Qualitative versus quantitative research — which is optimal?

Qualitative and quantitative research generate different but equally valuable insights, depending on the research subject and research question.

In this article, we’ll pick apart the two categories of research by answering the following questions:

• What’s the difference between qualitative and quantitative research?

• How do you decide which to use?

• Which will deliver the most insights and value?

• What are the benefits and drawbacks of each?

• Which incentives are most appropriate for either type of research?

We often hear discussions about picking the right method to match your research goals and questions, and a part of that consideration is what kind of data to collect.

It’s important to know that no data type is inherently more or less valuable. However, it is important to use data in the right context.

Table of contents

• What is qualitative research?

• What is quantitative research?

• What's the difference between qualitative and quantitative research?

• Qualitative vs quantitative survey questions

• Which incentives are most appropriate for either type of research?

What is qualitative research?

Qualitative data is just about anything you can capture that can’t be represented by a hard number, such as a user’s impression of a brand or a description of where they expected to find something in the user interface.

There isn’t necessarily a way to express this information numerically.

Qualitative research uses open-ended questions to explore thoughts and concepts through language. Encouraging a vibrant discussion is important to getting respondents to share their genuine thoughts and opinions.

Because this type of research involves gathering opinions, the research moderator might delve into an unscripted line of questioning (dependent upon how the participants answer). The subjective nature of questioning is a hallmark of qualitative research.

3 types of qualitative research methods

There are many ways to conduct qualitative research. Popular data gathering methods include:

1. One-on-one interviews — held in-person, by video or over the phone

2. Focus groups — typically held in-person to elicit group conversation on key topics

3. Surveys — featuring open-ended questions encouraging written, narrative responses

Side note: Likert scales can be a type of qualitative research, even though they offer a predetermined list of answers to choose from on a scale — ranging from “very bad” to “excellent,” for example. In this case, the wording is open for interpretation by the individual, because “very good” can mean something different to everyone. Therefore, it's subjective and not objective.

3 qualitative research benefits

Qualitative research asks participants for feedback and experiences in their own words, which has a few benefits:

1. You can gain more colorful insights into participant attitudes, thoughts, feelings, and behaviors

2. You can uncover emerging trends or insights that were otherwise unknown

3. Hearing various opinions allows you to evolve and adapt your research questions and hypotheses in subsequent interviews or surveys, which could strengthen your quantitative research strategy

How to analyze qualitative data

Given its subjective nature, a researcher must sift through individual responses manually to identify:

• Repeating words or phrases

• Themes and patterns

• Trends

• Consensus opinions

• Outlier opinions

Qualitative data usage and limitations

Qualitative data sometimes gets a bad rap, because it can be messy and hard to interpret.

Qualitative data often comes in the form of quotes, notes from interviews, video clips of users, or other observations.

Try to find ways to standardize your collection methods. For example, use the same note-taking system across a whole set of focus groups.

Be sure to use more than one lens to look at your results. For instance, if you ran interviews, it’s important to review notes, listen to recordings, and watch videos.

You might pick up different nuances from the different ways you process the same information in different formats.

Qualitative data can also be easily misunderstood, either because of poor analysis or because of biases.

People don’t mean to misinterpret data, but every single one of us comes from a certain set of understanding that can sway our points of view or prevent us from seeing a pattern.

Knowing and naming the potential biases can be helpful. Ensure your team follows thorough analysis and synthesis processes that includes several members of your team. 

Researchers generally use smaller sample sizes for qualitative studies compared to quantitative studies.

While you can’t make generalizations based on small amounts of feedback, it does not mean that the findings are unimportant.

Finally, qualitative research is often collected by asking people for their input or collecting their attitudes, rather than watching their behavior.

It’s well-known in the UX world that there is often a mismatch between what people do and what they say, whether because they’re worried about being too negative or just are terrible at predicting their future behavior. 

Again, this doesn’t mean that it’s not useful to collect, but it’s important to know that you can’t just ask participants what they want and rely on that response.

You’ll need to triangulate by understanding their core needs and context, evaluating how well their current systems are working, and uncovering opportunities to better serve them.

What is quantitative research?

Quantitative data is anything that you collect that represents numeric information or can be counted. It is an objective measurement that is not based on any opinion or interpretation. 

For instance, you can count the number of clicks someone makes on a screen or calculate the percentage of site visitors who ultimately make a purchase.

Assuming your collection methods are sound, quantitative data should give you a precise measurement. 

When you hear people refer to “quantitative research,” it usually means that the kind of data being collected are these hard, numerical pieces of information. 

It requires a larger number of responses than qualitative data to get a more reliable result. Unlike its counterpart, quantitative research involves forming a set of specific research questions that all respondents answer.

3 types of quantitative research methods

1. Closed-ended question surveys

A close-ended question is one that provides a set of possible answers. For example:

• Yes or no

• A, B, C or D

• Select all that apply

• On a scale of 1 to 10

These types of surveys are easy to scale and measure. Online surveys are the easiest and least time-consuming to set up and send out, though you can arrange in-store paper, telephone and mail surveys, too.

2. Polls

Polls are quick and efficient ways to get limited data on a specific topic. You can create polls on various online platforms, which then get shared via social media or a segmented email list.  

3. Observing data

Observing data helps you gather quantitative information in scenarios where you need metrics like:

• Quantity

• Frequency

• Duration

For example, websites often track and observe the number of visitors or page views over different time intervals. Observations can be more time-consuming than simply collecting survey data.

4 benefits of quantitative research

Quantitative research has a few inherent benefits:

1. Identically structured data (across participants) is easier to measure and draw conclusions from. Many automated survey platforms can filter information for you.

2. It produces objective, non-biased results (assuming research was conducted on a representative sample of the population)

3. Quantitative research is less time consuming and easier to scale than qualitative research.

How to analyze quantitative data

Statistical data analysis is the most popular way to process numerical data. It allows you to compare your results to find many key metrics, including:

• Averages

• Percentages

• Highest and lowest values

• Correlation

• Future projections

Specifically:

• Gap analysis compares your collected results with your desired numerical goals — to find out which areas need improvement.

• Trend analysis compares results over time to identify trends and changes.

Quantitative data: usage and limitations

Quantitative data is usually used to look at trends and answer questions like how much, how many, how often?

Anytime you want to make a count of something or get a sense of scale, you’ll need to include quantitative data. 

Many people view quantitative data as the most trustworthy because it feels unbiased - as long as you do the math right, you have a precise, unambiguous number. 

However, it’s really important to make sure you’re measuring the right things and putting those measurements in context to make decisions.

For instance, you could measure the average length of time each visitor spends on a particular page of your website. That length of time, of course, is easy to calculate and unambiguous.

But whether any particular amount of time on a page is good or bad depends on a lot of factors.

For instance, are users spending a long time on a page because you have a lot of content they’re engaging with?

Or are they getting stuck because they're looking around for what they want for a long time? Or are they navigating to the page and then moving on to another task but leaving the page open? 

It’s also important to note that while you can calculate anything with numbers, having numerical data isn’t the same thing as having statistical significance.

It can be easy to misinterpret quantitative data, especially if you’re working with too small of a set.

For example, if you run a usability test and 3 out of 5 users fail a task, that doesn’t necessarily mean that 60% of all users will fail.

It just means that 60% of the users you included in the test failed.

That probably still means you want to address the issue, but be careful about trying to apply significance just because you have numbers.

If you truly are looking to quantify trends, you’re going to need to be sure to include a large enough sample size to make generalizations for the population you’re studying.

What’s the difference between qualitative and quantitative research?

The difference between qualitative and quantitative research is the type of information you’re hoping to gather and how you’d like to analyze that information. Qualitative research focuses on understanding:

• Behaviors

• Opinions

• Ideas

These can be instrumental in developing products and services. Numbers only tell us so much. According to QRCA, a community of qualitative research professionals, qualitative research also reveals how customers may feel about your:

• Marketing messages

• Customer service

• What influences certain behaviors  

Quantitative research is about drawing facts that you can measure numerically. Hard figures help you:

• Show exactly what works and what doesn't (without guesswork)

• Make tactical and strategic decisions

• Guide business strategies and goals

Surveys conducted regularly over time can show you trends and changing data, too.

Mixed method approach

You don't have to stick with one kind of research. According to a 2017 study by University of Alabama at Birmingham, using qualitative and quantitative research together can yield powerful results that wouldn’t be possible on their own.

This is a mixed-method or hybrid style of research.

Explanatory sequential research focuses on gathering numerical data. Then you follow up with qualitative questions to validate the reasoning behind the respondent’s choices. Exploratory sequential research is the inverse of explanatory. You gather experiential data and then back up your findings after with quantitative data analysis.  

Qualitative vs quantitative survey questions

Both kinds of research can use surveys to obtain useful feedback. Here, we’ll define the differences between the questions asked in qualitative and quantitative research to get the best results.

Qualitative survey question examples

To obtain meaningful information in a qualitative survey, open-ended questions are a must. Avoid questions with “yes” or “no” answers. Focus on:

• Who

• What

• When

• Where

• Why

• How ‍

Pro tip: If you’re conducting an interview and accidentally ask a yes/no question, there’s a simple solution: Ask “Why do you feel that way?”

When interviewing individuals or groups:

• Make participants feel comfortable by first asking easy questions or for light-hearted information about themselves

• Transition into more challenging questions that ask about their sentiment on a specific aspect or feature of the main topic

• Then ask your most specific questions

• Always end interviews by asking some version of this question: “What did I not ask about that we should be thinking about?”

Interviews conducted in person or on video call often yield the best results, because you can observe body language. Interviews can work well over the phone. Questions answered in writing or over email are the least effective because they require more effort from the participant to write out their thoughts.

Pro tip: When asking participants to write answers to open ended responses, ask your most important questions first. They’re more likely to get fatigued the more questions you ask.

A line of questioning in a focus group interview about the fictional breakfast cereal, Fiber O’s, might look like this:

• Tell me about yourself and your first memory of eating Fiber O’s.

• What can you tell me about the taste of Fiber O’s?

• How does eating a bowl of Fiber O’s make you feel?

• What do you dislike about Fiber O’s?

• Would you recommend Fiber O’s to your friends? Why or why?

• What have we not discussed regarding Fiber O’s that we should be thinking about?

Quantitative survey question examples

This research focuses on data and statistics, which means closed questions are ideal. Finalize your questions prior to conducting research — so every respondent provides data on the same questions. Examples of quantitative questions are:

1. On a scale of 1 to 10, how satisfied are you with the technical support you received at XYZ brand?

2. Why did you decide to cancel your membership?

a) Too expensive

b) Not enough features

c) Wasn't happy with the support

d) Didn't use it enough

3. How often do you visit XYZ brand's store in person?

a) Daily

b) Several times a week

c) Several times a month

d) Less than once a month

Is a survey a quantitative or qualitative research method?

You can successfully use both open-ended and closed questions in surveys. A solid approach begins with qualitative research methods to establish your initial strategy, then use your findings to get numerical data to provide measurable results.

Some number-driven surveys have open questions to ask why the respondent picked their answer, or to ask for feedback on anything they didn't ask in the set questions. This helps pick up useful feedback and reasoning.

Which incentives are most appropriate for either type of research?

By this point, you should have some idea of what type of research you want to conduct:

• Quantitative research

• Qualitative research

• Mixed methodology

Now you need to get people to take part in the research. Enter: incentive programs.

Incentives are a simple, effective way to maximize research participation. But which incentives do you select for the type of research you’re conducting?

The value needs to reflect the work the participant puts in. Here’s a couple rules of thumb:

• For easier tasks like quick multiple-choice surveys, your incentive will likely be lower value.

• A more in-depth kind of research like a video interview or focus group should be rewarded with a higher value incentive.

You can offer various types of rewards like:

• Cash

• Gift cards

• Prepaid Visa® cards

• Non-monetary, tangible gifts

Want an exact number? Our research incentive calculator will tell you exactly how much to pay research participants based on a number of factors, including study type.

Key takeaways

Both qualitative and quantitative research serve up valuable data in different ways.

• Quantitative data represents numbers or counts but doesn’t inherently represent any context of a situation

• Qualitative data represents non-numerical information like preferences or perceptions, and helps us dig into why things are happening but need to be synthesized carefully

• Quantitative calculations can be powerful to understand trends and scope, but be careful not to imply statistical significance just because you have numbers

• To be most successful, set clear research objectives and match your method and data types that way

The end result is a strong research strategy that gives you the data you need to achieve your goals.

Regardless of the type of research you conduct, you should incentivize your research participants to maximize participation rates. Tremendous makes it simple. Sign up and send your first reward in minutes, or chat with our team.