Every successful business has one thing in common: they know their market. After all, without a strong consumer base and demand for products and services, a business won’t last long in a highly competitive, ever-changing market.

But how do advertisers and product developers know what their consumers want? It all begins with market research, which yields two types of data – qualitative and quantitative.

Qualitative research is a methodology that collects non-numerical data with the goal of gaining insights into opinions, biases, motivations, decision-making processes, perceptions, and attitudes. This type of data explores human behavior and delves into the most basic research question: “Why?”

Most qualitative research involves open-ended surveys, focus groups, or interviews conducted in a natural setting without any manipulated experiments or control groups.

However, in the wake of the COVID-19 pandemic, face-to-face interviews and focus groups have shifted to digital communication. Western countries have already adapted to conducting 90% of their research online as more people turn to Zoom and online surveys to collect information.

Quantitative research is a scientific method of collecting numerical data to measure variables in the form of numbers or statistics.

For example, a survey might conclude that 356 respondents out of a total of 500 (71.2%) were in favor of a new product feature. These numbers are concrete, and they allow marketers to draw general conclusions, predict outcomes, and report their findings with compelling evidence that shows a clear majority ruling among survey participants.

The words are similar and easy to mix up, but an easy way to remember the difference between the two types of data is with a word trick – “quantitative” has a t, like “quantity.” When we think of quantities, we think of numbers.

“Qualitative” measures the “quality” rather than the numerical value. For example, if we’re studying a group of dogs, we can use both types of data in our observations. Any notes about the dogs’ qualities such as appearance, size, demeanor, et cetera would be qualitative. However, once we assign a numerical value, such as the number of dogs that have black fur, then it becomes quantitative.

Let’s explore these two types of data further:

When researchers collect qualitative data, they’re seeking to add extra details and include a human element to their survey results. Researchers do not use qualitative data for statistical analysis. Remember that qualitative research primarily addresses the question “Why?”

Quantitative data may tell researchers that 75% of their respondents preferred one product design over another, but the qualitative data helps them understand why that statistic exists.

Types of qualitative data include:

• Observations: Anything you observe through sight, smell, touch, hearing, or taste
• Notes: Written or oral descriptions about qualities or characteristics
• Open-ended surveys: A type of survey that allows respondents to type their own answers and feedback rather than selecting from a predetermined list of choices
• Case studies: In-depth investigations of an individual, group, or event
• Audio recordings: Can apply to recorded interviews, focus groups, or observational studies, or other audio content such as speeches, podcasts, etc.
• Video recordings: May include footage of interviews, studies, or focus groups, but can also extend to online video content like YouTube videos, news reports, films, recorded events, etc.
• Transcriptions: Audio or video recordings translated into written text
• Photographs: Images of research subjects, products, activities, workspace, living space, or other relevant still images

Quantitative research tells us how many, how much, or how often. Researchers collect this data through measuring and counting. Because of its fixed nature, researchers rely on quantitative data for conclusive statistical results.

The most common ways to collect quantitative data for market research are probability sampling, analytical tools such as Google Analytics, and questionnaires. Quantitative research has two types of data in statistics: discrete and continuous.

Discrete data is quantitative data that has fixed numerical values incapable of breaking down into smaller parts. An example of discrete data would be the number of children a person has. You can measure whole numbers, but a person wouldn’t have 2.6 children. Typically, researchers use pie charts, bar charts, or tally charts to graph discrete data.

Continuous data is quantitative data that can fluctuate or divide into infinitely smaller parts. An example of continuous data would be taking measurements. An object measured in centimeters isn’t constrained to a whole number – the measurement could be divided into as many decimals as needed for an accurate reading. A line graph is the most common way to display continuous data.

Types of quantitative data include:

• Revenue
• Distance
• Number of items or occurrences
• Height
• Weight
• Length
• Volume
• Age
• Percentage
• Probability

To put it simply, if you can assign a numerical value to an aspect of your study, it’s quantitative data. When measuring this type of data, researchers should use a uniform unit of measurement. For example, if you’re measuring annual revenue, use the same type of currency for all values in the study.

An average business spends between 25% and 50% of its annual marketing budget on research-related activities. Quantitative and qualitative data both provide valuable insights, and they don’t conflict with each other. Using both types of data provides a more complete picture.

In most cases, qualitative research is an ideal starting and ending point. This type of data helps to uncover new challenges and opportunities so you know what problems demand your attention. Then, use quantitative research to provide concrete measurements and fixed statistical data. Following up with another round of qualitative research sheds light on the final impact, especially if your research focused on variables you changed in response to the initial data.

The best way to combine qualitative and quantitative data on surveys is to include both multiple-choice and open-ended questions. Multiple-choice questions generate fixed, structured results while limiting a respondent’s choices to a set number of options.

For example, after you conclude a seminar, perhaps you send out a survey to gauge participant feedback. Asking closed-ended questions like “Did you enjoy the seminar?” will provide numerical data so you know exactly how many people left with a favorable impression compared to those who did not, giving you a quantitative overview to determine if the seminar was a success.

But what made the seminar a success or failure? What steps can you take to improve the next seminar for a more favorable response? If your survey doesn’t include qualitative feedback opportunities, you may never know what circumstances prompted respondents to answer the way that they did.

Following with open-ended questions like “What did you like most?” or “How could we improve your experience?” adds insightful clarification that will help you adjust your approach for the next seminar. If most people enjoyed the topics but felt that the location was poor, you can adapt your strategy by choosing a new venue next time.

Using both qualitative and quantitative data in your research efforts allows you to see both the “how much” and the “why,” of an issue. They’re two sides of the same coin, each offering unique insights that help you understand how consumers are using and perceiving your products or services.

Surveys continue to be one of the most effective types of primary data that deliver feedback directly from consumers. CheckMarket is a world leader with users in more than 150 countries.

We designed our easy-to-use software to handle whatever type of data collection your business requires, whether it’s a basic follow-up survey or a sophisticated research campaign with advanced logic, scoring, and customized branding. Our survey templates can accommodate quantitative data, qualitative data, and hybridized models. CheckMarket is the quickest and easiest way to unlock the valuable insights you need.

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