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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

96: Using Predictive Analytics in Product Prioritization Decisions