This is a brief summary of the types of research we undertake when we conduct user research. The type we choose, depends on the user research questions we are asking and what we hope to learn.
Attitudinal research (what people say)
Attitudinal research is about learning about people's attitudes from their stated beliefs. For example, we can use a survey to measure and categorize attitudes. This can help us discover issues our users experience so we can address them.
Behavioural research (what people do)
Behavioural research is about observing human behaviour. In other words - what people do. What people say and what people do aren't always the same. For example, they might say they like a feature on a website, but then they might never use it. Or they use it and it doesn't work the way they expected.
To get the best understanding of users, we often combine attitudinal and behavioural research. For example, usability testing is one of the main user research techniques we use. We watch people interact with a service and they share their observations first hand. If they do something, or don't do something we follow up with questions.. This helps clarify why participants behaved the way they did.
Qualitative user research generates data about behaviour and attitudes. We observe a person behave or hear directly from them. This works the best for answering questions about "why" or "how" to address an issue.
The usability testing example above describes qualitative research. We observe how people use a service to meet their needs. We look for opportunities to clarify behaviour and ask questions to follow up. The idea is to get a better understanding of why people take, or do not take specific actions.
Analysis of qualitative research data is not mathematical.
Quantitative research also generates data about behaviour and attitudes. In this case we gather the data indirectly though analytics and surveys. This type of research is great for answering questions like "how many" and "how much." It is useful for prioritization because you can focus on addressing the issues that will impact the greatest number of users.
When we start a quantitative research project, we know what sort of data we want to collect. For example:
- how long it takes a person to complete a task;
- how often people are successful at task completion; or
- whether a person uses a specific feature.
Our insights into behaviour and attitudes come from mathematical analysis.