Hi, I’m Agata and I’d like to demystify MMM. Start with BASICS, then you can take a look at TECHNICAL DETAILS, at the end check the section WHAT’S WRONG WITH MMM?!


What is MMM?
  • Marketing Mix Modelling
  • statistical analysis to estimate the impact of various marketing activities on KPIs
  • used for marketing mix optimization:
    • calculation of ROI for each channel/campaign
    • forecast/plan future activities

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Why to do MMM?
  • no cookies data required
  • do not require unique user data
  • not based on a declarative survey
  • based on actual numbers and statistical models

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What questions does MMM answer?
  • what is the ROI of my marketing activities?
  • how to optimize the marketing budget?
  • which ads perform better?

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What KPI can we model?

KPIs that we want to increase/manage thanks to MMM?

  • sales volume/value
  • awareness
  • traffic

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What data do we need?

for MMM, we need historical data over time:

  • 2-year weekly data – gives the best result
  • 3-year monthly data

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How does the statistical model work and what is it the benefit?

Model for weekly based on historical data: 

  • KPI
    • sales
  • influencing factors:
    • online ads spend
    • newsletter

It can be applied to the media plan.

check the example


MMM vs. linear model

MMM is not just a linear model; we must make a few adjustments

  • adstock
  • saturation
  • possible lag

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Adstock functions in MMM

Two main groups of adstock functions:

  • geometric: adstocki = adsi + 𝞭 * adstocki-1
  • convolution: adstock = 𝜮conv ⨂ ads

check the example

Why do we need historical data?
Why do we need historical data?
  • one point if not enough
  • function having only two dimensions
  • to find a function that defines relation between media spend and sales we need enough points, one point is not enough



What’s wrong?


we have to manage our expectations;

unrealistic expectation is the main issue of MMM failure:

  • we want to know too many details rather than a general overview
  • data are not available, so we cannot estimate the effectiveness
  • external factors we are not aware of also may have an impact
Issues with MMM
  • time-consuming
  • does not invent anything, only optimizing existing spending for media channels
  • result may vary based on assumptions
  • may give unrealistic recommendations
Recommendation traps
  • by optimizing, you will never introduce anything new; what limits your potential growth
  • introducing more and more promotions may be harmful to your brand
Competitors influence
  • competitors may influence us both positively and negatively, depending on a category and message
  • we are not sure what will be the competitors’ actions in the future
What came first, the chicken or the egg?
  • MMM tends to add too much weight to media activity
  • however, during a heavy promotion period, there may be other activities that impact KPI (e.g., increased distribution, visibility)
  • other activity during promotion period may be price discounts or promo bundles
Data quality and availability

without data, you cannot do MMM, but there are so many issues; most common are:

  • data are not available
  • data are not structured in any way
  • data are confidential
Real reasons to do MMM
  • proof that you use sophisticated tools while spending money on marketing activities
  • proof that we spent money wisely
  • show off at a board meeting