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Web Site Performance Analysis Success Assessment of Information Driven Web Site on User Traces
Abstract
With growing importance of the internet, Web sites have to be continuously improved. Web metrics help to identify improvement potentials. Particularly success metrics for e-commerce sites based on transaction analysis are commonly available and well understood. In contrast to transaction based sites, the success of Web sites geared toward information delivery is harder to quantify since there is no direct feedback of the user. We propose a generic success measure for information driven Web sites. The idea of the measure is based on the observation of user behaviour in context of the Web site semantics. In particular we observe users on their way through the Web site and assign positive and negative scores to their actions. The value of the score depends on the transitions between page types and their contribution to the Web site’s objectives. To derive a generic view on the metric construction, we introduce a formal meta environment deriving success measures upon the relations and dependencies of usage, content and structure of a Web site. In a case study we got aware that in single cases unsatisfied users had been evaluated positively. This divergence could be explained by not having considered the user’s intentions. We propose in this approach to integrate search queries carried within referrer information as freely available information about the user’s intentions. We integrate this new source of information into our meta model of Web site structure, content and author intention. Hence we apply well understood techniques such as PLSA. Based on the latent semantic we construct a new indicator evaluating the Web site with respect to the user intention. In a case study we can show that this indicator evaluates the quality and usability of a Web site more accurately by taking the user’s goals under consideration. We can also show, that the initially mentioned diverging user sessions, can now be assessed according to the user’s perception.
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