Blog Post

Disrupting MTA

nancy smith
nancy smith 11.21.2019

“May you live in interesting times” is often quoted as an ancient Chinese curse. And though the source of the quote is disputed, the sentiment is appropriate. The truth is, we are all in interesting times right now. There is disruption across all industries from multiple directions, and change is happening more quickly than ever. This is the new normal, and businesses need to learn to be adaptive to survive.


We at Analytic Partners feel strongly about the importance of being adaptive – our tagline “Adapt. Evolve. Thrive.” fits these interesting times perfectly. And in helping our clients adapt, we also adapted our approach to measurement.


In the past, we approached Unified Measurement with the idea that you can bring Marketing Mix Modeling (MMM) and Multi-Touch Attribution (MTA) together with customer data and fulfill the promise of a single version of the truth.


However, this suggests an equal billing for MMM and MTA, when our research shows that when looking through the MMM/MTA lens, on average 80% of the impact in Unified Measurement comes from MMM and only 20% from MTA.


Value of MMM vs MTA

% of Margin Opportunities Identified

Value of MMM vs MTA


This smaller impact contribution also comes in the face of MTA being problematic, given walled gardens, blind spots and data limitations – all of which have reached a breaking point in recent days. That is not to say MTA is dead – it is just facing disruption. And for this reason, Analytic Partners’ approach to attribution is more appropriately called “Touchpoint Analytics”, which was developed specifically to address these challenges. We can still go into deep, user-level analyses within touchpoints through a proprietary profiling algorithm that filters out noise with probabilistic discrete choice models.


And yes, MMM is overall more valuable, but we have been concerned with what we have seen when bridging new clients from their existing models: There is a wide variation in speed, quality, and granularity across insights produced under the umbrella of MMM. When we look at the quality of some of the analyses, it is clear why MMM is incorrectly known to some as a slow method yielding results that are too high-level to be actionable. At Analytic Partners we go to a deeper, more granular level and produce actionable insights faster through MMM.


We then take it a step further – which brings me to our adaptation: Commercial Mix Modeling. It’s faster, more granular and can not only tell you what happened but also lend insights into what you need to do next.


Commercial Mix is:

  • More granular - by Geography, Store, Channel, and Persona
  • More holistic – goes beyond media and marketing for a full business view
  • More flexible – enables multiple views of data and insight to address a spectrum of strategic & tactical questions
  • More adaptive – allows seamless integration with other solutions


CMM: Foundation for Unified

By addressing the whole business at a deeper, more granular level, Commercial Mix Modeling acts as a foundation for our Unified approach. With Commercial Mix lens at the center, we can gain a holistic picture of the business by customizing each model to address specific market, brand, and business challenges.

Commercial Mix Modeling

This foundational analysis allows to add on other analyses that build on your full business view such as branding, operational, customer and channel analytics. The result is robust granular insights to support strategic and tactical decisions – which results in a strong impact on your business. Depending on the type of company, this new Unified approach delivers a 30% increase in value.


With this Unified approach, our clients are better prepared to face this disruption by having a framework to address the full business (not just marketing) and be ready to adapt through data-driven decision making. And when you can adapt, especially in interesting times, you can build competitive advantage, evolve and thrive. Thus, a curse can become a blessing.


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