Visualizing online activity

Look and learn which page of perhaps thousands Web site visitors linger on before clicking yes and no, which drove them to the exit button, and many more actionable patterns, trends, and insights. T he dot-com revolution established the e-channel as a critical component of corpo-ration/customer interaction. A characteristic aspect of this channel is its rich instrumen-tation, whereby every visit, click, page view, purchasing decision, repeat visit, and other fine-grain detail describing online visitor activity can be captured automatically on the fly and stored for later analysis. The problem for business managers and site operators , as well as for Web site designers, is that the huge volume of relevant data overwhelms conventional analysis tools (such as spreadsheets and reports). To overcome this problem, I describe how my company, Visual Insights, and other organizations have developed information visualization tools for displaying Web site structure, navigation, paths, flows, and activity. Information visualization is a research area in computer science that focuses on creating rich visual interfaces to help users understand and navigate through complex information spaces. Data sets are frequently large and time-varying and usually involve multi-dimensional structure. Unlike scientific visualization, where the research focus is creating 3D representations of physical phenomena, the fundamental problem for developers of information visualizations is that, because the data is nonspatial, it lacks natural physical representation. Thus, the information visual-ization research challenge is how to invent new visual metaphors for presenting information and developing ways to manipulate these metaphors to make sense of the information. Applied to e-business data, information visualiza-tion designers face three significant issues: Scale. There are a vast number of Web sites, each of which may be arbitrarily complex. The largest of them in terms of numbers of page views accommodate millions of visitors per day. The combination of complexity and volume overwhelms traditional approaches to calculating and analyzing Web site activity. For effective analysis, information visualiza-tion systems have to manipulate and process exceedingly large, real-time data sets. Dimensional complexity. It is now technically feasible and cost-effective for any organization operating a Web site to collect rich, fine-grain, online data sets. Integrating online and offline activity further increases the dimensionality of the problem. Moreover , many of the most interesting and important analysis problems involve correlating site activity with enterprise data.