96: Using Predictive Analytics in Product Prioritization Decisions

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In this episode of the How to Succeed in Product Management Podcast, marketing professor Jeff Shulman and The Product Management Center advisory board members Red Russak welcome Varun Kulkarni (CISCO) and  Ash Naik (AAIS) as they discuss the use of predictive analytics in product prioritization decisions. Using predictive analytics in product prioritization decisions is beneficial for product managers because it enables data-driven decision-making. By analyzing historical data and patterns, predictive analytics can forecast the potential success and impact of different product features or enhancements. This empowers product managers to allocate resources effectively, focus on high-impact initiatives, and align their strategies with customer needs and market trends. Ultimately, this approach increases the likelihood of delivering products that resonate with customers, optimizing resource allocation, and driving overall business success.

Disclaimer: All opinions of the speakers are their own.

What to Listen For:

00:00 Intro

08:09 Right data collection and cluster analysis

10:29 Having a direct data or proxy

12:27 Setting up a validation process

13:55 Softwares for analyzing and visualizing data 

18:44 Conjoint analysis and canal model

23:58 Data that goes into a cluster analysis

28:07 Avoid using vanity metrics

30:21 Using predictive analysis on personalized experience

34:38 Scenario modeling

39:34 Risk in utilizing predictive analysis

44:06 Advice for aspiring PMs

48:54 How often does the marketplace change?

51:39 Final Thoughts