In this episode, Alan and Oded discuss “Decisions Over Decimals,” Oded’s latest co-authored book with Christopher Frank, Vice President of the Global Advertising and Brand Management team at American Express, and Paul Magnone, Head of Global Strategic Alliances at Google, who are also professors at Columbia. Having worked on the front lines and taught future executives, they identified two data myths that served as the inspiration for this book. Oded presents these myths and explores the three core pillars of quantitative intuition covered in the book, highlighting how marketers can improve decision-making by understanding these concepts.
Oded advises against the inclination to rush to find a solution and instead encourages spending more time understanding the problem. According to Oded, a well-thought-out problem is already half-solved. This interview and the book emphasize the significance of asking insightful questions and properly defining the problem. This approach is evident in the emergence of Prompt Engineers for tools like ChatGPT, where precise questioning leverages quantitative intuition to achieve desired outcomes.
The conversation also touches upon unstructured data and its implications for marketers in terms of analysis, decision-making, customer listening, and demonstrating that marketing is not just a cost but can also drive revenue.
In this episode, you’ll learn:
- “Decisions Over Decimals”: Why this book and why now?
- What we should be thinking about in terms of good data-based decision-making
- How quantitative intuition is relevant to Prompt Engineers using tools like ChatGPT
Mentioned Faculty

Oded Netzer
- Arthur J. Samberg Professor of Business
- Marketing Division
- Vice Dean for Research
- Dean's Office

Oded Netzer
- Arthur J. Samberg Professor of Business
- Marketing Division
- Vice Dean for Research
- Dean's Office
Professor Netzer's expertise centers on one of the major business challenges of the data-rich environment: developing quantitative methods that leverage data to gain a deeper understanding of customer behavior and guide firms' decisions. He focuses primarily on building statistical and econometric models to measure consumer preferences and understand how customer choices change over time, and across contexts. Most notably, he has developed a framework for managing firms' customer bases through dynamic segmentation.