and Coupon Usage from Aggregate Information Most researchers in the Marketing literature have typically relied on disaggregate data (e.g., consumer panel) to estimate the behavioral and managerial implications of coupon promotions. In this article, we propose the use of individual-level Bayesian methods for studying this problem when only aggregate data on consumer choices (market share) and coupon usage (number of distributed coupons and/or number of redeemed coupons) are available. The methodology is based on augmenting the aggregate data with unobserved (simulated) sequences of choices and coupon usage consistent with the aggregate data. Different marketing scenarios are analyzed, which differ in terms of their assumptions about consumer choices, coupon availability and coupon redemption
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