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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/29455
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| Title: | A Dynamic Model of Sponsored Search Advertising |
| Authors: | Yao, Song - Duke University
Mela, Carl F. - Duke University |
| Issue Date: | 2008 |
| Series/Report no.: | Net Institute Working Paper;08-16 |
| Abstract: | Sponsored search advertising is ascendant Jupiter Research reports
expenditures rose 28% in 2007 to $8.9B and will continue to rise at a
15% CAGR, making it one of the major trends to affect the marketing
landscape. Yet little, if any empirical research focuses upon search
engine marketing strategy by integrating the behavior of various agents
in sponsored search advertising (i.e., searchers, advertisers, and the
search engine platform). The dynamic structural model we propose serves
as a foundation to explore these and other sponsored search advertising
phenomena. Fitting the model to a proprietary data set provided by an
anonymous search engine, we conduct several policy simulations to
illustrate the bene ts of our approach. First, we explore how
information asymmetries between search engines and advertisers can be
exploited to enhance platform revenues. This has consequences for the
pricing of market intelligence. Second, we assess the effect of allowing
advertisers to bid not only on key words, but also by consumers
searching histories and demographics thereby creating a more targeted
model of advertising. Third, we explore several different auction
pricing mechanisms and assess the role of each on engine and advertiser
profits and revenues. Finally, we consider the role of consumer search
tools such as sorting on consumer and advertiser behavior and engine
revenues. One key finding is that the estimated advertiser value for a
click on its sponsored link averages about 24 cents. Given the typical
$22 retail price of the software products advertised on the considered
search engine, this implies a conversion rate (sales per click) of about
1.1%, well within common estimates of 1-2% (gamedaily.com). Hence our
approach appears to yield valid estimates of advertiser click
valuations. Another finding is that customers appear to be segmented by
their clicking frequency, with frequent clickers placing a greater
emphasis on the position of the sponsored advertising link. Estimation
of the policy simulations is in progress. |
| URI: | http://hdl.handle.net/2451/29455 |
| Appears in Collections: | NET Institute Working Papers Series
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