Drivers and Dynamics: Managing Customer Relationships in Data -Rich Environments

With the growing importance of the service sector and subscription-based models, effective management of customer relationships has become both increasingly important and
increasingly plausible. This dissertation focuses on two key outcomes in relationship management:
customer churn and cross-buying.

Service companies in competitive environments face significant customer churn, underscoring the importance of understanding and managing this behaviour. Chapter 2 therefore presents insights from the first meta-analysis of the churn literature. In this chapter, we analyse data from 96 studies involving over six million customers and examine the impact of various churn drivers and moderating factors like industry, region, and competitive intensity.

Understanding and managing cross-buying behaviour is crucial in services, and an increasing amount of data is available to do so. Chapter 3 contributes to this goal by providing the first empirical analysis of so-called cross-buying journeys, which focus on the evolution of customers’ openness to cross-buying over time. In this chapter, we model cross-buying journeys using data from 14,933 insurance customers over three years. We find that the nature and frequency of customer-visited touchpoints can predict future cross-buying. Additionally, we find that the effectiveness of cross-selling efforts depends on a customer’s current trajectory.

We present a general discussion, conclusions and suggestions for future research in chapter 4. This dissertation contributes to the customer relationship management literature, particularly in the context of services. Both the approaches and results are particularly relevant for firms that are not just interested in managing customer relationships, but in creating value for customers. in data-rich environments.