Detecting Routines: Implications for Ridesharing CRM

Forthcoming, Journal of Marketing Research

Columbia Business School Research Paper No. 3982612

Posted: 11 Feb 2022 Last revised: 28 Jun 2023

See all articles by Ryan Dew

Ryan Dew

University of Pennsylvania - Marketing Department

Eva Ascarza

Harvard Business School

Oded Netzer

Columbia University - Columbia Business School, Marketing

Nachum Sicherman

Columbia University; IZA Institute of Labor Economics

Date Written: February 12, 2023

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: routines, customer management, customer relationship management, Bayesian nonparametrics, Gaussian processes, machine learning, ride-sharing

Suggested Citation

Dew, Ryan and Ascarza, Eva and Netzer, Oded and Sicherman, Nachum, Detecting Routines: Implications for Ridesharing CRM (February 12, 2023). Forthcoming, Journal of Marketing Research, Columbia Business School Research Paper No. 3982612, Available at SSRN: https://ssrn.com/abstract=3982612 or http://dx.doi.org/10.2139/ssrn.3982612

Ryan Dew (Contact Author)

University of Pennsylvania - Marketing Department ( email )

700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States

Eva Ascarza

Harvard Business School ( email )

Soldiers Field
Boston, MA 02163
United States

HOME PAGE: http://evaascarza.com

Oded Netzer

Columbia University - Columbia Business School, Marketing ( email )

New York, NY 10027
United States

Nachum Sicherman

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States
212-854-4464 (Phone)
212-316-9355 (Fax)

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

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