Paper Info
Title
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.
Year
DOI
Venue
2013
10.1109/ICDM.2013.100
2013 IEEE 13TH INTERNATIONAL CONFERENCE ON DATA MINING (ICDM)
Keywords
Field
DocType
search advertising, content analysis, regression
Search advertising,Contextual advertising,Advertising research,Advertising,Native advertising,Computer science,Online advertising,Keyword advertising,Artificial intelligence,Cost per impression,Machine learning,Cost per acquisition
Conference
ISSN
Citations 
PageRank 
1550-4786
0
0.34
References 
Authors
7
3
Name
Order
Citations
PageRank
Guanting Tang1754.57
Yupin Yang281.98
Jian Pei319002995.54