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96: Using Predictive Analytics in Product Prioritization Decisions
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Manage episode 431390650 series 2930898
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
131 episodes
96: Using Predictive Analytics in Product Prioritization Decisions
How To Succeed In Product Management | Jeffrey Shulman, Red Russak & Soumeya Benghanem
Archived series ("Inactive feed" status)
When? This feed was archived on July 12, 2024 21:56 (). Last successful fetch was on July 30, 2024 04:40 ()
Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.
What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.
Manage episode 431390650 series 2930898
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
131 episodes
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