The Analytics Power Hour

Winston Li, founder of Arima and a former data science leader at PWC Canada, dives deep into the fascinating realm of synthetic data. He discusses how synthetic data can revolutionize analytics by safeguarding privacy while providing robust alternatives to traditional datasets. The conversation covers its generation, applications in marketing mix modeling, and the balance between statistical integrity and privacy concerns. Li also shares insights on its utility in consumer research and the modern implications of AI in education and career choices.

Is it just us, or are data products becoming all the rage? Is Google Trends a data product that could help us answer that question? What actually IS a data product? And does it even matter that we have a good definition? If any of these questions seem like they have cut and dried answers, then this episode may just convince you that you haven't thought about them hard enough! After all, what is more on-brand for a group of analysts than being thrown a question that seems simple only to dig in to realize that it is more complicated than it appears at first blush? On this episode, Eric Sandosham returned as a guest inspired by a Medium post he wrote a while back so we could all dive into the topic and see what we could figure out! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Dan McCarthy, Associate Professor of Marketing at the University of Maryland, unpacks the intricate world of customer metrics. He highlights the challenges in defining metrics like Customer Acquisition Cost (CAC) and Customer Lifetime Value (CLV). The conversation reveals how multiple interpretations can lead to financial misrepresentations and regulatory hurdles. McCarthy also discusses the importance of clarity in corporate disclosures, the influence of leadership on corporate governance, and how emerging AI perceptions complicate metric calculations. A must-listen for metrics enthusiasts!

Dr. Lindsay Juarez, a behavioral scientist and director at Irrational Labs, shares her expertise on the fascinating world of behavioral science. The discussion dives into the concepts of nudging versus sludge and the importance of understanding the 'why' behind human decisions. Juarez highlights real-world applications of behavioral insights in finance and health. She also humorously breaks down a classic Seinfeld bit, showcasing her fun side. The conversation wraps up with reflections on how to effectively implement behavioral strategies in organizations.

We finally did it: devoted an entire episode to AI. And, of course, by devoting an episode entirely to AI, we mean we just had GPT-4o generate a script for the entire show, and we just each read our parts. It's pretty impressive how the result still sounds so natural and human and spontaneous. It picked up on Tim's tendency to get hot and bothered, on Moe's proclivity for dancing right up to the edge of oversharing specific work scenarios, on Michael's knack for bringing in personality tests, on Val's patience in getting the whole discussion to get back on track, and on Julie being a real (or artificial, as the case may be?) Gem. Even though it includes the word "proclivity," this show overview was entirely generated without the assistance of AI. And yet, it’s got a whopper of a hallucination: the episode wasn’t scripted at all! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Brett Kennedy, a freelance data scientist and author of 'Outlier Detection in Python,' delves into the nuances of outlier detection methods. He compares identifying outliers to obscenity, noting the challenges of definition and detection. The discussion spans techniques such as z-scores and the Median Absolute Deviation, emphasizing the importance of context in data analysis. Kennedy also highlights the human touch needed in distinguishing significant anomalies from normal variations, showcasing the interplay between technology and human insight in deciphering data.

Chris Kocek, CEO of Gallant Branding and author of "Any Insights Yet?", joins to tackle the cringe-worthy concept of 'insights' in data analytics. They discuss the essential differences between plain data and true insights, emphasizing the importance of context and communication. Chris shares how Netflix exemplifies using customer frustrations to spark innovation. The conversation dives into the 'five whys' method, the collaborative nature of insight generation, and the critical role of curiosity in analytics, making it a lively, informative exploration.

Chelsea Parlett-Pelleriti, a statistician and data scientist from Recast, returns to dive deep into the fascinating world of linear regression. She simplifies complex concepts like feature engineering, multicollinearity, and overfitting, making statistics accessible. The discussion explores how statistical models can improve marketing efforts and the distinction between predictive and inferential analysis. They also share lighthearted anecdotes about pet safety and social media experiences, blending humor with insightful analytics.

Kathleen Walch, Director of AI Engagement Learning at the Project Management Institute, shares her expertise on overcoming obstacles in AI projects. She emphasizes the importance of clearly defining problems before implementing solutions. With humorous anecdotes, she highlights common pitfalls, like treating AI as mere software projects, and advocates for a data-centric approach. Kathleen also explores the necessity of realistic ROI expectations and evolving skill sets in project management, providing insightful frameworks to navigate the complex world of AI.

Michael Tiffany, Co-founder and CEO of Fulcra Dynamics, delves into the realm of connected wellness and personal data sovereignty. He discusses the allure of self-tracking through devices like smartwatches and continuous glucose monitors, exploring their impact on health and privacy. The conversation emphasizes the balance between leveraging technology for proactive wellness and safeguarding personal data against misuse. Tiffany also envisions future AI interactions in health management, highlighting ethical considerations of data ownership in an increasingly connected world.