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Designing Information to Engage Customers

Authors: Liang Guo 0004;

Designing Information to Engage Customers

Abstract

Collaborative customization is common in many markets. Sellers and customers can collectively discover the value of the product’s basic design. Customers’ willingness to pay can also be increased by being engaged to improve the product design. We study how a seller can design the information structure of collective learning about the product’s basic value to induce costly customer engagement. We consider a setting in which the parties’ expected payoffs are determined endogenously through the strategic interaction between seller pricing and customer engagement and purchase. The customer tends to be engaged in equilibrium, as the uncertainty on the product’s basic value becomes higher to dilute the responsiveness of the optimal price to customer engagement. Therefore, the seller seeks to maximize the probability of generating an intermediate posterior belief. Thus, the optimal information design involves either exaggerating or downplaying the product’s basic value when the prior is low or high, respectively. We show that considering restrictive information structures can generate qualitatively different implications. We also examine how the unobservability of engagement may influence the parties’ strategic interaction, their expected payoffs, and the seller-optimal information design. Interestingly, unobservability may lead to lower equilibrium engagement, hurt the seller, render the customer’s equilibrium expected payoff to increase as customer engagement becomes less important or more costly, and yield more or less information provision. This paper was accepted by Dmitri Kuksov, marketing.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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