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Marketing Science
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Segmenting Customers from Population to Individuals: Does 1-to-1 Keep Your Customers Forever?
IEEE Transactions on Knowledge and Data Engineering
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Marketing Science
Technical Note---Personalized Dynamic Pricing of Limited Inventories
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The Perils of Behavior-Based Personalization
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Manufacturing & Service Operations Management
Demand Dynamics in the Seasonal Goods Industry: An Empirical Analysis
Marketing Science
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We explore opportunities for targeted pricing for a retailer that only tracks weekly store-level aggregate sales and marketing-mix information. We show that it is possible, using these data, to recover essential features of the underlying distribution of consumer willingness to pay. Knowledge of this distribution may enable the retailer to generate additional profits from targeting by using choice information at the checkout counter. In estimating demand we incorporate a supply-side model of the distribution channel that captures important features of competitive price-setting behavior of firms. This latter aspect helps us control for the potential endogeneity generated by unmeasured product characteristics in aggregate data. The channel controls for competitive aspects both between manufacturers and between manufacturers and a retailer. Despite this competition, we find that targeted pricing need not generate the prisoner's dilemma in our data. This contrasts with the findings of theoretical models due to the flexibility of the empirical model of demand. The demand system we estimate captures richer forms of product differentiation, both vertical and horizontal, as well as a more flexible distribution of consumer heterogeneity.