Customer Management Dynamics and Cohort Analysis
The digital revolution has allowed companies to amass considerable amounts of data on their customers. Using this information to generate actionable insights is fast becoming a critical skill that firms must master if they wish to effectively compete and win in today’s data-driven marketplace. This note explains the value of examining customer metrics, such as retention rate, revenues, and social influence (k-factor), on an ongoing basis by conducting a cohort analysis. Such an analysis segments customers using one or more criteria, and tracks the behavior and performance of each of these segments over time. Using several instructive examples, the presentation highlights the benefits of running a cohort analysis for deriving a deep understanding of customer trends. Moreover, the examples expose the pitfalls that arise from not accounting for segment characteristics (such as when a customer joined, from what media vehicle they were acquired, how heavily they use the product, etc.) and not paying attention to the evolution of customer metrics over time. The implications of conducting a cohort analysis for firm strategy and for determining customer lifetime value (CLV) are discussed.
Keywords: cohort analysis; Customers; Data and Data Sets; Segmentation; Analysis; Customer Value and Value Chain;
Citation:
Ofek, Elie, Barak Libai, and Eitan Muller. "Customer Management Dynamics and Cohort Analysis." Harvard Business School Background Note 520-122, June 2020. View Details