A Renewable-Resource Approach to Database Valuation

We demonstrate in this paper that firms should view customers in a database as a renewable resource when valuating them. Indeed, customer names flow in and out of the firm’s databases, and the goal of the firm is to optimize the overall customer acquisition/cultivation/attrition process. The renewab...

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Bibliographic Details
Main Authors: Dreze, Xavier, Bonfrer, Andre
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2003
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/1913
https://ink.library.smu.edu.sg/context/lkcsb_research/article/2912/viewcontent/1603paper1.pdf
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Institution: Singapore Management University
Language: English
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Summary:We demonstrate in this paper that firms should view customers in a database as a renewable resource when valuating them. Indeed, customer names flow in and out of the firm’s databases, and the goal of the firm is to optimize the overall customer acquisition/cultivation/attrition process. The renewable resource approach to the problem of maximizing the profits generated by a flow of customer names is more appropriate than the traditional Customer Lifetime Value (CLV) approach. We show that CLV underestimates the true value of names (by more than 400% in some cases) and leads to sub-optimal customer relationship management and acquisition strategies. For instance, while a firm should discount future profits when valuating its database, it should not discount these same profits when setting its acquisition policy. We derive the first-order condition, and perform comparative statics, for a firm trying to optimize its contact policy. Perhaps the most interesting result stemming from the comparative statics is the implication that start-up companies should contact their customers less frequently than established companies. Start-ups should resist the temptation of boosting short-term revenues in favor of accumulating names by spacing communications. We finish the paper with an analysis of customer heterogeneity.