Qualitative vs Quantitative Data in Surveys: What’s Better?

Deciding whether to collect customer data through stories (qualitative data) or numbers (quantitative data) can be tricky. 

Many researchers and marketers find themselves stuck between the detailed insights of qualitative data and the clear, measurable facts of quantitative data. 

It then creates a big debate about which method, qualitative vs quantitative, is better for surveys. 

Let’s talk about it!

What is qualitative data?

Qualitative data refers to non-numerical information gathered through methods like interviews, focus groups, open-ended questions in surveys, and scraping the web for customer reviews. 

➡️ GOAL: providing in-depth insights into human behavior, motivations, and attitudes. It gives a better understanding of the subject matter.

What is quantitative data?

Quantitative data consists of numerical information that can be measured and analyzed statistically. It is collected through methods such as surveys with closed-ended questions, experiments, and observations

➡️ GOAL: providing a broad overview of trends and patterns across a large sample.

When to use qualitative data in research?

Have you got doubts about that? Let’s clear them.

Exploring new phenomena

When conducting research in areas where little is known, qualitative data collection methods are invaluable. 

They let researchers gather qualitative insights through open-ended questions, focus groups, and interviews. It also provides a rich, detailed understanding of the subject matter. 

Useful in: qualitative studies exploring concepts, behaviors, or experiences in depth, offering a foundation for further quantitative research.

However, you won’t gather the data effectively without a robust tool for that. Surveylab provides many question types suitable for collecting both: qualitative and quantitative data. 

For example: open-ended questions, single choice, multiple choice, matrix, numeric / slider, NPS, and more.

Other Surveylab’s superpowers:

• multi-language surveys, 
• dedicated customer and domain support,
• ideal for mobile surveys 
• integrations with other tools ( CRM, eShop, BI / DWH)

Check out pricing and other features.

Understanding contexts and complexities

Qualitative research shines when the goal is to understand the context behind behaviors, decisions, or perceptions. 

Through methods like thematic analysis and discourse analysis, qualitative researchers can interpret non-numerical data to uncover patterns and meanings that numerical data cannot reveal. 

Useful in: fields like sociology or anthropology, where the nuances of human interaction and culture are central.

Developing concepts and theories

In the early stages of research, particularly when developing theories or concepts, qualitative data provides the depth and flexibility needed to form hypotheses. 

Useful in: collecting data from focus groups or in-depth interviews to build theoretical frameworks that explain how and why certain phenomena occur.

Gaining user or customer insights

For businesses and designers, qualitative research offers a pathway to deep user or customer insights. 

Gathering qualitative data through user interviews, customer feedback, or focus groups helps understand users’ needs, preferences, and pain points.

Useful in: developing new products, services, or features that closely meet customer expectations and improve the overall user experience.

Evaluating social programs

Qualitative data is essential for evaluating the impact of social programs or interventions. 

Unlike quantitative data, qualitative feedback from participants provides insights into how and why a program succeeded or failed. 

This can include participants’ personal stories, experiences, and perceptions. 

Useful in: comprehensive view of the program’s effectiveness and areas for improvement.

When to use quantitative data in research

As it’s a different approach, you need to know when to use quantitative data.

Measuring variables quantitatively

Quantitative research is the go-to when the objective is to measure variables and analyze numerical data statistically. 

The approach is suited for studies that require quantitative data collection methods like surveys with closed-ended questions or experiments where numerical values can be assigned to outcomes. 

Useful in: fields like psychology or economics, where researchers seek to quantify behaviors, attitudes, or conditions.

Testing hypotheses or theories

When researchers want to test hypotheses or validate theories, quantitative research methods provide the rigor and structure needed. 

Through controlled experiments and statistical analyses, quantitative data allows for hypothesis testing. It enables researchers to draw conclusions based on empirical evidence. 

Useful in: establishing causal relationships and validating theoretical models.

Identifying trends and patterns

Using statistical analysis and descriptive statistics, researchers can analyze quantitative data to uncover significant trends, correlations, or differences within the data. 

Useful in: market research, epidemiology, and other fields where understanding broad patterns is essential.

Generalizing findings to a larger population

Quantitative research methods, particularly those involving a random sample, are designed to generalize findings from a sample to a larger population. 

Useful in: researching broad inferences about a group’s behaviors, attitudes, or characteristics, ensuring that the conclusions drawn are statistically significant and representative.

Comparing groups or conditions

Through quantitative analysis, researchers can use numerical data to conduct comparative studies, and employ statistical analyses to determine if significant differences exist between groups. 

Useful in: clinical trials, educational research, and any study where comparing outcomes is key.

Qualitative and quantitative data: key differences

To make things clearer, we’ve compiled a list of key differences, with a quick explanation.

Nature of data

✔️ Qualitative research focuses on textual data, gathering qualitative data through methods like interviews and focus groups. All to gain insights into the subjective nature of human experiences. 

✔️ Quantitative research deals with numeric data, employing quantitative data collection methods to gather numerical values that can be analyzed using inferential statistics.

Analysis methods

✔️ Qualitative data analysis involves interpreting non-numerical data, often through thematic or content analysis, to uncover patterns and meanings. 

✔️ Quantitative analysis, however, relies on statistical analyses to test hypotheses and draw conclusions based on numerical data, using descriptive and inferential statistics to quantify relationships and differences.

Research aims and objectives

✔️ Qualitative research aims to explore the depth, meaning, and complexity of phenomena. It focuses on the subjective interpretation of data to provide in-depth insights. 

✔️ Quantitative research seeks to quantify variables and generalize findings from a sample to a larger population. The goal is to identify trends, test theories, and establish causal relationships.

📚 Read: how to analyze survey data and best practices for that.

Approach to data collection

✔️ Qualitative researchers gather qualitative data through open-ended questions and discussions. Understanding the participants’ context and perspectives is the goal.

✔️ Quantitative researchers, on the other hand, collect data through structured methods like surveys and experiments. Here, the focus is on generating quantifiable evidence that can be statistically analyzed.

Role of the researcher

✔️ In qualitative research, the researcher often plays a more active role in interpreting data, with a focus on analyzing qualitative insights and the subjective experiences of participants. 

✔️ Quantitative researchers maintain a more detached stance, focusing on objective measurement and analysis to ensure that the findings are not influenced by the researcher’s biases.

📚 Read: what is non-response bias and why it matters?

Key similarities of qualitative and quantitative data collecting methods

As those two methods differ, there are also similarities.

Objective of understanding

Both qualitative and quantitative research share the objective of understanding human behavior, social phenomena, or specific research questions. 

Whether through qualitative or quantitative data, both approaches aim to gain insights into their respective areas of study, contributing valuable knowledge to the field.

Use of mixed methods

Another similarity is the increasing use of mixed methods, combining qualitative and quantitative research in a single study. 

The approach uses the strengths of both methods to provide a more comprehensive understanding of research questions, It allows researchers to explore complex issues with both depth and breadth.

Importance of rigorous data collection

They emphasize the importance of rigorous data collection processes. 

When collecting qualitative or quantitative data, they ensure that the data is reliable and valid so they can make accurate conclusions.

Contribution to knowledge

These research methods contribute to the expansion of knowledge within various fields. 

They explore new concepts and test theories. They also help to fill gaps in understanding, contributing to the development of new theories and practices.

Ethical considerations

Both qualitative and quantitative research are bound by ethical considerations. They ensure the research is conducted responsibly and with respect for participants. 

For example: obtaining informed consent, ensuring confidentiality, and minimizing any potential harm to participants. All to highlight the shared values and standards that guide research practices across methodologies.

📚 Read: 10 tricks to help you build better surveys

How to tackle qualitative vs quantitative in surveys – best practices

Do you feel quite overwhelmed? Check out our tips!

Balancing qualitative and quantitative questions

Start with quantitative data questions to get statistical insights, then use qualitative questions to explore respondents’ thoughts and feelings in more depth. 

It’s a balanced approach that combines numerical value with subjective insights for a deeper understanding.

Designing effective qualitative questions

When crafting qualitative questions, go for open-ended questions that encourage detailed responses. Use qualitative research methods like thematic analysis to identify patterns and themes in the responses. 

You can gain a deeper understanding of the numbers and their context by understanding the nuances behind them.

Utilizing quantitative data for broad insights

Quantitative questions should be designed to collect numeric data that can be easily analyzed through statistical analysis. We can use this quantitative data to catch the trends, patterns, and general behaviors across a large sample. 

Leveraging descriptive statistics and quantitative data analysis, researchers can quantify attitudes and opinions. They get a broad overview of the study population.

Analyzing qualitative data thoroughly

Qualitative data analysis requires a detailed approach to interpreting open-ended responses. Techniques such as qualitative analysis and thematic analysis help researchers to explore textual data, uncover underlying meanings and gain qualitative insights. 

It’s essential to understand the “why” behind the numbers in quantitative data.

Applying statistical analyses to quantitative data

For quantitative data, employ statistical analyses to validate findings and draw conclusions. Data patterns can be summarized using descriptive statistics and inferential statistics. 

Then, you may get robust and reliable results for both quantitative and qualitative research.

Leveraging mixed methods for comprehensive insights

Adopt a mixed methods approach that combines qualitative and quantitative research – it’s a way for enriched data collection and analysis. 

Researchers then can explore a topic through qualitative data and then measure those findings with quantitative data, or vice versa. 

Ensuring quality in data collection methods

High-quality data collection is vital, no matter if the focus is on qualitative or quantitative data. Reliable data collection methods, such as: 

• carefully designed surveys and focus groups for qualitative data, 
• and structured questionnaires for quantitative data, 

Provide the research findings with validity and reliability.

Navigating the advantages and disadvantages

Understanding the advantages and disadvantages of qualitative vs quantitative research is key to choosing the right approach for your study. 

While qualitative studies offer depth and detail, quantitative studies provide breadth and generalizability. 

When deciding how to tackle their survey design for optimal results, researchers should consider: 

• their research goals, 
• the nature of the data, 
• and the intended analysis methods 

Source: Designs.ai

Key takeaways

• Combining quantitative and qualitative data in surveys provides a comprehensive understanding of research topics.
• Quantitative data refers to numerical information that can be statistically analyzed for broad insights.
• Qualitative methods involve open-ended questions that explore participants’ thoughts and experiences in depth.
• A quantitative researcher focuses on collecting and analyzing numerical data to identify trends and patterns.
• Gap analysis can benefit from both quantitative and qualitative data to identify and address discrepancies between current and desired states.
• Nursing research often utilizes both qualitative and quantitative studies to improve patient care and healthcare practices.
• Developing strong research skills is essential for effectively designing and conducting mixed-methods research.
• Focus group discussions are a valuable qualitative method for gathering detailed feedback and insights.
• A quantitative study aims to quantify variables and often uses statistical methods to test hypotheses.
• A qualitative study seeks to understand the meaning, characteristics, and descriptions of phenomena, providing rich, detailed insights.

Conclusion on qualitative and quantitative research

Mastering the blend of quantitative and qualitative research is super important to unlocking deeper insights.

Crunching numbers for clear trends? Diving into discussions for nuanced understanding? Each method offers its own strengths. 

As you refine your research skills, remember: the best insights come from combining the clarity of quantitative data with the depth of qualitative analysis. 

Now, it’s your turn to take these strategies and turn them into actionable insights. And it wouldn’t be smooth without the surveying tool. Sign up for SurveyLab, and make data collection a breeze.

FAQ on qualitative vs quantitative data

Do you have any questions? Check out our answers.