How to collect qualitative and quantitative data in customer surveys

Understand the difference between qualitative and quantitative data for better customer feedback survey design

How to collect qualitative and quantitative data in customer surveys

When it comes to surveys, knowing the difference between quantitative and qualitative data is crucial. These two types of data have distinct characteristics and serve different purposes, so it's important to understand and use them appropriately. Analyzing the data you collect is just as important as gathering it. Here, we’ll explore the differences between quantitative and qualitative data and how to balance them effectively in your surveys.

Quantitative Data

Quantitative data is all about numbers. It's objective, accurate, and easy to analyze statistically. It means qualitative data is perfect for processing large datasets and spotting trends. 

Quantitative Customer Research 

Quantitative surveys are designed to collect numerical and statistical data. They typically use multiple-choice, rating, or scale questions, which makes it easier to quantify responses because the answer choices are predefined. If you include an "Other" option where respondents can enter a number, you can easily convert these responses into indicators or graphs later. Quantitative surveys are great for identifying general trends and analyzing correlations between variables, patterns, and other statistical relationships. They also tend to have lower drop-off rates compared to qualitative surveys, which require more effort from respondents since they involve text input.

Quantitative Survey Examples
- Product Usage Rate Survey: This is a survey used to see how the usage rate of a specific product or service changes. You can perform statistical analysis by measuring frequency of usage or satisfaction through multiple-choice questions.

- Market Survey: This is a survey used to numerically identify consumers’ preferences, purchase intentions, and market share within the interested market. Market trends can be understood through statistical analysis of collected data.

Qualitative Data

Qualitative data is subjective and descriptive. It encompasses text, emotions, attitudes, and opinions, making it difficult to quantify. This type of data includes product reviews, emotional expressions, personal experiences, and perceptions. Because it involves subjectivity, the interpretation of qualitative data can also be subjective, varying from person to person.

Qualitative Survey

Qualitative surveys are designed to explore subjective experiences, opinions, attitudes, and more. They are ideal for understanding individual respondents' views and feelings, as well as collecting detailed opinions and experiences. These surveys typically consist of short-answer, long-answer, and paragraph questions, providing a space for respondents to freely express their thoughts. Although qualitative data is challenging to quantify objectively, it is invaluable for gaining in-depth insights and identifying correlations, offering detailed information about specific topics. Such surveys can even uncover unexpected new perspectives that can help improve your brand’s services or products.

Qualitative Survey Examples
- Customer Satisfaction Survey for Product or Service: This is a survey to understand how customers feel about a product or service and what needs to be improved. It provides a detailed understanding of the customer’s experience through essay questions.

- Employee Opinion Survey: Surveys are conducted to identify employees’ opinions, suggestions, and problems within the organization. Through this, problems within the organization are identified and solutions are sought.

How to balance quantitative data collection and qualitative data collection in surveys

It is difficult for a survey to be effective if the questions are structured for the sole purpose of collecting only quantitative data or only qualitative data. If questions consist of only quantitative questions for the sake of ease of response and data analysis, there will be no space for respondents to freely share additional opinions. It blocks ‘Communication’, the core value of survey. On the other hand, if questions consist of only qualitative questions to infinitely respect the respondents’ opinions, the respondents may feel burdened and drop off the survey. Also, it’s difficult to figure out what our customers feel in common as the data is difficult to objectify. Therefore, when creating a survey, it is very important to efficiently utilize multiple-choice questions and essay questions, which are the question types that collect quantitative and qualitative data, respectively.

Question Design  

Monotonous surveys with only one type of question can reduce response completion rates. Providing various types of questions can stimulate respondents’ curiosity and increase their motivation to participate in the survey. Therefore, in order to collect both quantitative and qualitative data, try designing your survey with various types of questions. For example, quantitative data collection questions can take various forms, such as multiple-choice, scale, rating, slider, and more. Afterwards, it is effective to place essay questions about why a respondent chose a certain choice or score.

Question Order

It is best to place questions that collect qualitative data late in the survey or after related topics. The key of the beginning of the survey is to arouse respondents’ interest and increase participation, so the beginning should be composed of quantitative data collection questions that require simple answers. Then, if you place qualitative survey questions in the later, the response completion rate increases. Additionally, placing qualitative data collection questions after a related topic increases the likelihood that respondents will respond more sincerely because they have already thought about the topic.

Ratio of Question Types

There is no absolute standard for the ratio of questions collecting qualitative data to questions collecting quantitative data. This is because the composition of questions varies depending on the purpose of the survey and the response analysis method. However, usually about 70-80% of the entire survey consists of quantitative data collection questions. According to actual statistics, the average number of questions in a satisfaction survey is about 14, of which less than 2 are qualitative questions.

If your survey is intended to gain in-depth insights, the ratio of essay questions may be higher. However, if you want quick data collection and analysis, the ratio of multiple-choice questions should be higher. Therefore, consider the appropriate ratio depending on the purpose and situation of the survey you wish to conduct. 

It is important to understand the difference between quantitative and qualitative data and conduct a balanced survey that collects both. Gaining balance helps respondents to answer more sincerely and without getting tired and the company to collect higher quality data. Doing so provides richer information for decision-making and helps with in-depth understanding of respondents. Therefore, please refer to the information explained today to establish an effective survey strategy based on your understanding of various data collection and create an actual survey.