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Expert review supported with Web analytics data

Client: 
Employment agency
Tasks: 
Expert Review and Web analytics

Assignment

A large employment agency in the Netherlands was planning to redesign their website. One of the most important elements of the site is the option for users to search the available jobs. Additionally, the site offered a way to directly apply to these jobs online.

In addition to searching for jobs in the traditional way (using keywords), the new site would enable the users also to browse through all the available jobs. To find out in an early phase if the set-up of this new browse feature was considered easy to use, User Intelligence proposed to conduct an Expert Review.

Methods used

The study did not only focus on the new job browser, but the whole process of finding a job and applying online was reviewed (including the registration process). To back-up the qualitative findings of the Expert review with user data, the review was complemented with web analytics data.

By combining these two methods it became possible to validate and ground the issues found in the Expert review with quantitative data. One of the reviewers for example, assumed that certain elements on the homepage would be confusing to visitors. Using web analytic data we could directly draw conclusions based on site traffic data that this was an issue.

Additionally it became possible for the reviewer (usability expert) to search for explanations for remarkable trends in the usage statistics. Good examples of this were low number of visits for some of the key pages of the site. The reviewer could directly analyze these pages to see if there are any possible reasons for these findings.

Result

Combining data from web statistics with a qualitative review made it possible to have a more solid foundation of the findings from the review. Recommendations regarding identified issues could be made with much more certainty. A traditional Expert review is the result of the experience of one or more reviewers. By using the possibilities offered by Web analytics, the actual behaviour of thousands of visitors were added.

Although these visitors couldn’t give personal feedback (as can be done in a usability test), their actions were recorded. “Which pages were visited?”, “Where did the visitors come from?” and “What are the most frequently followed paths through the site?” are questions that can be answered. By combining this type of quantitative data with a qualitative review, a more complete picture of the state of the site emerged. These insights helped in making decisions on how to improve the site in the redesign process.