Nicolas Padilla
Assistant Professor of Marketing
London Business School
Nicolas Padilla is an assistant professor of marketing at London Business School, where he builds probabilistic machine learning models of consumer preferences, customer journeys and marketing measurement. He was an equal first author of a study showing that people who started using ChatGPT and other chatbots searched less on traditional search engines and visited fewer small websites.
Measuring the Shift Away from Search
"These shifts also raise competitive questions, as LLMs increasingly operate as alternative gateways to information that challenge the central role long held by search engines," Padilla and Anja Lambrecht said in a February 2026 London Business School article about their paper, The Impact of Early LLM Adoption on Online User Behavior. The study, written with H. Tai Lam and Brett Hollenbeck of UCLA Anderson and accepted at Management Science, followed the desktop browsing of American households from late 2022 through 2023 and compared people who adopted chatbots early with those who started later.
Searches fell slowly at first and, after about 20 weeks, sat more than 20% below pre-adoption levels. Question-based searches declined while navigational searches for a brand or site held steady, and large websites kept their traffic while smaller sites that depend on search referrals lost visits. "Substitution away from direct website visits has implications for monetisation," the researchers said, pointing to a drop in display ad exposures among heavy online shoppers, while search ad exposures did not decline. Lambrecht and Padilla also walked through the findings in a January 2026 LBS video.
Modeling Consumers with Machine Learning
"I explore how companies can leverage first-party data and sophisticated machine learning tools to enhance marketing decisions," Padilla writes on his personal site. One stream of his research asks how firms can infer what customers prefer when they have little data about them, and how the sequence of steps along a customer journey reveals those preferences. Another addresses marketing mix models, including effects that change over time and frameworks that fold in evidence from experiments. He co-wrote "Probabilistic Machine Learning: New Frontiers for Modeling Consumers and their Choices," accepted at the International Journal of Research in Marketing in 2026.
From Universidad de Chile to Columbia
Padilla earned a BSc in engineering science and an MSc in operations management at Universidad de Chile in Santiago, Chile. He then completed an MPhil and a PhD in quantitative marketing at Columbia Business School before joining London Business School.