New York, NY – Advances in data analytics allow companies to uncover individual patterns of customer behaviors. Specifically, an important pattern of customer behavior is the detection of consumer routines. In a recent study, Columbia Business School’s Professor Oded Netzer and Professor Nachum Sicherman, along with their co-authors, University of Pennsylvania Professor Ryan Dew and Harvard Business School Professor Eva Ascarza, underscore the significance of identifying the moment when consumers integrate a service into their daily routines.
The research, Detecting Routines in Ride-sharing: Implications for Customer Management, builds a statical model to measure a new and important dimension of customer behavior, the degree of routineness in customer behavior. By identifying consumer routines, companies can tailor their marketing and services more precisely to cater to the needs of their most valuable customers. The researchers collaborated with a rideshare company, analyzing usage data to identify routine users. They detected several different patterns of routines, whereas some customers may be mainly active during the week, others may be weekenders. Some of the identified routines include: a commuting routine, a night and weekend travel routine, a work hard, play hard routine with morning travel to work but late-night return, and an evening travel routine. The researchers found that routine customers not only provide a steady revenue stream but also display higher loyalty and tolerance for price increases and service issues.
The ability to detect and understand consumer routines offers companies the opportunity to adapt their offerings and engagement strategies to attract and retain routine customers, aligning perfectly with businesses' growing recognition of the value of understanding and leveraging consumer data in today's data-driven marketing landscape.
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