Episode #24: Is Marketing Mix Modelling the future of B2B analytics? - Mark Stouse
A methodology that even your CFO might love
“How do I know whether my marketing is working?”
It’s a question that haunts the dreams of CMOs.
The technology and data to answer that question have never been more abundant or easily accessible.
And yet, paradoxically, the discipline of marketing analytics remains a chaotic Wild West.
There’s still no consensus among marketers on the methodology we should use or whether its even possible to measure the ROI of marketing investments with any kind of precision.
Into this debate steps Marketing Mix Modelling (MMM) — a technique so old it’s become cool again.
It stems from econometrics, a nearly-100-year-old discipline that applies statistical techniques such as linear regression to model the relationship between different variables.
MMM applies those same techniques to marketing activities and outcomes. It’s a common methodology in B2C but historically has required significant investment, making it out of reach for most non-enterprise companies.
However, advances in technology have made this technology accessible and more cost-effective than ever before — even for B2B.
Today’s episode goes deep into MMM with Mark Stouse. He spent decades applying it in practice as an enterprise marketing leader before founding Proof Analytics.
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About Today's Guest
Mark Stouse is CEO of ProofAnalytics.AI. With over 26 years of experience in marketing communications and strategy, he has a passion for transforming GTM performance with data-driven insights and agile decision making. Prior to founding Proof, Mark was CMO at Honeywell Aerospace, CCO at BMC Software, and a marketing leader at Hewlett Packard Enterprise.
Key Topics
[00:00] - Introduction
[01:15] - Clarifying the acronym “MMM”
[02:39] - Mark’s background and how he founded Proof Analytics
[07:57] - Limitations of multi-touch attribution (“MTA”)
[14:16] - How MMM avoids the shortcomings of MTA
[16:42] - The Fischer Price definition of MMM
[19:56] - Demand vs. brand investments and their impact
[24:09] - A/B vs. multivariate regression
[25:21] - MMM is aggregate modelling, no reliance on PII
[27:12] - Simple explanation of multi-variate regression
[30:29] - Incorporating third-party data sources
[31:48] - Historical ROI vs. forecasted ROI
[32:52] - Is MMM just for enterprise?
[34:51] - Marketing as a non-linear multiplier
[38:02] - Getting started with MMM
[41:18] - Updating models to include new data sources
[42:07] - Competition in the marketing analytics space
[44:41] - B2C marketing is more advanced in usage of multi-variate regression