Publications
Publications
- April 2024
- Journal of Marketing Research (JMR)
Detecting Routines: Applications to Ridesharing CRM
By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
Abstract
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal structures— for customer management. One reason for this dearth is the difficulty of measuring routines from transaction data, particularly when routines vary substantially across customers. We propose a new approach for doing so, which we apply in the context of ridesharing. We model customer-level routines with Bayesian nonparametric Gaussian processes (GPs), leveraging a novel kernel that allows for flexible yet precise estimation of routines. These GPs are nested in inhomogeneous Poisson processes of usage, allowing us to estimate customers’ routines, and decompose their usage into routine and non-routine parts. We show the value of detecting routines for customer relationship management (CRM) in the context of ridesharing, where we find that routines are associated with higher future usage and activity rates, and more resilience to service failures. Moreover, we show how these outcomes vary by the types of routines customers have, and by whether trips are part of the customer’s routine, suggesting a role for routines in segmentation and targeting.
Keywords
Ride-sharing; Routine; Machine Learning; Customer Relationship Management; Consumer Behavior; Segmentation
Citation
Dew, Ryan, Eva Ascarza, Oded Netzer, and Nachum Sicherman. "Detecting Routines: Applications to Ridesharing CRM." Journal of Marketing Research (JMR) 61, no. 2 (April 2024): 368–392.