The idea behind UX design is to prioritize the user experience, to consciously design in a way that evokes the kind of emotions and attitudes we want our customer to have.
satisfactory . In other words, we have a cognitive bias to find appeal in things that please us or that reduce suffering.
We don't like difficult choices in our daily lives, so unless we are motivated by challenges (like those in a game), we tend to opt for whatever makes our lives easier and then retroactively attribute positive attributes to them. they. justify our selection.
The evolution of operating systems is a great example. With each iteration, both Windows and iOS become leaner, simplifying the experience of using a computer. The “inner workings” of the system are hidden behind a user-friendly interface and automated solutions.
This is why User Experience has become synonymous with ease of use, accessibility, simplicity, directness and noise reduction, as it weighs heavily in the human decision-making process. The question then is: 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 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 for scientists throughout the 20th century.
Many designers act based on intuition and trial and error, they design expecting a response from people and then adapt depending on the user's reaction. This type of approach has 2 problems:
People don't like change and are reactionary. Therefore, first impressions can be misleading when collecting feedback after implementing a change. We need to wait for the dust to settle to see if users adapted to the change or if they didn't like it at all.
On the other hand, going back on your design choice can be costly in terms of time and investment. This leaves the designer in an unfortunate situation: he has to move forward or backward and incur additional costs.
Ingenuity and experimentation will always be part of the process, but preparation and data collection can help guide the design team. Just as initial interviews help designers get a clear picture of client requirements, 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 type of data collected and the analysis process that follows. The first type is quantitative methods. In this approach, we measure user behavior with numerical indicators to try to infer what they are experiencing.
An example of quantitative methods is research, where we ask the user to rate how they feel about different aspects of our product. This type of approach is called self-report as people are interpreting how they feel and assigning a number.
One of the major limitations of self-reports is that they are subject to cognitive biases. For example, it is known that participants are susceptible to social pressure, the desire to help, the fear of unfair judgment, among other variables, which can distort their responses.
An alternative to self-reporting is direct observation of behavior. A user's fingerprint is a great way to gauge how they feel about a product. You can measure practically everything, from the number of new users, time, number of visits per day and so on, comparing between different designs to see which one shows the best indicators.
A great example of this approach is engagement. Users tend to spend more time on apps and services they enjoy using, so you could develop 2 or 3 different UIs and run a test and measure the amount of time invested per user in each condition.
Qualitative methods
Although quantitative methods are excellent for collecting large amounts of data in a very short time, they are often limited by the depth of information. Yes, we may know that users are spending more time on condition A than condition B, but why?
For these types of questions, we need a methodology that allows us to explore in depth why people feel the way they do. And as philosophers have been telling us for the last two hundred years, feelings and experience are very difficult to understand in mathematical terms.
Instead, you can opt for a qualitative approach. You can collect qualitative data, such as interviews and written (natural language) feedback, to get a more comprehensive view of why people like or dislike certain choices.
The 3 most common qualitative methods are:
Qualitative surveys : where you ask people to fill out a form with their comments and ideas.
Personal interviews: where you sit down with the user and do an interview, asking questions that help them understand why they feel the way they do.
Sample: Similar to in-person interviews, but instead you get a group of people together and have an open conversation. The interviewer, in this case, is a moderator, asking questions that stimulate discussion among users while recording what they say.
While qualitative methods are very useful for getting a better picture of user experience, they have their own set of problems. First, qualitative methods are better suited to smaller samples, as they take longer and the information is more difficult to process.
On the other hand, it is much more difficult to analyze because the process involves our intuition. We sat down, read the transcripts, and discussed how to approach design based on these testimonies.
Qualitative data can be analyzed with quantitative methods such as Natural Language Processing, but the result is quantitative in scope.
An integrated approach
Although these approaches are different, they are not mutually exclusive. In fact, researchers have been mixing quantitative and qualitative approaches for many years, as the result is a more comprehensive understanding of the user than just being limited to scores or testimonials.
UX design is a powerful tool that creates a better user experience, and research methods are a great way to create a roadmap to guide the process.
