The optimal Choice of pre-launch reviewer

Gill, D. and Sgroi, D. (2007) The optimal Choice of pre-launch reviewer (Mimeo) Mimeo 28pp.

Abstract

We consider the impact of pre-launch reviews on sales of products of quality unknown to consumers. Sales occur simultaneously after consideration by a reviewer with a known level of bias. Consumers observe the reviewer’s decision and a private signal. Using convex analysis we prove three major results: (i) a monopolist, which can choose the type of reviewer and the price conditional on the chosen reviewer’s decision, will always want to have its product reviewed; (ii) choosing an extreme reviewer, that is either the toughest or softest reviewer type available, is always optimal; and (iii) the switch from the toughest to softest reviewer occurs when the precision of private information reaches a calculable threshold. The paper provides a justification for the existence of heavily biased reviews and tests, and also suggests a clear course of action for firms in different situations. For example, an entrant with a very innovative product should risk a tough pre-launch test, while an incumbent with a new product that provides only a small change over an existing one would do best using a soft pre-launch review.

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