From Marketing Mix Modelling to Econometrics: Top 10 FAQs answered

Or, everything you wanted to know about MMM and econometrics, but didn’t dare to ask. 

MMM and econometrics are powerful strategic tools, but many of the old views of MMM persist. It's just for sales modelling. It's only for media. But those views mean MMM is often misunderstood, misused and under-valued. 

In this episode, we put the top 10 most searched for questions about MMM to our UK GM & Partner, Matt Andrew, to help bring to life the breadth of MMM’s capabilities and bust a few myths. 

SPOLIER ALERT: it’s not just for media… Or sales.

Find out: 

1. How does Marketing Mix Modelling work? 
2. What are the benefits of Marketing Mix Modelling? 
3. What data is needed for Marketing Mix Modelling? 
4. How do you implement Marketing Mix Modelling? 
5. What are the limitations of Marketing Mix Modelling? 
6. How do you interpret the results of Marketing Mix Modelling? What are some of the most useful outputs of Marketing Mix Modelling? 
7. How does Marketing Mix Modelling differ from other marketing analytics? 
8. Can Marketing Mix Modelling predict future sales? Or other KPIs? 
9. Should all brands invest in MMM? How do you know if it’s right for you? 
10. If you’re starting out with MMM for the first time, what advice would you give? 

Whether you're just starting out or a complex, global, multi-category business, you can expect to hear straightforward answers to these questions with further discussion on how to use MMM as a strategic value driver.

The conversation ranges across a broad set of applications, from forecasting and scenario planning to pricing and driving your sustainability agenda. And an equally broad set of integrations. From how to use MMM in conjunction with other techniques, such as multi-touch attribution to experiments to develop a unified marketing measurement capability to how to nest real-time data using Bayesian Priors. Plus we consider how to embed customer lifetime value and capture creative effectiveness. And much more...

The Bayesian modelling explainer referenced in the podcast can be found on our website. 

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