Attribution isn’t the only way to analyze media, and in some cases, it isn’t the most appropriate tool. Consider media mix modeling when you want to measure offline and branding initiatives more than the direct response to media:
Attribution, whether rules based or data-driven, captures credit towards a conversion or purchase.
So what doesn’t get credit? Attribution models cannot measure things like brand awareness, recognition, and loyalty. Even if all advertising was turned off, some customers would still purchase with a brand because of this. These feelings can’t necessarily be measured in a hard and fast way using attribution pathing. Further, branding initiatives on offline channels such as billboards or TV ads may not get credit since attribution pathing can rarely connect a user in the offline world to the online world and all these pieces must come together.
This is where media mix modeling can complement your attribution. In media mix modeling, weekly data rather than user level data is analyzed to find out what weekly volumes were contributing the most to weekly sales. And one of the benefits of looking at this more aggregated data is that we can measure the impact of the base (what volume of revenue was not due to media effects). Further, seasonality, weather, offline spend, and other exogenous factors can be put into the model to get credit towards sales, provided the data exists.
Read my post on the Cardinal Path blog here.