the new challenges to Media Mix Modeling

Among many themes discussed in the 2009 Digital Outlook report by Razorfish, there is a strand linked to media and content fragmentation, the complex and non-linear consumer experience, interaction among multiple media and multiple campaigns – all of these lead to one of the biggest analytics challenge: the failure of traditional Media Mix Modeling (MMM) in searching of a better Attribution Analytics.

The very first article of the research and measurement section is on MMM. It has some of the clearest discussion of why MMM failed to handle today’s marketing challenge, despite of its decades of success.  But I believe it can be made clearer. One reason is its failure to handle media and campaign interaction, which I think it is not the modeling failure but rather a failure for the purpose of attribution ( I have discussed this extensively in my post: Attribution, what you want may not be what you need).  The interaction between traditional media and digital media however, is of a different nature and it has to do with mixing of both push and pull media.  Push media influence pull media in a way that render many of the modeling assumptions problematic.  

Here’s its summary paragraph:

” Marketing mix models have served us well for the last several decades. However, the media landscape has changed. The models will have to change and adapt. Until this happens, models that incorporate digital media will need an extra layer of scrutiny. But simultaneously, the advertisers and media companies need to push forward and help bring the time-honored practice of media mix modeling into the digital era.”

The report limit its discussion to MMM, the macro attribution problem.  It did not give a fair discussion of the general attribution problem – no discussion of the recent developments in attribution analytics ( called by many names such as Engagement Mapping, Conversion Attribution, Multicampaign Attribution etc.).  

For those who interested in the attribution analytics challenges, my prior post on the three generations of attribution analytics provide an indepth overview of the field. 

Other related posts: micro and macro attribution and the relationship between attribution and  optimization.