Like it or love it, most fields come with their own sets of lingo, jargon, and ways of saying things that are not immediately obvious to the uninitiated. From industry specific terms, to hot topics of professional debate, to new philosophies, to soon-to-be-passe buzzwords, UX research is no stranger to such things.
Here are just a few terms you’ll certainly come across as you build your expertise in user research and as you work your way through our UX Research Field Guide. Should we add something to the list? Hit me up at email@example.com.
Design thinking is not new, but it is having a moment.
With origins going back to the 1960s and 70s, and specifically books like The Sciences of the Artificial, Visual Thinking, and How Designers Think, design thinking really hit prominence within design communities at Standard University in the 80s and 90s. Rolf Faste and David M. Kelley were colleagues at Stanford and Kelley went on to found IDEO in 1991. As IDEO describes it:
Design thinking utilizes elements from the designer's toolkit like empathy and experimentation to arrive at innovative solutions. By using design thinking, you make decisions based on what future customers really want instead of relying only on historical data or making risky bets based on instinct instead of evidence.
Design thinking is the center of Standford’s “d.school,” founded in 2004. D.school together with IDEO, the massive growth of Apple—which puts human centered design at the forefront—and the growth of design as a critical discipline in many hugely successful organizations like AirBnB, have served to bring design thinking to the larger realm of business, not “just” design and product development functions.
More and more we’re seeing both progressive tech startups and enterprise companies alike seek to bring design thinking to every corner of their business. We predict this trend isn’t going anywhere.
You wouldn’t always know it to look at, say, the news, but empathy is booming.
You can’t have design thinking, human centered design, or UX research without empathy. Empathy is often confused with sympathy, so let’s separate those. Sympathy is about caring, about feeling, about compassion for others. It’s probably a really good quality for most people most of the time, but it’s not necessarily critical to building great products or businesses. Empathy, by contrast, is simply about understanding the contexts, motivations, and truths of people’s actual lives by imagining they were your own.
The growth of empathy in the context of product design and business philosophy has been huge. If I can understand my user, I can build something that will improve their lives, solve their problems, and make me money. Much of UX research is about using various methods and tools to uncover this understanding of users. Why do they do what they do? Who are they, actually? Qualitative research is critical here, as is asking “why” when evaluating quantitative data sets.
The very act of empathy requires imagination, and flexing those creative muscles is like ongoing conditioning for the designer to build innovative products.
Information architecture is all about organizing content. Search, navigation, labels, structures and systems can all have a place in your site or app’s IA.
A good IA considers users, context, and the content itself. For instance, how might a tree novice, vs a certified arborist go about identifying some leaf damage that impacted a tree they had come across? What if they are on their smartphone with a camera and WIFI vs desktop without a camera? Do they have your app downloaded or are they accessing this information via your website? Do you have a hotline perhaps? How is that phone tree menu working out for your users? These are just a few of the things you might consider for one job to be done: figure out what’s wrong with my tree leaf.
UX researchers employ a variety of methods to answer IA questions. Tree testing and card sorting are two popular methods to help discover and validate systems to organize content. In tree testing participants try to find information within a hierarchy of content (trees with branches) you share with them. In a card sort, they organize topics into groups. Generally a card sort would be run first, with a tree test to help validate the findings of a card sort.
IA is a complex and multidisciplinary field within UX that might bring together designers, developers, product managers, and marketers to ultimately build the right content organization systems to benefit the user and the business in all key contexts.
Mental models are a useful tool in UX research when it comes to describing and understanding how a user thinks. (All roads lead to empathy). Mental models are ways we describe how people think about the world. This could be at a very very high level, or a very granular level. Books like Thinking, Fast and Slow or The Undoing Project consider the role of cognitive biases in how we make decisions.
Regardless of the why of a mental model, defining them can be very useful for product design. For example, imagine we’ve built a site navigation for a pet store around different types of animals (cats, dogs) and different categories of need (food, medicine). Does bringing these systems together into one menu fit with a user’s mental model, or confuse them? Does wildly reimagining a checkout experience introduce friction by challenging familiar patterns or mental models of doing things? Does your product experience fit with or challenge your user’s understanding of the world?
Research can be a great way to uncover what some of those views are in the context of using your product, which can be invaluable in building a product that works with, and doesn’t fight against, how they believe things work.
Your participant panel is the group of people you could potentially call upon for research. At User Interviews we have a panel of over 75,000 participants we connect with researchers based on demographic criteria, occupation, and custom screener survey results. You may also have a panel of your own users, or more specialized panels for different types of research. However you source participants or define your panels, they’re an incredibly important part of user research. You cannot run good research with bad participants.
Long the ugly stepsister of quantitative research, qualitative research has become an integral part to user research, with the goal of building products people want and that make businesses successful. Qualitative research aims to answer questions of why and address context. Qualitative methods focus on building understanding through inquiry, dialogue, and observation in real life scenarios or lab settings.
Popular methods of qualitative research include interviews, field research, and remote or in-person usability tests. A great advantage of qualitative testing is that it can often yield insights quickly and inexpensively. Simply talking to five or so people can seriously save you from building a fundamentally wrong product, validate you’re on the right track, or help you make tweaks to improve your product’s performance and save you tons of time and heartache.
Our collective obsession with data often points us here. This is where we get numbers, lots and lots of numbers. When numbers yield insights and action, they are great. Researchers may run large surveys in the discovery stage to better understand a market, a/b tests on prototypes to better understand which version will perform best, or closely monitor customer support tickets and web analytics in a post-launch phase to see how a product is performing in the wild. When looking at large data sets, anomalies are particularly important, as well as benchmarking against past or anticipated results.
Quantitative and qualitative research work wonderfully together and most established research programs take advantage of both.
How easy is my product to use? How quickly, efficiently, joyfully can my users complete certain tasks in certain contexts? Usability is the aspect of UX and UX research that seeks to answer and address these questions.
Qualitative usability testing is perhaps the most valuable research a product team can do, giving tangible insights into the effectiveness of a product while also providing the context as to why these findings are true, making them actionable.