User-Driven: Why We Should Look at People Beyond Numerical Values
With the successful execution of our second UX workshop, we were very lucky to have had Ariel Lee from UBC’s UX Lab give us the rundown on collecting data; but what does “data” mean in the context of today’s world?
Chances are, you were probably creeped out by the Facebook ads that somehow know what you Googled a couple days back. Imagine searching for a couples Halloween costume one time and suddenly the internet seriously thinks you’re into lepidopterology and antique lamp shades. Dated memes aside, today’s world is more driven by data than you think.
Around the early 1900’s, a surge of competition amongst companies to promote their products and services gave way to the idea of marketing; that is, in simple terms, research-backed, customer-centric advertising. No longer were people being subjected to posters and commercials that seemed to just target everyone. Instead, companies strategized ways to increase their customer base by targeting specific audiences, allowing them to not only grow substantially but sustainably. It’s no surprise that these efforts still exist today, with companies even looking at ways to have their users market their products for them. In the same way that data drives marketing and business, it is also the reason that UX ever became a thing.
Let’s talk a little bit about history
For the ego-boosting engineers like myself, UX designer Caglar Araz found that one of the first accounts of usability came from engineers Whiteside and Nixon in a usability engineering journal published in 1987. There, they discussed that “usability exists in the experience of the person. If the person experiences a system as usable, it is.”
The way that we find out if something is usable is to gather data and test it. But if you’re like Jay-Z (or potentially an engineer) and think “men lie, women lie, but numbers don’t”, then I feel bad for you, son. There’s a lot to be said on thinking about data beyond just numbers on a graph.
Let’s say you’re given a problem, and your task is to ultimately come up with a solution. If you read my last article on defining the problem statement, you find a direction to approach the problem with. What do you need to know in order to find anything relevant? What kind of data do you need to prove your assumptions? What type of data is appropriate for this scenario? That’s where knowing the basics of gathering data come into play.
Exploring the different types of data
The realm of data exists in a variety of dimensions, namely: summative vs. formative, qualitative vs. quantitative and attitudinal vs. behavioural.
When you’re just starting, you want to use formative data collection in order to finalize the end form of the design, in comparison to summative data collection to test out the design as a whole.
When talking about performance, quantitative data helps us compare relative metrics such as time to execute a given task, whereas qualitative data tells us more about their experience using a certain product feature.
Understanding the notion that what users say they do is different from what they do is why attitudinal and behavioural data matter, and why we should observe rather than ask for some cases.
In the context of design at least, the data-driven world we live in today should really be the viewed as user-driven.
Understanding when to use certain data collection techniques allows us to ask the right questions at different stages of the design process. Coming up with good questions can give us clearer information to work with. Knowing that people exist beyond numbers gives us the power to create ideas that can really make an impact on someone’s life.
In our second workshop, we were able to successfully get participants to think about what they can do in order to ask better questions. We led a series of exercises to get them to identify problems with existing surveys, rephrase leading questions, perform a cognitive walkthrough and formulate their own interview questions. With data collection now under their tool belts, we can move on to figuring out what to do with this data.
On November 16th, we will find out how to synthesize data, taking what we know from users to formulate the facts and validate our assumptions. Stay tuned by following us on Facebook!
