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When it comes to understanding human behavior, you may find yourself wondering if your research approach should be qualitative or quantitative. While there are major differences between qualitative and quantitative research methods, it’s important to understand the advantages and disadvantages of each. Because frequently, they complement each other and help highlight different perspectives (or a holistic view) of the same situation.
Qualitative research is a behavioral research method that relies on non-numerical data derived from observations and recordings that approximate and characterize phenomena. In other words, it’s concerned with understanding human behavior from the perspective of the subject.
To do this, qualitative researchers acquire data by studying subjects in their natural environment—focusing on understanding the why and how of human behavior in the given situation. It’s especially effective in obtaining information about values, opinions, and behaviors during particular situations.
There are three common qualitative research methods:
Each method is unique and particularly suited for obtaining a specific type of data.
Participant observation is best used for collecting data on naturally-occurring behaviors as they happen in their usual contexts.
In-depth interviews are optimal for collecting data on individuals’ personal histories, perspectives, and experiences—particularly when sensitive topics are being explored or follow-up questions are likely necessary.
Focus groups effectively gather information from multiple subjects at once and generate broad overviews of issues or concerns related to the demographics represented.
At UserTesting, we’re able to conduct qualitative research with our platform by collecting data and human insights that reveal people’s behaviors, needs, and opinions. Like the ones we just explained—common qualitative research methods can all be accomplished through moderated or unmoderated testing.
Our customers often:
Quantitative research is the process of collecting and analyzing numerical data. It aims to find patterns and averages, make predictions, test causal relationships, and generalize results to broader populations through the representation of data expressed as numbers.
The thing to remember is that quantitative research is unlike qualitative research in one key aspect—it relies on numerical data.
Quantitative data helps you see the big picture—generally in the form of trends and patterns. On the other hand, qualitative data adds color and context, giving a human perspective to the numbers.
The two types of research don’t conflict with each other. They actually work much better together. In a world where data is collected everywhere and with almost everything, there’s a wealth of cold hard numbers that can form the strong foundation from which you can base decisions. However, that foundation is incomplete without human insight collected from real people to give those numbers meaning.
So how do you put these two forms of research together?
Often we spot trends in data. We see what people are doing, but it’s tough to understand why. The numbers are trying to tell us something about trends in behavior, but numbers can’t give you the full story.
When you pair qualitative insights with quantitative data, however, they can tell a richer story.
Let’s say you’re a marketer, and you notice that people are finding one of your landing pages, but they’re not converting. Or you’re a product manager who notices that people aren’t using an entire element of your product that you just launched. Whichever the case, you likely came to these realizations by analyzing your quantitative data. It told you what was happening but not why. This is when you should turn to qualitative research methods to see and hear—from real people—exactly what the issue might be.
Both methods can be helpful on their own, but together, qualitative and quantitative research methods give you an intimate understanding of your customers’ needs, expectations, and pain points.
Discover which qualitative method is most suitable to pair with your quantitative data.
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