Ep. 33 - Transformer Models for Customer Journeys, with Zipei Lu and P.K. Kannan

<p>Can the architecture behind large language models predict where a customer journey is headed? Zipei Lu (Baruch College) and P.K. Kannan (University of Maryland) treat a hospitality firm’s customer touchpoints like words in a sentence. They build a transformer whose attention patterns vary from customer to customer. </p><p>They talk with co-host Brett Gordon about how the paper moved across journals before landing at JMR and what they learned from industry feedback.<br>Lu, Zipei, and P.K. Kannan (2026), “AI for Customer Journeys: A Transformer Approach,” <em>Journal of Marketing Research</em>, 63(1), 1-26.<br>JMR: <a href="https://journals.sagepub.com/doi/10.1177/00222437251347268" target="_blank">https://journals.sagepub.com/doi/10.1177/00222437251347268</a><br>SSRN: <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4684617" target="_blank">https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4684617</a></p>