Research and analytics: are they more like peanut butter and chocolate, or more like oil and water? On this episode, we dig into the surprisingly common (and surprisingly unfortunate) divide between these two disciplines with Stefanie Zammit, Global Director of Analytics and Insights at Bang & Olufsen. Stefanie has spent her career bridging the qual and quant worlds, and she makes a compelling case that the best insights come from putting both methodologies to work on the same business problems. From the "never ask a survey question you already have the answer to" rule to why personas are usually terrible (spoiler: it's not the clustering, it's the storytelling), we explore how organizations can break down the silos between research and analytics teams. Turns out, the fear of the unknown and a bunch of fancy terminology might be keeping us from some pretty powerful insights. Also, apparently 100% soundproof rooms are absolutely terrifying.

For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

AI is moving fast. But so is life. AI is widely recognized as a must-adopt technology, but how and where are data workers expected to find the time for that?! Organizations are struggling to find effective ways to productively drive healthy adoption of AI: What is it they expect their workers to do with AI? Is it purely an efficiency driver, or should they expect other avenues of value creation to be pursued? What guardrails need to be in place? What incentive structures are (and are not) effective when it comes encouraging team members to take the AI plunge? One tactic that is definitely effective is to have leaders who are excited, engaged, and transparent as they get their hands dirty. And, boy, did the algorithm deliver one of those to us in the form of John Lovett, VP of Analytics at SEER Interactive, for this discussion!

For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

The one rule about the Analytics Power Hour is that we don't talk about specific tools. But that doesn't mean we won't talk about tool SELECTION! Jason Packer recently released the second edition of Google Analytics Alternatives, (also available on Amazon) and his approach in the book is very much not an RFP-like "check which features your tool offers" system. And his rationale for that seems just as applicable (to us, at least!) for any data platform selection, be it a digital/product analytics platform, a BI tool, database or storage infrastructure, or, well, you name it! Ultimately, the challenge is how to go about getting a reasonably strong understanding of the philosophy and historical roots of each platform being considered and then marrying that up with the foundational priorities and needs of the organization. Is that a lot harder than a feature checklist? Yes. But them's the breaks.

For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.