IC Toolkit is a series that dives into a Designer, Researcher, or Developer’s goody bag to find out what they use to get through the day. Furthermore, how they supercharge their workflows or get inspiration for a project.
Today, we feature User Experience Research Co-op, Meghan Plank, discussing her go-to tools.
In general, our research “toolkit” is composed of online literature, such as academic journals and UX magazines, and software, such as Excel, SPSS, and eye-tracking programs. Excel and SPSS are especially vital for analyzing quantitative data, particularly when there is a lot of it to be coded.
Here at IC, we believe numbers are… well, exactly that. Numbers. They’re part of the user’s story, but certainly not enough to write the whole novel. We firmly believe in the power of qualitative data, which we gather through client interviews, usability testing, think-aloud protocol, and contextual inquiries (to name a few methods). Numbers can tell us a lot about the efficiency of a certain layout, or provide some reassurance around the decision to change a feature. But qualitative data – direct quotes from users, body language, emotion, gestures, etc. – can tell us why we need to change a feature. It answers questions like, “Why does the user want to interact with the interface in this way?”
So, without further ado, here are my top 3 tools for analyzing qualitative and quantitative data:
Expos (yes, that’s right – expo markers)
When it’s time to analyze a set of qualitative data, I prefer the old pen and paper method. Scratch that – I prefer the modern version of pen and paper – Expos and whiteboards. Expo markers afford me the opportunity to step back from an overwhelming spreadsheet and think critically about the responses to each item. With expo markers, I am equipped to craft any phrase, diagram, graph, chart, or shape that best fits the data. As the patterns emerge, I create codes that I can then draw directional symbols to combine, re-sort, or connect two or more related codes.
Like I said, we’re not hugely concerned about numbers. But, when we have a lot of quantitative data to analyze, StatsGuru is a fantastic tool for brushing up on methodology and data interpretation.
A great feature of this app is that users can bypass the decision tree process. If you think you know the name of the test, you can simply select it from a drop down menu on the home screen. Again, the test name, description, and screenshots will appear.
There are only two major drawbacks of StatsGuru. The first is that it’s not free ($1.99 on the iPhone app store) – a rather disappointing fact for this penny-pinching college student. The second drawback is that the app lacks zoom functionality. The screenshots of SPSS are thus very difficult to see on a mobile phone. Comparatively, the tablet version is much better for viewing the app.
Excel is a tool I use almost every day. I decided to include it in this toolkit because I think it is more than an analytical tool – it’s also a valuable organizational tool. Prior to working at IC, I used Excel primarily for running statistics in various business and research methods classes. Nowadays, I’m using Excel for all sorts of things from coding large batches of qualitative data, to categorizing codes, and tracking user responses. It’s clearly not as flexible or colorful as whiteboarding, but when time is of the essence, it’s my go to tool.