Consumer Online Search Strategy and Its Implications for Search Engine Marketing

Consumer search literature generally maintains that consumers maximize their expected payoffs when engaging in information search. Yet, the process of consumer information search has not received adequate attention in the e-commerce domain. In particular, in the dynamic e-commerce sector of search engine marketing, little is known about how consumers decide on which links to click and in what orders ---when they are provided with a list of web site links in search engine results pages (i.e., organic or natural search results). This issue is further complicated by consumer heterogeneity as some consumers are more likely to rely on search engine display rankings as surrogates for the level of congruency between search tasks and search results.Understanding how consumers' search behaviors with regard to search engine results has important implications for the search engine marketing industry. For instance, firms that utilize search engines for online advertising must decide on the appropriate techniques so as to achieve desirable rankings in search engine results given consumers' online search strategy. In addition, this research topic carries significant social implications for consumers, whose search payoff may be lower if they pledge blind allegiance to the relevancy of top ranked search engine results.The study intends to fill a void in the e-commerce literature by identifying key factors that affect consumer information search strategy in the search engine results setting. In particular, the researchers explicitly model the impact of information congruency (or matching probability) between search results and search tasks on their search behaviors. The researchers also take into account consumer heterogeneity in online search strategy in the model. This study will consist of two parts. In part I, the researchers shall derive a theoretical/analytic model that incorporates key decision parameters underlying the information search process in search engines, including matching probability, order of display, and consumer heterogeneity. The model will also lead to a series of testable predictions. In part II, the researchers use controlled experiments to corroborate their model assumptions and also to test the predictions derived from the theoretical model. Finally, the researchers derive managerial implications for firms that use search engines for online marketing, one of the most important sectors of e-commerce.