Quantitative and qualitative research are complementary methods that you can combine in your surveys to get results that are both wide-reaching and deep.
Simply put, quantitative data gets 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 data is designed to collect cold, hard facts. Numbers. Quantitative data is structured and statistical. It provides support when you need to draw general conclusions from your research.
Qualitative data collects information that seeks to describe a topic more than measure it. Think of impressions, opinions, and views. A qualitative survey is less structured: It seeks to delve deep into the topic at hand to gain information about people’s motivations, thinking, and attitudes. While this brings depth of understanding to your research questions, it also makes the results harder to analyze.
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.
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 say 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 also may 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 to add quantitative questions about these topics after the next conference.
For example, let’s say several attendees said that their least favorite 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 recognizing 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 it will provide you with consistent data that is easy to analyze.
There are many methods you can use to conduct qualitative research that will get 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 analyzing the results is hard because people will use different words and phrases to describe their points of view, and 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.
How long have you been a customer of our company?
How likely are you to purchase any of our products again?
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.
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