix it can be applied to all attribution models.

As an example, you may have a sequence of interactions like: Display > Direct > Paid Social > Direct > Direct > Conversion. The direct filter would reconstruct these interactions as the path: Display > Direct > Paid Social > Conversion. The direct interactions are removed from the end of the path, so now Paid Social leads to the conversion. Additionally, you see that we retain direct interactions throughout the rest of the path - only removing those that occur at the very end.

The direct filter is used to shift credit away from direct interactions and towards your marketing interventions. In reality, the interaction that caused a customer to come directly to your website and make a purchase is of much more interest than the direct interaction itself. Even if there are numerous direct interactions between the last non-direct interaction and the conversion, you want to give credit to the channel that started the habit of this customer continually returning to your website.

Was this article helpful?
0 out of 0 found this helpful
Have more questions? Submit a request

Comments

0 comments

Please sign in to leave a comment.