Qualitative vs. quantitative research: A simple guide

Quantitative research deals with numbers and statistics, while qualitative research involves pulling information from experiences and stories.

Image is a collage combining visuals of a vintage photo of people with a pie chart.

From Tesla to Tushy, every successful brand is built on a foundation of both quantitative and qualitative research. Marketers and product developers use this zero-party data to frame their advertising strategies, product positioning, and brand voice—basically, everything that goes into designing and selling a product or service.

When it comes to qualitative vs. quantitative research, both methods have their benefits and drawbacks in certain applications. We break down what you need to know before running your next round of market research. 

Qualitative vs. quantitative research: What’s the difference?

Quantitative research counts and measures numbers to find statistical patterns, while qualitative research is a deep dive into understanding people’s thoughts and experiences. They're similar in that they both aim to uncover valuable insights, but they use different tools and approaches to do so.

But don’t be fooled into thinking that one research method is better than the other—both require systematically applied research methods and analysis.

  Qualitative Research Quantitative Research
Goal Understand reasons or trends Quantify or measure data
Sample size Smaller, often nonrepresentative Larger
Analysis Nonstatistical Statistical
Question type Open-ended Close-ended
Response type Personalized Predetermined

What is qualitative research and data?

Qualitative research is like the Sherlock Holmes of the research world—it seeks to uncover the hidden stories, motivations, and intricacies that numbers can't reveal. Instead of crunching data, it dives deep into people's experiences, thoughts, and feelings to help explain certain behaviors and patterns. 

In qualitative research, it's not about numbers but rather words, pictures, and observations. You'll collect rich, unstructured data via interviews, focus group discussions, or open-ended surveys. 

Say you're a marketing rep keen on understanding how people perceive your smartphone brand. 

First, you organize a series of in-depth interviews with smartphone users, asking open-ended questions about their experiences with the brand. Participants share stories about their interactions, likes, dislikes, and emotional connections with the product. You also delve into social media posts, online reviews, and forum discussions to gauge the brand's online reputation.

As you analyze this data, patterns begin to emerge. You find that users consistently describe the brand as "innovative" and "user-friendly." However, you also discover a recurring frustration with battery life and customer support. Qualitative research not only provides you with insights into how people perceive the brand but also dives into the emotional nuances behind their perceptions. Armed with this knowledge, you can fine-tune your advertising campaigns and product improvements to align with your target audience's genuine feelings and experiences.

Pros and cons of qualitative research

Qualitative research is your go-to when you want to explore the human side of data. It's like having a heart-to-heart conversation with your research subjects. Just keep in mind that, like any detective work, it comes with its own quirks and challenges.


  • Deep insights: It's great at uncovering the "whys" and "hows" behind human behavior, providing rich insights that quantitative data can miss.

  • Flexible and exploratory: Qualitative research allows for flexibility, so you can adapt your questions and approach when you face the unexpected.

  • Humanizing data: Unlike numbers, qualitative research humanizes data by bringing stories and personal experiences to the forefront. It's perfect for capturing human nuances and emotions.


  • Subjectivity: Different researchers might draw different conclusions from the same data based on their own personal feelings, experiences, or opinions, so it's crucial to stay aware of potential bias.

  • Resource-intensive: Qualitative research demands time and effort. Conducting interviews, transcribing, and analyzing data is a labor-intensive process, which might not suit all budgets or timelines.

  • Smaller samples: Your pool of participants tends to be smaller compared to quantitative research, making it challenging to generalize findings to a larger population. It's like diving deep into a few personal stories rather than looking at the bigger picture.

  • Can’t always be automated: Unlike quantitative research, where you can automate data collection and analysis with software, qualitative research relies heavily on human interaction and interpretation. You can, however, create a survey with open-ended questions to collect qualitative data. Better yet, try our VideoAsk feature, which allows you to ask questions via pre-recorded video and lets respondents answer in video, voice, or text format, preserving that ever-important human element that defines qualitative data. 

What is quantitative research and data?

Quantitative research is all about numbers, statistics, and cold, hard data. It’s more structured and objective and helps reduce researcher biases. It gets at the “what” of a person’s behavior by answering questions like how many, how often, and to what extent?

Let’s look at quantitative research in action. Imagine you're trying to pinpoint the target market for your new fitness app. You survey the app's users, collecting data on their age, gender, location, and fitness habits. The data reveals that 75% of your target users are ages 18-34, with a nearly even split between men and women. You also notice that users in urban areas are 20% more likely to use your app regularly than those in rural areas.

Quantitative research doesn't stop at just counting, though. It's also about analyzing data to spot trends and differences. In this case, it's clear that your core audience consists of younger adults in urban settings, and you can tailor your marketing strategies and app features to better cater to this demographic. So, if you're a number-crunching, stats-loving kind of researcher, quantitative research is your jam.

Pros and cons of quantitative research

In a nutshell, quantitative research is your go-to when you want solid, numerical answers. But remember, it won't tell you the whole story, and sometimes, life's questions are a bit too complex for a numbers-only approach. Keep these pros and cons in mind when running your next quantitative study:


  • Precision with numbers: Quantitative research is like a laser-guided missile for numbers. It offers precise measurements and statistical analysis, which is great when you need concrete answers.

  • Reproducibility: It's a cookie-cutter approach—your methods and results can be replicated by others, making it a cornerstone of scientific rigor.

  • Generalizability: You can often apply findings to a larger population—if it works for one group, it might work for a similar one.

  • Limited bias: Quantitative research can be a bias-buster. With structured surveys, standardized data collection methods, and statistical analysis, it's easier to minimize researcher bias and keep the study objective. 

  • Fewer resources: If you're watching your budget, quantitative research may give you more bang for your buck. It often requires fewer resources in terms of time, personnel, and money, making it a practical choice, especially for smaller-scale research projects.


  • Limited depth: While it's king of numbers, quantitative research can be a bit shallow in understanding. It's like knowing the “what” but not the “why.”

  • Context ignored: Sometimes context gets lost in a sea of numbers, and you might miss the bigger picture.

  • Inflexibility: If your research question isn't easily quantifiable, you might end up with results that are difficult to decipher. Not everything can be counted or measured.

Which is better: Qualitative or quantitative research?

“Without analysis, data is just numbers or anecdotes.” —Christine Shimoda

It’s a trick question. We’re not pitting qualitative and quantitative research against each other. However, one may prove more useful than the other, depending on your research goals. 

For example, it’s best to stick with qualitative research when:

  • You want to explore in-depth: Choose qualitative research when you need a deep understanding of a complex phenomenon, like customer perceptions or human behavior. It's like peeling back the layers of an onion to uncover the core.

  • You need to generate hypotheses: Qualitative research is fantastic for generating ideas or hypotheses that you can later test with quantitative research. 

  • You value the human perspective: If you want to capture emotions, stories, and personal experiences, opt for qualitative research. It's your go-to when you're interested in "the why" rather than just "the what."

On the other hand, quantitative research may prove more valuable if:

  • You need to measure and quantify: If you're after hard numbers, like percentages, averages, or correlations, quantitative research is your go-to.

  • You want to generalize to a larger population: Quantitative research allows you to make statistically valid generalizations to a broader audience. If you plan to reach a wide market, this is your best bet.

  • You prefer structured and standardized data collection: When consistency and minimizing bias are critical, quantitative research methods like surveys and online tests provide a structured and uniform approach. 

However, you aren’t limited to just one type of research method. You can use both qualitative and quantitative data to give you the most insightful information when:

  • You need a comprehensive understanding: Sometimes, using both qualitative and quantitative research sequentially is the ideal approach. Start with qualitative research to explore a topic, identify key variables, and generate hypotheses. Then, use quantitative research to test those hypotheses on a larger scale, ensuring a more comprehensive understanding.

  • You want to validate findings: When you've conducted qualitative research and want to make sure your findings are not just anecdotal, quantitative research can validate and generalize your insights to a broader population.

  • You're tackling a complex problem: For multifaceted issues, using both approaches can provide a well-rounded view. Qualitative research can uncover the depth and nuances, while quantitative research can quantify the extent of the issue and help prioritize actions.

Quantitative research provides evidence and predictions. Qualitative research provides context and explanations. So which one is best for you? That depends on the questions you need answered.

Research methods

Quantitative and qualitative research methods are systematic ways of collecting data and testing hypotheses. And guess what? It’s something you already do all the time.

We constantly take in information from our surroundings to figure out how to interact with the people around us.

The same goes for market research. A company tries to learn more about their customers and the market. Why? To develop an effective marketing plan or tweak one they already have. The method you use to do this depends on the data that will answer your key questions.

Qualitative research methods

Here are some of the most common qualitative research methods:

  • In-depth interviews: Known as IDI in market research circles, in-depth interviews are ideal for digging into people’s attitudes and experiences. 

  • Case studies: In-depth analysis of a single case or a few cases are best suited for investigating unique or complex cases in depth

  • Focus groups: These are effective for getting several opinions in a conversational format. Participants lead the discussion, while a facilitator guides the conversation through a list of topics, questions, or projective exercises.

  • Participant observation: Simply engaging and observing your audience day-to-day provides a firsthand view of how people interact in real-life situations.

  • Historical research: Exploring historical documents and records helps you examine the past through primary and secondary sources, contributing to our understanding of historical events and trends and how they may relate to the current scenario.

  • Qualitative surveys: Surveys comprised of open-ended questions provide an automated way to receive qualitative data through a quantitative approach..

  • Ethnography: Ethnography is a broad market research approach that involves all of the methods above in order to gain a comprehensive understanding of the culture or community being studied. 

Quantitative research methods

Here are some of the most common quantitative research methods:

  • Surveys: Surveys conducted online, over the phone, and even in person with structured interview questionnaires are an efficient way of collecting data from a large pool of participants. 

  • Polls: Polls are one- or two-question surveys that are often used to gauge public opinion on an important matter (or a frivolous matter—it’s your poll). Because polls are only one or two questions, analysis is pretty much immediate.

  • Structured observation: This is a structured form of ethnography used to measure certain actions or behaviors, such as tracking how many boxes of cereal people pick up before choosing one to purchase.

  • Experiment: Market researchers conduct controlled, manipulated, or randomized experiments to understand how specific variables influence outcomes through methods like A/B testing or pilot testing.

  • Quizzes: Answering a few general questions to find out which Harry Potter character you are may seem like fun and games, but interactive quizzes are a great tool for gathering information while keeping your audience engaged. 

  • Secondary data analysis: This cost-effective research method taps into big existing datasets like government databases or company records to pull relevant data. 

Mixed research methods

Mixed research methods combine both qualitative and quantitative approaches to provide a comprehensive understanding of the question at hand. Some of the most common mixed research methods include:

  • User testing: You’ve heard the phrase “Show, don’t tell.” So rather than asking people to explain their experiences, why not have them show you? User testing can tell you where you thrive and fall short, so you can adjust your marketing strategy accordingly.

  • Help transcripts: Live chat or call transcripts can yield both qualitative and quantitative data. Reading and coding them can help you understand people’s pain points and challenges throughout your conversion funnel.

  • Customer reviews: Look beyond your own surveys and check sites like Yelp or Google reviews. What are people saying about you? What do they like and dislike? The things people say and how often they say it can yield robust qualitative and quantitative data.

“The analysis is what brings the meaning of the data to the surface. It’s what identifies the trends, story, and insights. It translates data from something that is merely interesting to something that is useful and actionable.” —Christine Shimoda

Data analysis

Data analysis is the search for patterns in data, followed by the interpretation of that information to help explain why those patterns are there.

It’s important to keep in mind that quantitative and qualitative data aren't mutually exclusive.

Qualitative data can be translated into quantitative data. For example, you could count the number of times interviewees used a particular word to describe your product to yield quantitative data.

Similarly, quantitative methods of analysis require you to explain what the patterns mean and connect them to other parts of your business—a qualitative exercise!

Qualitative data analysis example

Qualitative data can be difficult to analyze since it’s largely made up of text, images, videos, and open-ended responses instead of numbers. Examples of qualitative data analysis include:

  • Thematic analysis: Identifying and categorizing recurring themes, patterns, or concepts within the data to uncover the most prevalent and significant themes in your dataset

  • Content analysis: Examining large amounts of text, visuals, or audio content to identify themes or patterns 

  • Discourse analysis: Dissecting the language used in the data to understand how individuals or groups construct meaning and social reality through their discourse

  • Cross-case analysis: Comparing and contrasting multiple cases to identify commonalities and differences, helping to develop broader insights

Quantitative data analysis example

Quantitative data analysis is all about crunching numbers. It can involve presenting data models such as graphs, charts, tables, probabilities, and more.

Tools like Excel, R, and Stata make it easy to track quantitative data like:

  • Average scores and means

  • The number of times a specific response is recorded

  • Connections or potential cause-and-effect relationships between two or more variables

  • The reliability and validity of results 

Get the right data with Typeform

Congrats—you’ve learned all about the differences between qualitative vs. quantitative research.

Now, the key to successful data collection is iteration.

That doesn’t mean doing the same thing again and again.

It means continually returning to your questions, methods, and data to spark new ideas and insights that'll level up your research—and your business.

Typeform makes it easy to design and automate forms that collect both quantitative and qualitative data—no extensive interviews or focus groups required. With conditional formatting and various question types, you can gather the information you need to get more customers.

Liked that? Check these out: