Discover the differences between qualitative and quantitative data and discover how SurveyMonkey can help you create surveys and analyse results.
Quantitative and qualitative research are complementary methods that you can combine in your surveys to obtain results that are both wide-reaching and deep.
Simply put, quantitative data gives you the numbers to prove the broad general points of your research. Qualitative data brings you the details and the depth to understand their full implications.
To get the best results from these methods in your surveys, it’s important that you understand the differences between them. Let’s have a look.
Quantitative research methods are designed to collect numerical data that can be used to measure variables. Quantitative data is structured and statistical; its results are objective and conclusive. It uses a grounded theory method relying on data collection that is systematically analysed. Quantitative research is a methodology that provides support when you need to draw general conclusions from your research and predict outcomes.
Surveys are a great tool for quantitative research as they are cost-effective, flexible and allow for researchers to collect data from a very large sample size.
Qualitative research is a methodology designed to collect non-numerical data to gain insights. It is non-statistical and unstructured or semi-structured. It relies on data collected based on a research design that answers the question “Why?”
Qualitative data collects information that seeks to describe a topic more than measure it. This type of research measures opinions, views and attributes vs. hard numbers that would be presented in a graph or a chart.
Qualitative research methods usually involve first-hand observation, such as interviews or focus groups. This is market research that is usually conducted in natural settings, meaning that researchers study things as they are without manipulation; there are no experiments and control groups.
Qualitative researchers seek to delve deep into the topic in hand to gain information about people’s motivations, thinking and attitudes. Although qualitative approaches bring depth of understanding to your research questions, they can make the results harder to analyse.
Quantitative data can help you see the big picture. Qualitative data adds the details and can also give a human voice to your survey results.
Let’s see how to use each method in a research project.
Launch a quantitative research study with our online panel and reach a sample audience that matches your needs.
These two research methods don’t conflict with each other. They actually work much better as a team. In a world of Big Data, there’s a wealth of statistics and figures that form the strong foundation on which your decisions can rest. But that foundation is incomplete without the information collected from real people that gives the numbers meaning.
So how do you put these two forms of research together? Qualitative research is almost always the starting point when you seek to discover new problems and opportunities, which will help you do deeper research later. Quantitative data will give you measurements to confirm each problem or opportunity and understand it.
How about an example?
Let’s suppose that you held a conference and wanted feedback from your attendees. You can probably already measure several things with quantitative research, such as attendance rate, overall satisfaction, quality of speakers, value of information given, etc. All these questions can be given in a closed-ended and measurable way.
But you may also want to provide a few open-ended, qualitative research questions to find out what you may have overlooked. You could use questions like:
If you discover any common themes through these qualitative questions, you can decide to research them more in depth, make changes to your next event and make sure you add quantitative questions about these topics after the next conference.
For example, let’s suppose that several attendees said their least favourite thing about the conference was the difficult-to-reach location. Next time, your survey might ask quantitative questions like how satisfied people were with the location or let respondents choose from a list of potential sites they would prefer.
A good way of recognising when you want to switch from one method to the other is to look at your open-ended questions and ask yourself why you are using them.
For example, if you asked: “What do you think of our ice cream prices?”, people would give you feedback in their own words and you will probably get some out-of-the-box answers.
If that’s not what you’re looking for, you should consider using an easily quantifiable response. For example:
Relative to our competitors, do you think our ice cream prices are:
This kind of question will give your survey respondents clarity and, in turn, provide you with consistent data that is easy to analyse.
There are many methods you can use to conduct qualitative research that will give you richly detailed information on your topic of interest.
However, this open-ended method of research does not always lend itself to bringing you the most accurate results to big questions. And analysing the results is hard because people will use different words and phrases to describe their points of view, and they may not even talk about the same things if they find space to roam with their responses.
In some cases, it may be more effective to go ‘full quantitative’ with your questions.
To avoid confusing your respondents, you may want to eschew questions like, “What do you think about our internet service?” Instead, you could ask a closed-ended quantitative question like in the following example.
The internet service is reliable:
Survey respondents don’t always have the patience to reflect on what they are being asked and write long responses that accurately express their views. It’s much faster to choose one of several pre-loaded options in a questionnaire. Using quantitative questions helps you get more questions in your survey and more responses out of it.
Even word responses in closed-ended questionnaires can be assigned numerical values that you can later convert into indicators and graphs. This means that the overall quality of the data is better. Remember that the most accurate data leads you to the best possible decisions.
Our customer satisfaction survey template includes some good examples of how qualitative and quantitative questions can work together to provide you with a complete view of how your business is doing.
How long have you been a customer of our company?
How likely are you to purchase any of our products again?
The following is another example from our employee engagement survey.
When you make a mistake, how often does your supervisor respond constructively?
Now that you know the definition of qualitative and quantitative data and the differences between these two research methods, you can better understand how to use them together. You can put them to work for you in your next project with one of our survey templates written by experts.
We’ve got templates for all types of questions. Check out our library of expert-designed survey templates.
SurveyMonkey can help you choose whether to collect qualitative or quantitative data to get the best results.