Synthetic data: it's a fascinating topic that sounds like science fiction but is rapidly becoming a practical tool in the data landscape. From machine learning applications to safeguarding privacy, synthetic data offers a compelling alternative to real-world datasets that might be incomplete or unwieldy. With the help of Winston Li, founder of Arima, a startup specializing in synthetic data and marketing mix modelling, we explore how this artificial data is generated, where its strengths truly lie, and the potential pitfalls to watch out for! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

udging by the number of inbound pitches we get from PR firms, AI is absolutely going to replace most of the work of the analyst some time in the next few weeks. It's just a matter of time until some startup gets enough market traction to make that happen (business tip: niche podcasts are likely not a productive path to market dominance, no matter what Claude from Marketing says). We're skeptical. But that doesn't mean we don't think there are a lot of useful applications of generative AI for the analyst. We do! As Moe posited in this episode, one useful analogy is that thinking of using generative AI effectively is like getting a marketer effectively using MMM when they've been living in an MTA world (it's more nuanced and complicated). Our guest (NOT from a PR firm solicitation!), Martin Broadhurst, agreed: it's dicey to fully embrace generative AI without some understanding of what it's actually doing. Things got a little spicy, but no humans or AI were harmed in the making of the episode. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

For those who celebrate or acknowledge it, Christmas is now in the rearview mirror. Father Time has a beard that reaches down to his toes, and he's ready to hand over the clock to an absolutely adorable little Baby Time when 2024 rolls in. That means it's time for our annual set of reflections on the analytics and data science industry. Somehow, the authoring of this description of the show was completely unaided by an LLM, although the show did include quite a bit of discussion around generative AI. It also included the announcement of a local LLM based on all of our podcast episodes to date (updated with each new episode going forward!), which you can try out here! The discussion was wide-ranging beyond AI: Google Analytics 4, Marketing Mix Modelling (MMM), the technical/engineering side of analytics versus the softer skills of creative analytical thought and engaging with stakeholders, and more, as well as a look ahead to 2024! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Multi-touch attribution, media mix modeling, matched market testing. Are these the three Ms of marketing measurement (Egad! The alliteration continues!)? Seriously. What's with all the Ms here? Has anyone ever used experimentation to build a diminishing return curve for the impact of a media measurement technique based on how far along in the alphabet the letter of that technique is? Is "M" optimal?! Trust us. You will look back on this description after listening to this episode with John Wallace from LiftLab and find it… at least mildly amusing. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Hey there, mister. That's a mighty nice multi-touch attribution model you're using there. It would be a shame to see it get mixed up with a media model. Or... would it? What happens if you think about media mix models as a tool that can be combined with experimentation to responsibly measure the incrementality of your marketing (while also still finding a crust of bread in the corner for so-called "click attribution")? According to a 2019 paper published by ThirdLove (which happens to have been Michael's last call on our last episode), that's a pretty nice way to go, and we thought it would be fun to see if we could raise Tim's blood pressure by giving him something to vigorously agree with for once. It was. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.