When you’re conducting research, your data will fall into two categories: qualitative or quantitative. So what’s the difference between these two data types?

Well, here’s a quick and easy way to remember at least the basic difference: quantitative data deals with quantities of things – numbers and measurable information, like how many people visit a website each day. That’s all about quantity (sounds like quantitative, right?).

On the other hand, qualitative data gives you more insight into what people think, feel, and believe – the quality of a thing, person, or situation. Alright that one’s a bit more of a stretch, but it works.

Now let’s get more into the details of qualitative and quantitative research so you know how to conduct each.

What is Qualitative research?

Qualitative research focuses on the human perspective, and usually answers the question “why?” If you want to learn how people perceive their environment, why they hold certain beliefs, or how they understand their problems, you’ll conduct qualitative research.

It’s also all about context. When you’re researching a group, you want to study them in their natural environment. This gives you insights into their behavior, beliefs, opinions, and so on.

How do you conduct qualitative research?

You can conduct qualitative research in a few different ways. Doing interviews, setting up focus groups, giving people open-ended questionnaires, studying photo collections, and observing people in their daily routines are all forms of qualitative data collection.

When you engage with people in these ways, you’re giving the opportunity to give more in-depth, elaborate responses. They’re not just responding “yes” or “no” – they’re telling you what they think.

You can also make observations from photographs or from watching people – things like the way people are looking at each other lovingly, or how two old people might hold hands while they watch TV.

From these observations, you can theorize that those people love each other, are close to each other, know each other well and are comfortable around each other, and so on. Things that are hard to quantify with numbers or measure with figures.

What is Quantitative research?

Quantitative research, on the other hand, involves collecting facts and figures and often results in numerical, structured data. Think data you can put in a spreadsheet and analyze.

Instead of talking to people and getting their opinions, you’re asking them yes or no questions. Instead of asking someone why they do something, you’re finding out what they do, or how many people do that thing, or how often – and so on.

Real quick - what is structured data?

Let's say you're looking at a recipe on your favorite online cooking blog. The structured data are things like the ingredients, the oven temperature, how many calories a serving has, and how long you cook the food. These are all quantifiable (and measurable with numbers/facts) things.

Unstructured data, on the other hand, would include the food blogger's little story about how they discovered or created the recipe, what people have said about how delicious it is, and how much they love the texture of those soft, gooey cookies. You can't measure these data – they're opinion and experience-based.

How do you conduct quantitative research?

You can conduct quantitative research by looking at statistical data (how many people did x), giving people multiple choice or true/false tests, asking them yes/no questions on a survey, and so on.

All in all, you’re trying to answer the question “what” or “how” – what something is, what’s the number of people who order from Amazon every day, how many cars are in that parking lot.

Because of the nature of the data and collection methods, context isn’t a factor in this type of research.

With quantitative research, you’re interested in gathering data that support and prove or disprove a hypothesis or theory you already have.

So instead of observing and talking to people and then forming a theory about what’s going on, you collect your data, and then make conclusions about the validity of your hypothesis based on that data.

Is Qualitative or Quantitative research better?

Alright, so you have these two methods of research – which is better?

Well, most people would argue that they’re better when used together. They’re complementary. Each has its pros and cons (which we’ll discuss), but each method definitely brings important information to the table.

Before we discuss just how they can work together, let’s look at the good and the bad of each.

Pros and Cons of Qualitative research

Let's start with the good. Qualitative research lets you dig deeper into a problem, situation, or context and see why things are happening. You get personal insights from your subjects that can't necessarily come from numbers and figures.

You also have the benefit of context, which can shed light on why a person said certain things or was feeling a certain way (for example if they live in a war zone or in a small village in the middle of nowhere or in the largest city in the world).

On the other hand, qualitative research is more time-consuming and therefore expensive. It takes a lot more time to interview people or set up focus groups than it does to send someone a simple yes/no survey.

It can also be harder to get people to participate in qualitative research. They might not have the time or energy (or desire) to share extensively.

Finally, qualitative research is never really definitive. People are always changing, as are their perceptions of the world around them. So while qualitative data can help inform your hypothesis and fill in gaps in your research, it should usually be supported by quantitative data.

Pros and Cons of Quantitative research

Quantitative research produces hard facts, numbers, and other measurable things. Which can be very useful when you're trying to prove a theory or understand what you're dealing with.

It's also independent of changeable things, like researcher bias or people's current opinions or moods. So qualitative research is repeatable and can be tested and re-tested again and again.

And, practically speaking, quantitative data analysis can be performed much more quickly than qualitative research. You can simply send someone a survey, collect the response data, and dump that data into a spreadsheet or database. From there, running various queries and analyses is easy (assuming you know what you want to ask).

Still, quantitative research is limiting in certain ways. People can't explain their answers to a multiple choice test or yes/no survey (again, lack of context). This means you can't take human factors into account.

So while you have the facts and numbers, you have to decide how to interpret them and use them in your research. (This can be both good and bad.)

How to use Qualitative and Quantitative research together

Sometimes it’s best to start with qualitative research – gather information, talk to people, try to understand their problems/perceptions/opinions, then form a hypothesis.

Then, once you have your hypothesis, use quantitative methods to confirm (or disprove) it with data analysis. This will show you whether the issue/problem/situation exists in general, or was just part of someone’s perception.

But qualitative research/insights can also help round out your structured data/conclusions – if you’ve learned that x people use your site every day, quotes from people about why they use it (as opposed to another company) can teach you more about what’s working (or not) and why.

Examples of Qualitative and Quantitative research

First example

Say you want to learn more about people who visit Paris on vacation. You could look at flight data, museum admission numbers, tourist info to figure out how many people visit Paris each year. But that won’t tell you why they’re visiting.

To learn why, you have to ask people why they wanted to visit Paris, what was their favorite part of the city, what was their experience like as a tourist in Paris, and so on. This will give you insights into what motivates people to travel there in the first place.

Another example

Let’s say you run an e-commerce site that helps people resell their gently used clothing.

You can gather information about how many people sell clothes on your site, how many items the average person has sold, how many people visit the site to buy those clothes, and so on. All that’s right there in the analytics.

But if you want to know why people choose to use your site – either to sell or buy clothes – you’d want to start by conducting an open-ended questionnaire or ask for feedback on a survey.

Also, if you want to know what they like about your site, and how that influences their decision to use it, you could ask them to describe their experience using the site, and so on.

Ultimately, you’ll want to use both qualitative and quantitative research to get the whole picture. And you won’t just use one, and then just use the other. You can go back and forth between the two methods as your research evolves and you gather more information.

This will help you get a more complete picture, form a stronger and deeper hypothesis, and establish both facts about and insights into the situation.