The labels
for the web sites are going to be designed using several methods. First of all
some labels are defined using conten authors’s knowledge of the content that
the web site is going to contain. According to Morville & Rosenfeld this
method is useful for finding candidates for labels but not the final labels.
This I because the content authors are professional indexers and don’t
necessarily speak the language of the user (2007, p. 105). The labels defined
by the content authors are tested with users by using an open card sorting as
described earlier. The data from the card sorting are analysed and held
together with log data from the former web site. More specifically the log data
are analysed using Search Log Analysis (SLA) following recommendations from the article by
Jansen, Understanding User – Web
interaction via Web Analytics (2009). SLA has a grounded theory approach
where theories are grounded in observations from the real world rather than
hypotheses. This means that the method has an inductive approach as well as the
DBR method (p. 65). Using the knowledge from these three methods I as a
designer define the final labels in collaboration with the content author.
When the
web site is launched and has been running for about a month it is possible to test
whether the instructional goals has been fulfilled. As described earlier the
instructional goals are: 1) the users
should be able to find information that they are looking for and 2) be inspired
to explore the web site and find additional information of interest. Both goals
should be fulfilled leaving the user with a feeling of having had a good
experience where their individual wishes have been taken into consideration.
A useful method for doing this is web analysis. When doing a web
analysis Jansen is describing several metrics (2009). There is a lot of useful and interesting metrics that directly or
indirectly tell something about goal 1) and 2). In the following I am going to
describe some of the most obvious ones.
Keyword Analysis tells us what
keywords the user are searching for when finding our site. By looking at these
keywords in relation to the labels it tells us whether we have succeeded in
speaking the language of the users when designing the labels. Top pages is a metric that shows which
pages of the web sites that receive the most traffic. By looking at this it is
possible to analyse whether the pages has been sorted so that the post popular
pages are the ones that are easiest to access. It is also possible to get an
indication of whether we have succeeded in designing the page so that it suits
the different target groups. E.g. if the main menu Handikapvenlig has very low traffic compared to the other main
menus maybe the disabled people doesn’t feel that the web site design suits
them. Visit length is an important
metric as it tells us whether the user is spending time at the web sites or
just entering and leaving right away. This information can be combined with
another metric Referring URL which
tells what sites have directed traffic to the web site. My combining these two
set of data it is possible to see which sites that are referring the most
time-consuming users. E.g. does a site for disabled users refer a lot of users
that spend less than five seconds on the site? If this is the case, it could
also be an indication that the design is not appropriate for the segment of
disabled people. The last metric that I am going to mention is Visitor path. This gives us information
about how the user navigates through the web site and can give an indication of
whether the user finds what he/she is looking for.
Even though
web analysis provides some valuable data it has some shortcomings. Jansen
stresses that “These shortcomings include failing to understand the affective,
situational, and cognitive aspects of system users.” (2009, p. 51). He
therefore recommends that the method is combined with other data such ad
surveys and laboratory studies (ibid. p. 51ff). In the case of testing whether
the instructional goals of the web site for Feriecenter Slettestrand has been
fulfilled it would be ideal to combine the web analysis with a usability test
followed by an interview or a post questionnaire.
This post is going to be updated with reflections upon the interpretive framework used in this design...