Take a horror game, for example. The developers want the user to feel fear, and the user is open to the experience (that’s why they acquired the product). With that in mind, the developer can create a confusing interface, provide vague information, use poor lighting, and other techniques to psychologically push the user into a state of stress and anxiety
Having said that, if the game menu is cumbersome to use, has performance issues, or bugs that destroy the illusion of the world, the user may instead experience anger and frustration, which is not quite what the developer intended. That’s what Horman points to: user-centered design is about aligning our intentions with the user’s experience via our product.
What do people want?
The horror game example is a corner case phone number list at best. As Steven Krug puts it in his book Don’t Make Me Think, users are prone to satisficing. In other words, we have a cognitive bias to find appeal in the things that please us or that reduce suffering.
We don’t like difficult choices in our day-to-day routine, so, unless we are motivated by challenges (like those in a game) we tend to go for whatever makes our life easier, and then we retroactively assign positive attributes to justify our selection.
The evolution of operating systems is a great example. With each iteration both Windows and iOS have become leaner, simplifying the experience of using a computer. The “inner workings” of the system are hidden behind a friendly UI and automated solutions.
That’s why UX has become synonymous with ease of use, accessibility, simplicity, directness, and noise reduction since it weighs so much on the decision-making process of human beings. The question is then, how do we know which design choices bring us closer to those goals?
How do we know what people feel?
While we may have a general idea of all of those 3 steps of the cv process require what people want to feel, how they react to a stimulus is another matter entirely. Trying to measure people’s behaviors and attitudes has been a constant struggle of scientists throughout the 20th century.
Many designers act on intuition and trial and error, they design expecting a response from people and then adapt depending on the user’s reaction. This kind of approach has 2 problems:
People don’t like change and are reactionary. As such, first impressions can be misleading when gathering feedback after implementing a change. You have to wait until the dust settles to see if the users adapted to the change, or if they didn’t like it at all.
On the other hand, going back on a design choice can be costly in terms of time and investment. This leaves the designer in an unfortunate place: they either have to push forward or backtrack and incur further costs.
Ingenuity and trial will always be a part of the process, but preparation and data gathering can help guide the design team. Much like how initial interviews help the designers get a clear picture of the requirements from the client, UX research methods can help them understand the best approach to UX design.
Quantitative methods
In general, we can divide UX research methods into 2 broad categories depending on the kind of data gathered and the analysis process that comes after. The first kind is quantitative methods. In this approach, we measure user behavior with numeric indicators to try to infer what they are experiencing.
An example of quantitative methods gambling data is the survey, where we ask the user to score how they feel about different aspects of our product. This kind of approach is called self-report since people are interpreting how they feel and assigning a number.
One of the big limitations of self-reports is that they are liable to cognitive bias. For example, it’s a well-known fact that participants are susceptible to social pressure, the desire to help, the fear of judging unfairly, among other variables, which can skew their responses.