Marketing Mix Modelling has been around for a long time, digital attribution (non last click) has been around for maybe the last 5 years. The challenge is how to come up with a holistic evaluation approach that gives all media the correct credit.

This is tricky because digital data is at user/cookie level whereas traditional media (TM) data is aggregated. However I think they can be combined. The trick is to merge the data at a particular level. For instance if the TM is at region and date/hour, then you can insert a hypothetical, weighted  TM event into the digital data. For example if the GRP for region A at hour 10 is 120 then insert such an event for all users that had a digital event a few hours after 10 in region A. The assumption here is that usually TM precedes a digital event (eg search). Here you can use Adstock or other sequential functions to create a lasting effect. Once you have created such artificial events you can run your model of choice to predict conversion and hence assign credit to channels. Note that the TM->digital assumption introduces some bias in your model.

You could also give a higher weight to Outdoor media for (digital) mobile users as they usually are on the go. If you have demographics in your TM and digital data you can match even better.