If the output is to be a stellar information architecture, what are the inputs we need?
Card sorting is a technique to gain insights and understanding into how users would organize the content we provide in our digital products, and what labels they would give to that content. It uncovers users’ mental models related to the content on our site, app, software, etc. We, as IA’s, should use that insight to inform a better IA for our product bearing in mind that card sort results are a great input, but not the only one we need to consider.
In our last post on Information Architecture, we talked about card sorting and about the fact that as a precursor to doing a card sort, we need to understand a few things so as not to introduce bias:
Then we conduct the card sort and gather the data. So what now?
There are a few good online tools for card sorting that don’t require a lot of deep knowledge about the statistical analysis behind the results. Knowing that the kind of stats that are running in the background of these tools is a kind of cluster stats is helpful conceptually, and knowing that the output is a hierarchical dendrogram sounds impressive; but, the answers to how to structure our IA are only suggested by the impressive and complicated looking dendrograms – not prescribed.
So, recall one of the definitions of information architecture:
At this point in the process of creating a stellar IA, (we’ve done our user research, have our user personas, conducted our card sort), we have to start combining the art with the science. The kinds of questions that the science part, (the card sort results), will answer for us are:
Now we start to inject the “art” part – these are also essential inputs we need to consider. With what we know from the science and what we (should) know about our users and their scenarios of use:
And, finally, what does the business need? Are there requirements they insist upon in terms of the voice or tone that’s conveyed through the IA? Does an organisational approach to the IA make sense in their context? The impact of a good IA to a business can’t be understated…but that’s another post for another time.
By now, only a couple of these approaches will likely strike you as the “best” to use, so start out trusting that feeling and start to play with the top level groupings. Don’t labour over this too much – just start creating the IA, let it sit for a bit, come back to it and tweak it. Validate that the groupings make sense from the point of view of a SME, but exercise your good judgement about the balance that’s needed between a SME’s point of view and your users – if your users aren’t all also SMEs. Then start to test it – again – with real users by conducting a reverse card sorting activity … which we’ll discuss in an upcoming post.
Cindy Beggs, MLS, is Partner and Vice President at Akendi, a firm dedicated to creating intentional experiences through end-to-end experience design. To learn more about Akendi or user experience design, visit www.Akendi.com.
Akendi is a product strategy, user experience design and usability research firm. We are passionate about the creation of intentional experiences – whether those involve digital products, physical products, mobile, service or bricks-and-mortar interactions. We work shoulder-to-shoulder to optimize the experiences you deliver. Akendi Corporate Overview (PDF).
Experience Thinking innovation firm in Product UX Strategy, User Experience Design & Usability Testing for Companies: Toronto, Ottawa, Montreal, Vancouver, Canada.
T: +44 (0)20 35982601
22 Highbury Grove
London, N5 2EF