Virginia Gow, Content Strategy Lead at Springload: Often our clients have a wealth of really good – or important – content they want to connect with audiences or customers but it’s just not being used, so they’re not getting the return on investment. Small adjustments to how the information is organised so it’s closer to what users expect or are trying to do, or changes to what things are called, can make a huge difference.
When we were redeveloping Massey University’s website, for example, we made so many small changes to labels so they matched what students called things rather than what the university called them. For example, changing “distance learning” to “distance and online study” will mean information about how flexible study at Massey can be will reach far more people who could potentially benefit from what Massey offers.
Chris Webber, Customer Success Manager at Optimal Workshop: My favourite story of IA is about a supermarket trying to optimise their online shopping offering. They were consistently having shoppers abandon their carts mid-shop and wanted to find out why. How should they structure their online shopping in a way that makes sense to their customers?
On their IA journey, they had to learn how their customers grouped different products, where they expected to find them, and how they would be categorised. Do you find bacon with pork in the meat section? Or maybe with the other breakfast foods, like cereals or eggs? Why does salsa appear twice in the supermarket in two different sections? Finding meaningful answers to these questions, backed by research, is what is so exciting about IA for me. Creating beautiful and intuitive experiences that feel effortless for your customers.
Aidan Pearce, Product Coach at Optimal Workshop: I worked with a company who were looking to restructure their Help Centre experience in response to their customer support teams being continually stretched. Through initial research, we identified they have two key customer segments. The team were able to build defined Help Centre experiences for each of these customer groups using labels that aligned best with the knowledge and perspectives of each group.
Through OptimalSort in particular, it was found that one customer group opted for 3 very generic categories to show initially, whereas the other group (who had more technical perspectives) opted for 6-7 categories at the top level of the Help Centre. This informed the design decisions when creating intuitive experiences for customers from each segment. Treejack was also iteratively used to A/B test proposed taxonomy structures until final structures with high levels of success were decided on.