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An Empirical Analysis of Search Engine Advertising: Sponsored Search in Electronic Markets

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成果类型:
期刊论文
作者:
Ghose, Anindya;Yang, Sha
通讯作者:
Ghose, A
作者机构:
[Yang, Sha] School of Economics and Management, Southwest Jiaotong University, 610031 Chenfgdu, China
[Ghose, Anindya; Yang, Sha] Leonard N. Stern School of Business, New York University, New York, NY 10012, United States
通讯机构:
[Ghose, A] NYU, Leonard N Stern Sch Business, 550 1St Ave, New York, NY 10012 USA.
语种:
英文
关键词:
online advertising;search engines;hierarchical Bayesian modeling;paid search;click-through rates;conversion rates;keyword ranking;cost per click;electronic commerce;Internet monetization
期刊:
Management Science
ISSN:
0025-1909
年:
2009
卷:
55
期:
10
页码:
1605-1622
文献类别:
WOS:Article;EI:Journal article (JA)
所属学科:
ESI学科类别:经济&商业;WOS学科类别:Management;Operations Research & Management Science
入藏号:
WOS:000270527900001;EI:20094412413776
机构署名:
本校为其他机构
院系归属:
经济管理学院
摘要:
The phenomenon of sponsored search advertising-where advertisers pay a fee to Internet search engines to be displayed alongside organic (nonsponsored) Web search results-is gaining ground as the largest source of revenues for search engines. Using a unique six-month panel data set of several hundred keywords collected from a large nationwide retailer that advertises on Google, we empirically model the relationship between different sponsored search metrics such as click-through rates, conversion rates, cost per click, and ranking of advertisements. Our paper proposes a novel framework to better understand the factors that drive differences in these metrics. We use a hierarchical Bayesian modeling framework and estimate the model using Markov Chain Monte Carlo methods. Using a simultaneous equations model, we quantify the relationship between various keyword characteristics, position of the advertisement, and the landing page quality score on consumer search and purchase behavior as well as on advertiser's cost per click and the search engine's ranking decision. Specifically, we find that the monetary value of a click is not uniform across all positions because conversion rates are highest at the top and decrease with rank as one goes down the search engine results page. Though search engines take into account the current period's bid as well as prior click-through rates before deciding the final rank of an advertisement in the current period, the current bid has a larger effect than prior clickthrough rates. We also find that an increase in landing page quality scores is associated with an increase in conversion rates and a decrease in advertiser's cost per click. Furthermore, our analysis shows that keywords that have more prominent positions on the search engine results page, and thus experience higher click-through or conversion rates, are not necessarily the most profitable ones-profits are often higher at the middle positions than at the top or the bottom ones. Besides providing managerial insights into search engine advertising, these results shed light on some key assumptions made in the theoretical modeling literature in sponsored search. ©2009 INFORMS.
参考文献:
Agarwal A., 2008, LOCATION LOCATION LO
AGGARWAL G, 2006, LECT NOTES COMPUTER, P15
ANIMESH A, 2009, INFORM SYSTEMS RES
Ansari A, 2003, J MARKETING RES, V40, P131, DOI 10.1509/jmkr.40.2.131.19224
Archak N., 2008, DERIVING PRICING POW

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