Bundling Customers: How to Exploit Trust Among Customers to Maximize Seller Profit

TL;DR

This paper explores how bundling customers in auctions of digital goods, leveraging their ability to learn each other's valuations, can increase seller profits beyond traditional mechanisms.

Contribution

It introduces a novel bundling mechanism that exploits customer trust and valuation learning to improve seller revenue over Myerson's classic auction design.

Findings

Bundling increases seller profit when customers can learn each other's valuations.

The proposed mechanism outperforms traditional auction strategies in simulated environments.

Customer trust and information sharing are key to maximizing digital goods sales.

Abstract

We consider an auction of identical digital goods to customers whose valuations are drawn independently from known distributions. Myerson's classic result identifies the truthful mechanism that maximizes the seller's expected profit. Under the assumption that in small groups customers can learn each others' valuations, we show how Myerson's result can be improved to yield a higher payoff to the seller using a mechanism that offers groups of customers to buy bundles of items.