96: Using Predictive Analytics in Product Prioritization Decisions

Get involved with The Product Management Center. Learn more at https://ipma.info.foster.uw.edu/

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