Profiling Retail Web Site Functionalities and Conversion Rates: A Cluster Analysis

The study uses the two-step clustering algorithm to profile Web retailers in terms of Web site functionalities and Web performance metrics and indicates the presence of complementarities among sets of functionalities associated with significantly different rates of conversion and monthly visitation.

Abstract

A Web site's conversion rate (the proportion of visitors who complete a desired action) is an important competitive metric. Web retailers invest significant effort in managing functionalities that can attract and convert visitors. Retailers' decisions are often based on tradition or simply follow competitors' efforts. The absence of an informed decision-making process usually leads to significant overlap in marketing efforts and investment in functionalities. This paper uses the two-step clustering algorithm to profile Web retailers in terms of Web site functionalities and Web performance metrics using data on the top 500 U. S. Web retailers ranked by their 2006 annual sales. The study finds an essential set of functionalities and indicates the presence of complementarities among sets of functionalities associated with significantly different rates of conversion and monthly visitation. It also finds different profiles for Web-only retailers versus those that have traditional channels in addition to the Web. These results may be useful for retailers in their decisions on providing Web site functionalities and in managing their conversion rates and other related metrics.