Temporary attribution is a time-sensitive model used to give UA managers flexibility with how their data is presented. It can also be useful for implementing tests and campaign management.
To understand how this differs from regular attribution models, let’s take a look at an example:
You have a gaming app and want to run a campaign with a limited time offer. You also want to see how a new network, Network B, can drive in-app events within one week post-reattribution. But when the week is over, you also want to stop crediting Network B with future in-app events.
If you use a temporary attribution model, any attribution to Network B would move back to the previous source of attribution once that week is over. The network would still be paid for those reattributions, but the reattributed users’ ensuing session and event data would be reflected under the previous source, whether it be organic or another network source.
For this reason, temporary attribution can be useful for measuring the success of engagement and retargeting campaigns.