Price Information Patterns in Web Search Advertising: An Empirical Case Study on Accommodation Industry

Abstract—Unlike advertising in traditional media, web search advertising content can be easily customized with little cost. In this paper, we apply content analysis and regression models on 11, 818 unique ads related to the accommodation industry to empirically investigate how advertisers customize price information in their web search advertising content. To the best of our knowledge, our study is the first of this kind. We find that advertiser characteristics, such as website traffic, product quality, and position in the distribution chain, affect both the amount and forms of price information in its search advertising content. Moreover, the use of price information by an advertiser depends on query characteristics, such as search volume, cost per click (“CPC”), and specific words (e.g., trademark, location, price cue) in queries. Our empirical findings shed new light on how to effectively manage price information in search advertising, and suggest new research opportunities on web search advertising. Keywords-search advertising; content analysis; regression I