Joshua Mabry is an experienced professional with a robust foundation in data science and personalization. Starting with a Ph.D. and work in DNA sequencing, he transitioned to consulting roles at Bain & Company, where he became an expert advisor on machine learning and personalization. Now at AlixPartners, he designs AI solutions for different industries also with a focus on personalization strategies. Joshua’s expertise spans experimentation, modeling, optimization, and emerging technologies like MLOps and generative AI.
In our chat, Josh shared tips on when to use personalization and when to avoid it. He explained that companies relying too much on promotions or offering very simple product lines might struggle to make personalization work. Joshua also discussed "incrementality," which measures how much extra value personalization brings, such as encouraging customers to spend more over time.
Joshua presented a simple and practical framework for personalization while noting that keeping these projects running can be challenging because teams change, and priorities may clash.
When it comes to AI, Joshua said it’s not yet a big game-changer for personalization, though it can help with small tasks like checking for mistakes. He recommended starting with easy-to-understand tools instead of diving into complex ones, as simple systems often work just as well when paired with the right data. Overall, Joshua advised staying focused on customers and building a clear, team-wide plan for personalization.
In this episode, we cover:
(00:00) Joshua Mabry's Background and Expertise
(03:17) Defining Personalization
(06:37) What Companies Should Avoid in Personalization
(09:17) When to Consider Personalization
(10:17) When To and Not To Do Personalization
(12:13) The Importance of Incrementality in Personalization
(16:58) A Framework For Assessing Your Personalization Readiness
(21:50) Personalization Case Studies
(25:34) Personalization Research and Benchmarking
(30:23) The Role of AI in Personalization Strategies
(33:44) Final Thoughts and Resources
Referenced
Book: Introduction to Algorithmic Marketing: Artificial Intelligence for Marketing Operations - A detailed guide that combines economic theory and machine learning to explore advanced marketing automation techniques, focusing on programmatic micro-decisioning in areas like targeted promotions, ads, eCommerce search, recommendations, pricing, and optimization.
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