We began with a content inventory of the on-line help system. This was an important first step in describing the relationships between the different pages since it allowed us to answer questions like "Which help pages are most commonly accessed?", "What search terms are most common?" and "How many help pages does the typical user view in a session?" Answers to these questions helped us classify the content into "critical" and "secondary" content.
Next, we discovered how end users thought about the structure of the help system by using a card sorting technique. We asked 18 participants to sort a selection of help pages into groups that made sense to them.
Finally, we established the navigation structure. This was derived from a cluster analysis of the data (a dendogram), a surface map showing how often items were grouped together and a qualitative analysis of comments and annotations made by participants during sorting.
As a result of our work, the new information architecture reduced the number of support enquiries from users who were unable to find or understand content. Users could now solve issues themselves, which indirectly increased the number of sales and registrations. The work also enhances our client's reputation as a site that people can use and trust.