MMM Model Update Presentation – The most tense period for everyone 😅 I have been part of 100’s of MMM model presentation. However every model update presentations still makes me a little bit anxious. And funnily the client side too feels the same anxiety. Every MMM model update carries with it a lot of suspense […]
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Many had written off MMM (Marketing Mix Models) not so long ago. But like a phoenix, MMM keeps rising from the ashes.🔥 Thanks to: GDPR, Apple 14 privacy, Google’s cookie deprecation and ever growing pressure on marketing departments to justify their budget allocation, MMM is back to life again. 🚀 But how can we prevent
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How to get the maximum out of open source MMM libraries. (Hint: talk to MMM experts) Of late we are getting lot of calls from prospective clients for MMM adoption. Most of them have tried or are trying open-source MMM libraries. But here are some of the pestering questions clients have: · How do we
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In late 2018, We explored the option of VC funding. Some of the VCs asked us why we focused on Marketing Mix Modeling solutions. We told them at that time that MMM will be a sought after solution not only in FMCG/CPG space but in other domains as well. Call it a hunch or educated
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Mathematically Optimal Solution ≠ Optimal Marketing Solution One of the important use cases of Marketing Mix Modeling (MMM) is the Marketing Budget Optimization. The results of MMM are directly leveraged to provide various ‘What-if’ budget allocation scenarios. Such as: ▪️ Under the same budget, how could we have allocated the spends across media differently to
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As MMM is gaining acceptance in newer domains, most prospective clients ask the following questions. ▪ Why should we update MMM models? ▪ How often should we update them? 📌 Why should you update MMM model? To explain this, I normally use the analogy of movie making. A movie is a series of snapshots put
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MMM is not new. CPG/FMCG domain has been adopting MMM for nearly 30 years. The statistical methodology behind it, is proven and time tested. Why then should one innovate ? Through this post, I would like explain why. 🎯 Reason 1: MMM is being adopted by new domains. There has been increasing adoption of MMM
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Decomp RSSD – The business fit calibration During the Meta panel discussion (link in Resources section), I had mentioned about Robyn’s Decomp RSSD metric. In our earlier posts too, both my co-founder Venkat and I extensively covered the topic of calibration and validation extensively. Calibration of MMM model can be achieved through goodness of fit.
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MMM is for enterprises of all sizes Of late I came across a lot of posts proclaiming that MMM is not ideal for SMBs. I want to dispel some myths on this. 📌Small Marketing Spends Small marketing spends is not a show stopper. Not statistically and not marketing wise either. There are various statistical techniques
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How to use AIC to select the best Marketing Mix Model (MMM). Firstly, let’s look at what is AIC and the most common misunderstanding associated with it. The Akaike information criterion (AIC) is given by: AIC = 2k -2ln(L) where k is the number of parameters L is the likelihood The underlying principle behind usage
How to use AIC to select the best Marketing Mix Model (MMM). Read More »
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