Journal Article

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

Ghose, Anindya, Yang, Sha

2009

Overview

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 click-through 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.

• Publisher: INFORMS,Institute for Operations Research and the Management Sciences
• Subject: Advertisements / Advertising / Advertising campaigns / Advertising rates / Applied sciences / Bayesian analysis / Bayesian method / Brands / Business studies / click-through rates / Computer science; control theory; systems / Computer systems and distributed systems. User interface / Consumer advertising / Consumer behavior / Consumers / Conversion / Conversion experiences / conversion rates / Corporate sponsorship / cost per click / Data processing. List processing. Character string processing / Database searching / Electronic commerce / Email marketing / Exact sciences and technology / Externalities (Economics) / hierarchical Bayesian modeling / Information systems. Data bases / Internet / Internet monetization / Internet/Web advertising / Internet/Web search services / keyword ranking / Keywords / Management science / Marketing / Markov analysis / Markov processes / Memory organisation. Data processing / Monte Carlo method / Online advertising / Online searching / paid search / Panel data / Prices and rates / Product reviews / Profits / Retail stores / Revenue / Search engines / Software / Sponsored search / Stock conversion ratios / Studies / User generated content / Websites