Cooperative Search Advertising

Time：May 26th (Thursday) 10:30 -12noon

Location: Zhifuxuan, National School of Development, Peking U.

Speaker: Tony Ke, Assistant Professor of Marketing, MIT Sloan School of Management

 

Abstract

Retailing is among the top spenders in search advertising, and channel coordination in search advertising is becoming an important managerial decision for both manufacturers and retailers. Manufacturers and retailers cooperate in search ad spendings, while at the same time, compete in search ad auctions. Cooperative search advertising is new to study, because all channel members' advertisements compete with each other in position auctions, in contrast to the usual complementary effect in traditional cooperative advertising. We build a game-theoretic model to answer the following research questions: Why would a manufacturer sponsor several retailers to bid for his product at the same time? Isn't that indeed competing with himself and burning his own money? Given higher margin from direct sales than via retailers, why sometimes manufacturers do not advertise by themselves? What is a manufacturer's optimal cooperative search advertising strategy?

 

We focus on a manufacturer and multiple retailers' intra-brand competition in search advertising, but also count for the inter-brand competition with advertisers of other brands. We consider various model setups where the manufacturer can bid by himself, as well as incentivize his retailers to bid higher by providing positive participation rates in their bidding. We find the participation rate mechanism is inefficient in the sense that the retailer's bid is too low to maximize total channel profit. We also find that, the retailer with higher total channel profit per click always gets higher position, and given two symmetric retailers, the manufacturer may optimally choose to cooperate with only one of them. It is also shown that the manufacturer will optimally sell via its retailer even if a direct sale generates higher profit per click, as long as the total channel profit per click is higher.

 

T. Tony Ke is an Assistant Professor of Marketing at the MIT Sloan School of Management. His research is in the area of marketing analytics, social networks, and marketing strategy.  His current work focuses on modeling consumer search for information, especially on multiple attributes of products, and analyzing firms’ pricing and product strategies. He has work or consulting experience with Microsoft, Xerox, Walmart, Facebook, and Charles Schwab. He holds a PhD in Operations Research, an MA in Statistics, and an MA in Economics from University of California, Berkeley, and a BS in Physics and a BS in Statistics from Peking University.