The Analytics Power Hour
Michael Helbling, Moe Kiss, Tim Wilson, Val Kroll, and Julie Hoyer
Attend any conference for any topic and you will hear people saying after that the best and most informative discussions happened in the bar after the show. Read any business magazine and you will find an article saying something along the lines of "Business Analytics is the hottest job category out there, and there is a significant lack of people, process and best practice." In this case the conference was eMetrics, the bar was….multiple, and the attendees were Michael Helbling, Tim Wilson and Jim Cain (Co-Host Emeritus). After a few pints and a few hours of discussion about the cutting edge of digital analytics, they realized they might have something to contribute back to the community. This podcast is one of those contributions. Each episode is a closed topic and an open forum - the goal is for listeners to enjoy listening to Michael, Tim, and Moe share their thoughts and experiences and hopefully take away something to try at work the next day. We hope you enjoy listening to the Digital Analytics Power Hour.
Episodes
Mentioned books
20 snips
Mar 17, 2026 • 1h 6min
#293: Tool Selection and the Unhelpfulness of Feature Comparisons
Jason Packer, founder of Quantible Analytics and author of Google Analytics Alternatives, brings concise analytics tool evaluation expertise. He describes testing tools with real data and avoiding vendor demos. Conversation covers proof of concept strategies, hidden costs of DIY and open source, the influence of product philosophy and vendor roots, and how price and total cost of ownership should guide choices.
13 snips
Mar 3, 2026 • 1h 4min
#292: AI Without Adult Supervision with Aubrey Blanche
Aubrey Blanche, a senior leader researching AI ethics, equity, and human impact, joins to challenge AI hype. She reframes efficiency, warns about phantom value, and urges values-based governance. Short practical guidance covers who should decide AI risk, measuring harms early, and keeping human agency in AI-powered work.
24 snips
Feb 17, 2026 • 1h 3min
#291: The Data Work that Lives in the Shadows
They unpack the unseen "shadow work" analysts do to make data usable, from admin and project follow-up to rebuilding warehouses. They talk alignment challenges like standardizing metrics, explaining data realities, and teaching non-analysts. They cover risks of tribal knowledge, monitoring expectations, and how to make this hidden work visible and hire to fill gaps.
27 snips
Feb 3, 2026 • 1h 6min
#290: Always Be Learning
Mårten Schultzberg, product manager and staff data scientist at Spotify known for experimentation and co-author of Spotify's EWL framework, explores how organizations learn from experiments. He discusses valuing learning beyond wins, defining wins/regressions/neutrals, powering and monitoring tests, preventing metric fishing, and when neutral results still justify shipping. Practical lessons on scaling experimentation culture and tooling are highlighted.
37 snips
Jan 20, 2026 • 1h 10min
#289: The Imperative of Developing Business Acumen
The discussion dives deep into the importance of business acumen for analytics professionals. It outlines two types of acumen: general concepts and company-specific knowledge. The hosts emphasize the need to understand decision-making processes and highlight common pitfalls, like biases stemming from over-familiarity with a business. They also share practical strategies for developing acumen, including stakeholder interactions, public filings, and cross-training. Ultimately, the episode stresses that everyone on data teams should grasp business fundamentals to drive impactful results.
30 snips
Jan 6, 2026 • 1h 1min
#288: Our LLM Suggested We Chat about MCP. Kinda' Meta, No?
Sam Redfern, a Staff Data Scientist at Canva with experience at Meta, dives into the intricacies of Model Context Protocol (MCP). He explains how MCP works like ‘fingers’ for AI models, aiding their access to tools. The conversation highlights the differences between MCP and APIs, the importance of standardization, and the potential for custom implementations tailored to organizations. Sam discusses practical applications at Canva and emphasizes the need to avoid context pollution while navigating the governance risks associated with powerful AI tools.
14 snips
Dec 23, 2025 • 1h 1min
#287: 2025 Year in Review
Joining the conversation is Josh Crowhurst, Growth Marketing Director at Manulife, known for his insights and musical contributions. The hosts reflect on standout moments from 2025, including memorable episodes, the rise of AI analytics, and the balance between hype and practical application. Josh emphasizes the importance of critical thinking in the age of AI and highlights leadership insights from Anna Lee that shape data culture. They also indulge in nostalgic favorites and discuss trends for 2026, underscoring the need for consistent metrics and thoughtful decision-making.
35 snips
Dec 9, 2025 • 56min
#286: Metrics Layers. Data Dictionaries. Maybe It's All Semantic (Layers)? With Cindi Howson
Cindi Howson, Chief Data & AI Strategy Officer at ThoughtSpot and a seasoned expert in business intelligence, discusses the resurgence of semantic layers in data strategy. She explains how these layers provide essential business context to raw data, reducing misunderstandings across departments. Cindi debates the need for multiple, context-driven semantic implementations rather than a single monolithic layer. She also highlights the importance of data modeling skills for analysts and offers practical tips for creating effective semantic layers.
40 snips
Nov 25, 2025 • 1h 7min
#285: Our Prior Is That Many Analysts Are Confounded by Bayesian Statistics
In this discussion, Michael Kaminsky, Co-CEO of Recast and a specialist in Bayesian statistics, offers intriguing insights into the complexities of Bayesian analysis. He emphasizes how human beings naturally think in Bayesian terms, often updating beliefs with new evidence. Kaminsky contrasts Bayesian and frequentist statistics, pointing out the limits of traditional methods. He advocates for involving domain experts to set realistic priors and explores the application of Bayesian modeling in real-world scenarios, including pandemic and decision-making contexts.
7 snips
Nov 11, 2025 • 1h 8min
#284: I Used to Think...But Not Any More
The hosts dive into how personal beliefs in analytics have evolved over time. They question the efficacy of analytics intake forms and the myth of campaign parameter purity. There's a lively debate about the relevance of privacy today compared to earlier views. The discussion shifts to the limits of linear maturity models and the importance of collaboration over rigid structures. Humor interspersed with serious thoughts emphasizes that data is just one piece of the decision-making puzzle, not the whole meal.
