Valuing Non-Contractual Firms Using Common Customer Metrics

There is growing interest in "customer-based corporate valuation," explicitly tying the value of a firm's customer base to its financial valuation. While much progress has been made in building a well-validated customer-based valuation model for contractual (or subscription-based) firms, there has been little progress for non-contractual firms. Non-contractual businesses have more complex transactional patterns because they are characterized by latent attrition instead of observable churn behavior, and often have highly irregular purchase timing and spend amounts, making it harder to reconstruct granular purchase behaviors from aggregated metrics (e.g., active users and the repeat rate). Nevertheless, a number of firms disclose a variety of customer metrics to their shareholders. The authors use indirect inference, a well-established econometric estimation procedure, to estimate the aforementioned customer behaviors using aggregated metrics. The authors show how the predictive validity of the models varies as a function of the metrics used. They apply this methodology to data from a large business unit of an e-commerce retailer, valuing the business unit as a whole, decomposing this valuation into existing and yet-to-be-acquired customers, and analyzing customer profitability