Season 7, Episode 26: Demystifying open source MMM (with Michael Kaminsky)

On this week's episode of the podcast, I am joined by Michael Kaminsky, co-founder and co-CEO of Recast. We explore the rise of open-source Marketing Mix Modeling (MMM) tools and the challenges of measuring modern ad spend. Among other things, we discuss:Whether open-source MMM libraries like Robyn and Meridian are truly unbiased tools or subtle instruments for big tech self-gradingHow marketers can effectively evaluate the accuracy of MMM outputs through techniques like parameter recovery and predictive forecastingWhy smaller, performance-driven brands might actually find more value in last-touch attribution than in complex econometric modelingIf the inherent uncertainty in MMM estimates makes them fundamentally incompatible with the fast-paced feedback loops of digital advertisingWhat role generative AI and large language models play in democratizing access to sophisticated marketing data science analysisWhen a brand should transition from simple attribution methods to a multi-layered approach involving incrementality and econometric modelingHow the shift toward CTV and non-trackable channels is forcing a resurgence in probabilistic measurement frameworks like MMMThanks to the sponsors of this week’s episode of the Mobile Dev Memo podcast:⁠⁠INCRMNTAL⁠⁠⁠. True attribution measures incrementality, always on.Xsolla⁠. With the Xsolla Web Shop, you can create a direct storefront, cut fees down to as low as 5%, and keep players engaged with bundles, rewards, and analytics.⁠Branch⁠. Branch is an AI-powered MMP, connecting every paid, owned, and organic touchpoint so growth teams can see exactly where to put their dollars to bring users in the door and keep them coming backInterested in sponsoring the Mobile Dev Memo podcast? Contact Mobile Dev Memo advertising.The Mobile Dev Memo podcast is available on:SpotifyYouTubeApple Podcasts