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Research Details

Measuring Customer Churn and Interconnectedness

Abstract

Abstract: Can an household-level financial transaction data yield new insights about firm-specific risk? We develop two new measures characterizing firms' customer bases -- the rate of churn in a firm's customer base and the pairwise similarity between firms' customer bases -- using an increasingly accessible class of household financial transaction data. We validate our approach by using the data to construct accurate pictures of firm revenue, growth, geographic dispersion, and customer base characteristics. We show that these measures of customer bases are impossible to construct utilizing traditional sources of firm data, but provide important insights into the behavior of both real firm decisions and firm asset prices. Rates of customer churn affect the level and volatility of firm-level investment, markups, and profits. Churn also affects how quickly firms respond to shocks in the value of their growth options (i.e. Tobin's~Q). Similarity between firms' customer bases highlights one under-explored type of predictability among stock returns -- we demonstrate that significant alpha can be generated using a trading strategy that exploits our index of customer base similarity across firms.

Type

Working Paper

Author(s)

Scott Baker, Brian Baugh, Marco Sammon

Date Published

2020

Citations

Baker, Scott, Brian Baugh, and Marco Sammon. 2020. Measuring Customer Churn and Interconnectedness.

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