Where do the Most Active Customers Originate and How Can Firms Keep Them Engaged?
In this paper, we study how firms offering Web services can acquire and develop an active customer base. We focus on two basic questions. First, how does the method of customer acquisition affect the way customers use the service to meet their own needs and to interact with one another? Furthermore, how do firm-to-consumer communications affect the way customers use the service relative to customer-to-customer communications? Using data from a Web service start-up, we estimate a multivariate hierarchical Poisson hidden Markov model that captures the joint dynamics of customer engagement (personal and social usage) at the individual customer level. We segment the customers by the three most typical acquisition tools for Web start-ups: Word-of-Mouth (WOM), Mass-Invite (e.g. Techcrunch), and Search (e.g. Google). We find that customers who hear about the service through Search and Mass-Invite exhibit higher usage behavior as compared to customers from WOM, and that customer-to-customer communication is more effective than firm-to-customer communication at keeping customers engaged post-adoption. Even though WOM-acquired customers use the service less than customers from other adoption routes, WOM in the form of customer-to-customer sharing more robustly transitions customers into higher usage states. Hence, firms may be well-advised to encourage customers to share with each other post-adoption. Our work calls for a deeper understanding of the mechanisms that drive usage behavior, and for further exploration in the possibility of segmenting customers based on how they were acquired.
Keywords: Customer Engagement;
Hidden Markov Models;
Customer Relationship Management;
Marketing Reference Programs;
Web Services Industry;