What is Marketing Mix Modeling?
According to the paper “Challenges and Opportunities in Media Mix Modeling” by Chan, D., & Perry, M. (2017), Marketing Mix Modeling (MMM) are the statistical model used by advertisers to measure the effectiveness of their advertising spending and exists in various forms since the 1960s. MMMs, as we will call them from now on, use aggregated historical time-series data to model sales performance as a function of advertising variables, other marketing variables and control variables such as weather, seasonality and market competition.
Metrics such as return on advertising investment (ROAS) and optimised advertising budget allocations are derived from these models because they provide valid causal results.
In other words, MMMs attempt to answer causal questions for the advertiser. For example:
- What was my ROAS on TV last year?
- What would my sales be if more or less money were spent next year?
- How should my media budgets be allocated to maximise sales?
What does Marketing Mix Modeling bring to our business?
With MMM, we will achieve two different things:
- Attribution: we will analyse all the variables that influence the client’s business results and know which are the most relevant to enhance them. The advantage compared to user-level models is that this model does not only talk about digital data, but by using aggregated data, we will be able to incorporate offline investment data, types of offers, and seasonality, among others.
- Predictions: we will discover which variables have been the most relevant in the period analysed; an MMM will indicate how to boost each variable and predict how the results will change in each scenario presented to it.
We will only be able to make high-value activations, but only as decision making and for this, we will need an analyst to interpret the data. However, you do not have localised users by using aggregated data, so you cannot use an MMM to activate audiences or optimise campaign algorithms.
Choosing the best model for your business
In an MMM project, we will work and create different types of models, and the initial objective will be to choose the one that best suits our business:
In the following graph, we can see the actual sales history of the customer (pink line) and how this model predicted that time period (blue line).
Ultimately, we will choose the model that best fits the trend and the customer’s sales peaks.
What insights can we extract from our MMM model?
- Prediction of potential sales increase: this graph shows all campaigns or actions included in the model. The dots are the actual investment and sales of that campaign, and thanks to the trend lines, we can see the sales potential of each campaign as we increase the investment.
- ROI of the campaigns and variables: in the graph, we can see in dark blue the weight in the percentage of total sales that the campaign or action has had (calculated by the model). In light blue, we can see this action’s significance on the total investment (these are data that we give to the model). And finally, the orange dots show us the ROI of each action, identifying which are the most profitable for our business.
Do you want to know more about what Marketing Mix Modeling can bring to your business? Don’t hesitate to contact our team of experts. We are waiting for you! 🚀
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