Driving Media Strategy with ‘Consumer Mix’ Modeling


In the past, analyzing consumer packaged goods sales at the total-market, retailer or trade-area level may have been sufficient for topline insights. Today’s data-savvy marketer, however, is increasingly empowered by the rich information and granular measurement of consumer-level purchase behavior. 

Traditional media strategies and mix models were not designed for our increasingly personalized world. If marketing messages can be individualized based on what we know about consumers, our media and measurement strategies should follow suit. 

Data and ad technology solutions now allow marketers to identify the most valuable consumer targets and deliver media to them across multiple channels. Surprisingly, there is still significant complexity when it comes to optimizing personalized media plans. Enter the “Consumer Mix Model.”

Rather than focusing on campaign-level metrics, the Consumer Mix Model (CMM) focuses on the consumer as the core unit of measurement and decision-making. CMM analyzes the impact of marketing messages at the individual consumer level and then models the impact of those messages on sales outcomes. It’s a personalized media mix model. 

Challenges of Traditional MMM
To discuss CMM, a little context on traditional marketing mix models (MMM) helps. Marketing mix has been a fixture of media planning for more than 30 years, and its concepts are intuitive. If marketers can find the right “mix” or balance of various marketing tactics — pricing, placement, advertising and promotion, etc. — they will be well-positioned to drive positive sales outcomes. 

In a nutshell, the MMM attempts to model a brand or product’s sales outcomes by estimating the impact of marketing investments by channel, while controlling for other explanatory measures of incremental sales. These measures could include things like seasonality, holidays and historical sales trends.

Because MMMs rely on coarse measures of brand and product sales performance, they don’t fully leverage the precision and granularity of data available to the modern marketer. When a marketer has access to consumer-level purchase data, these rich insights don’t necessarily fit into a traditional MMM.   

The Power of the CMM
If we can capture each media exposure, CPG activation, and purchase for a consumer, it means we can layer in new levels of precision in measurement. Analyzing purchase data in the context of consumer mix inherently leads to richer insights on: 

  • Loyalty: Consumer-level purchase data lets marketers isolate regular purchase behavior from potentially incremental purchases. 
  • Targeting: Aggregating granular measures of conversion across similar sub-group audiences makes it easier to see if there are specific consumer-level attributes that identify the best creative executions or channels for a campaign. 
  • ROI Precision: In a world where media exposures and in-store activations are one-to-one measures, marketers can precisely align cost per exposure to consumer outcomes.

Integrating these granular measures with consumer-level marketing exposures and activation enables marketers to paint a new picture of media return on investment. As marketers refine campaign objectives, CMMs allow them to focus on the relevance of consumer targets, exposures, and specific activations — not just the relevance of marketing channels we get from a traditional mix model. 

Fortunately, there are many ways for marketers to dial in their media strategy right now to move toward a CMM solution:  

  1. Focus on granular insights. CMM identifies the most valuable consumer targets and impressions in the context of a specific brand campaign. Using this framework with a corresponding omnichannel solution can simplify the process of creating an optimal media exposure plan. 
  2. Insist on closed loop measurement. Executing marketing campaigns with an eye toward holistic measurement should be a priority. For example, coupling media with in-store targeting that includes print activations allows closed-loop measurement and far more precise channel attribution. 
  3. Define consumer target audiences consistently across channels. Improving marketing outcomes means understanding audiences across channels — otherwise, post-campaign measurement can end up fragmented. 

By making the consumer the focus of marketing, media and measurement, the notion of using media to push the right message at the right time takes on a new level of precision. Embracing the consumer-first approach to the marketing mix is a smart next step for marketers. 

About the Author
Wes Chaar, Ph.D., is chief data & analytics officer for Catalina Marketing. He is an established expert and leading thinker in the fields of analytics and data science, machine learning, AI and data fusion.