Where Do the Most Active Customers Originate from and How Can Firms Keep Them Engaged

We study how digital service firms can develop an active customer base, focusing on two questions. First, how does the way customers use the service post-adoption to meet their own needs (personal usage) and to interact with one another (social usage) vary across customer acquisition methods? Second, how do firm-to-customer and customer-to-customer communications promote usage? We study these questions using two data sets and by developing a multivariate hierarchical Poisson hidden-Markov model. The model fits the data significantly better than univariate and latent class models. We find that indeed post-adoption behavior varies depending on customer acquisition method and dynamic states. At the total usage level, in one context, an annotation and note-taking service, customers who heard about the service through Search and Mass-Invite exhibited significantly higher usage behavior than those who joined through Word-of-Mouth (WOM), whereas in a cloud-based file storage service, customers who joined through WOM referrals tended to exhibit higher usage behavior. Yet examining specific types of behavior reveals a more nuanced picture. For example, in the file storage service case, WOM-acquired customers tended to exhibit higher personal usage but lower social usage. Similarly, in both contexts, communications post adoption influenced engagement, but in different ways. Firm-to-customer communications, such as through company posts to Twitter and blog entries, had varying effects on customer behavior, and in some cases led to lower personal and/or social usage, while customer-to-customer communications tended to increase customer engagement across latent states and in both data sets. The findings suggest firms should pay attention to how the mode of customer acquisition is related to subsequent usage intensity for their offering, and encourage customers to share information with each other post-adoption.