The Analytics Power Hour

Stephen Follows has spent 15 years turning film-industry curiosity into a career — asking questions like how much movies really earn, why poster colors have shifted over decades, and whether old studio domains are still up for grabs. In this episode, he joined us to talk about building that unusual path, the cautionary tale of TheNumbers.com, and his theory about Sandra Bullock. Go start your passion project. This episode is brought to you, in part, by our sponsors, Prism from Ask-Y and Stape. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Twenty years of digital marketing created something of a monster: companies poured enormous investment into analytics teams, MarTech stacks, media capabilities, and data infrastructure—and then watched all those functions march off into their respective silos to work really, really hard at producing activity rather than impact. Rusty Rahmer, founder of Starize AI and author of Working As Designed, joined Michael, Julie, and Val to dig into why that happened, why it's still happening, and what it actually takes to flip the shovel over and use the right end. Along the way, Rusty—who Val correctly identified early as a spontaneous analogy machine—explained why customer journey maps on walls are basically the statistical average American life that literally nobody lives, why waffle fries are structurally superior to ridged chips (and what that has to do with cross-functional team design), and why the most important question a marketing leader can ask a room full of executives is also the one most likely to be met with complete silence. This episode is brought to you, in part, by our sponsors, Stape and Prism from Ask-Y. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Before you listen to this episode, can you quantify how useful you expect it to be? That's a prior! And "priors" is a word that gets used a lot in this discussion with Michael Kaminsky as we try to demystify the world of Bayesian statistics. Luckily, you can just listen to the episode once and then update your expectation—no need to simulate listening to the show a few thousand times or crunch any numbers whatsoever. The most important takeaway is that you'll know you've achieved Bayesian clarity when you come to realize that human beings are naturally Bayesian, and the underlying principles behind Bayesian statistics are inherently intuitive. This episode's Measurement Bite from show sponsor Recast is a brief explanation of statistical significance (and why shorthanding it is problematic…and why confidence intervals are generally more practically useful in business than p-values) from Michael Kaminsky! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Does size matter? When it comes to datasets, the conventional wisdom seems to be a resounding, "Yes!" But what about small datasets? Small- and mid-sized businesses and nonprofits, especially, often have limited web traffic, small email lists, CRM systems that can comfortably operate under the free tier, and lead and order counts that don't lend themselves to "big data" descriptors. Even large enterprises have scenarios where some datasets easily fit into Google Sheets with limited scrolling required. Should this data be dismissed out of hand, or should it be treated as what it is: potentially useful? Joe Domaleski from Country Fried Creative works with a lot of businesses that are operating in the small data world, and he was so intrigued by the potential of putting data to use on behalf of his clients that he's mid-way through getting a Master's degree in Analytics from Georgia Tech! He wrote a really useful article about the ins and outs of small data, so we brought him on for a discussion on the topic! This episode's Measurement Bite from show sponsor Recast is an explanation of synthetic controls and how they can be used as counterfactuals from Michael Kaminsky! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

From spreadsheets to strategy: what does data look like from the CEO's chair? For this episode, we sat down with Anna Lee, CEO of Flybuys and former CFO/COO of THE ICONIC, to get her view on data-led leadership and what great looks like in data and analytics. Discover how Anna's journey from finance to the corner office has shaped her approach to leveraging evidence for strategic decision-making. From productive curiosity, to informed pragmatism, and how data teams can build trust with leadership, this is a candid conversation about analytics from the top down. Whether you're embedded in a squad or building the next big data platform, this one's for anyone who's ever wondered what it takes to truly influence the C-suite! This episode's Measurement Bite from show sponsor Recast is an overview of the fundamental problem of causal inference from Michael Kaminsky! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.