This video introduces one of the key distinctions in types of research, between quantitative and qualitative data. Quantitative data is any that represents numerical data, such as percentage of visitors, and is great at predicting or describing trends. Qualitative data is any that represents non-numeric data, such as emotional responses, and is much better at describing why things are happening.
- Once you've decided that you need to incorporate UX research, you need to decide the proper approach for your project and your team. There are several types of research methods that UX professionals call on, depending on the type of question you're trying to answer. There's no one right or wrong approach, but in order to select the most appropriate method, it can be helpful to understand the major categorizations of research. The first distinction is quantitative versus qualitative research. Quantitative research is that which produces data that represents numeric information, such as the number of clicks on a certain area, or the percentage of site visitors that fill out a form.
Quantitative data is not based on opinion, and serves as an objective input to decision making. Quantitative research is best at capturing the trends of what is happening, because you normally collect a large amount of information. You may even be able to get statistically relevant data. For instance, you might calculate the percentage of support complaints that are about a particular feature, or perform an A/B test where you see which of two versions of a button gets more clicks. Other examples of quantitative research are card sorts, surveys, click tests, and eye tracking studies.
On the other hand, qualitative research produces data that can't be expressed by numbers, such as emotional responses or first impressions. Qualitative research is often used to help uncover why certain trends are happening. Qualitative research is normally done on a much smaller scale, because you need to hear directly from people. You don't always have to be sitting next to them talking, but you do need to be able to have them express their thoughts directly, whether in text or verbally. Examples of qualitative research are usability tests, focus groups, interviews, diary studies, and participatory design workshops.
For instance, let's say that you've designed two different versions of a signup form, and you want to figure out which one to go with. To understand which performs better, you'd want to use a quantitative method, like A/B testing, to monitor how many clicks you're getting on each one. Then, you'd want to perform qualitative research, like an in-person usability test, to find out why customers prefer one over the other. You might also try to collect both quantitative and qualitative information in one research set, such as by performing a set of interviews where you ask both open-ended questions and specific quantitative questions, such as how many times a week participants performed a particular task.
Both types of information are helpful, but you just need to be aware that you can misinterpret quantitative data if you're working with a very small set. Both quantitative and qualitative research are very helpful, but they're used for different purposes.
This course introduces the fundamentals of user experience research so that anyone can understand the benefits and start integrating research into their everyday design and development process. Start watching to learn how to use UX research to find the answers to the most basic questions about your customers—who, what, when, why, and how—and drive better user experiences and business outcomes.
- An overview of research methods, including usability testing, interviewing, eye tracking, surveys, and many more
- A review of the main types of research, including quantitative and qualitative, behavioral and attitudinal, and moderated vs. unmoderated
- Determining the right methodologies based on organizational environment, client type, and project stage
- Targeting the right research participants
- Crafting the right questions in the right way
- Analyzing and presenting your data