Every marketing team  wants attribution. But weirdly, it's often not that satisfying when they actually get it. I led many multi-touch attribution projects as a consultant, and we got really good at implementing tools, creating taxonomies, and making sure that data was clean. But I found that when you actually showed these reports to a C-level executive, it was usually kind of underwhelming. The data didn't always pass the common sense test. Today's guest thinks there's a better way — Marketing Mix Modelling. It's basically the application of mathematical techniques to model relationships between different variables. However, technology now enables it to happen faster and more cost-effectively than ever before. Thanks to Our SponsorMany thanks to the sponsor of this episode - Knak. If you don't know them (you should), Knak is an amazing email and landing page builder that integrates directly with your marketing automation platform. You set the brand guidelines and then give your users a building experience that’s slick, modern and beautiful. When they’re done, everything goes to your MAP at the push of a button. What's more, it supports global teams, approval workflows, and it’s got your integrations. Click the link below to get a special offer just for my listeners. Try Knak 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. https://www.linkedin.com/in/markstouse/ 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 Resource LinksProof Analytics - Official SiteEconometrics // Lecture 1: Introduction Learn MoreVisit the RevOps FM Substack for our weekly newsletter: Newsletter