Qualitative vs quantitative user research: Key differences of two research methods
Nowadays, most companies are focusing on creating user-centric products, let they be tech or IT related. Marketers have observed the benefits of putting their users first in their decision-making. However, what is the best way to know users’ needs and wants?
Conducting qualitative vs quantitative research is the best method to know users’ needs and deliver in accordance with that. When it comes to research, there are two ways you can go about it: quantitative vs qualitative user research.
Nonetheless, you can’t say that it is better to do just one type of research. Sometimes, quantitative data is useful, and other times qualitative data to get to the bottom. Here, in this blog, we will give you the quantitative definition, the qualitative definition, and the difference between qualitative vs quantitative research.
What does quantitative mean?
Quantitative means any data that can be quantified. It can be measured in numbers or numerical values. Quantitative data takes into consideration statistical, mathematical, and computational analysis of data. It answers questions like, “how much”, “how many” and “how often”.
Examples of quantitative data:
- 203 people visited the website today.
- This brand’s product costs $800.
- I lost 5 kg weight in the last month.
As you can see in the above statements every statement has a numerical value for each parameter. Next, we will discuss the advantages and disadvantages of quantitative data.
Advantages of quantitative data
There are many advantages of quantitative data that we have given below:
- Helps in conducting in-depth research: As the quantitative data can be statistically analyzed, therefore the research will be detailed.
- Less biased decisions: Many times it happens when the research is not quantitative, personal bias gets involved. The quantitative data is numerical in nature which eliminates personal bias.
- Accuracy: The quantitative data is objective in nature which makes it accurate. The decisions based on quantitative data are more accurate.
Disadvantages of quantitative data
We have mentioned some of the disadvantages of quantitative data as follows:
- Limited information: Since the quantitative data is not descriptive in nature, the marketers have to make decisions based on the gathered data.
- The questions asked to collect quantitative data: The questions that researchers ask to collect quantitative data play a crucial role. They should focus on the objectives of the research to gather the right quantitative data.
What is quantitative research?
Quantitative research is all about collecting and analyzing quantitative data. It aims at measuring the quantitative data by using inferential statistics and making data interpretations.
Examples of quantitative research:
- What is the total number of website visitors?
- How many people viewed a particular page?
- What is the bounce rate of website visitors?
Quantitative research can help you see things in a practical way. You talk about the digital experience in terms of quantifiable data. You can conduct statistical analysis for making decisions. You can identify feedback patterns using statistical operations.
Quantitative research can help you calculate averages, make future predictions, and analyze results. This research provides you with objective findings as it is based on numerical data.
What is qualitative data?
Qualitative data is descriptive in nature, unlike quantitative data which is expressed in numerical values. Qualitative data analysis provides you with information that can’t be measured or quantified. It usually includes words that describe particular traits or characteristics.
This data is more about the perceptions and emotions of people. It helps marketers and researchers to find answers to “why” or “how” questions.
Examples of qualitative data:
- Maximum visitors are coming from the US.
- Most of the users find session recordings the best feature.
Advantages of qualitative data
Here, we have discussed some of the best advantages of qualitative data:
- Helps in-depth analysis: This data offers the researchers with thematic analysis of different subject matters. They can find the reasons behind why users behave the way they do by asking the right questions.
- Helps understand customers better: Qualitative data can help marketers understand what customers think and feel. They can gain insight into what customers need, want, and expect.
- More data: The researchers can ask open-ended questions to customers. This helps them to get the customers’ feedback and suggestions. They can use this information to make future product advancements.
Disadvantages of qualitative data
We have listed below some of the disadvantages of qualitative data:
- Time-consuming: Collecting and analyzing qualitative data is a time-consuming process. It also requires a high budget and the right resources.
- Generalizing qualitative data is not easy: There are a lot of variations in the qualitative data. Therefore, generalizing this data is not easy.
- Depends on the researcher’s skill: The qualitative data is collected through observations, interviews, focus groups, etc. Thus, it depends on the researcher’s skills in gathering information.
What is qualitative research?
Qualitative research helps you in understanding the patterns and trends in the users’ behavior and actions. It is a subjective approach that describes an action rather than measuring it.
This type of research focuses on gaining insights, reasonings, and motivations that drive users’ actions. It provides you with information about the issues or problems that customers might be dealing with.
Examples of qualitative research:
- A man has blonde color hair.
- Maximum people prefer chocolate cake over pineapple cake.
Qualitative research provides you with more in-depth information about users. It can reveal information about your users that quantitative data can’t. You can find out what drives your customers to take specific actions.
Qualitative data analysis can help you make informed choices about your users. You can make decisions based on your customers’ requirements and motivations.
Difference between qualitative vs quantitative data
When it comes to conducting data research, it’s important that you understand qualitative data vs quantitative data differences. Here, we have given simple ways to differentiate the quantitative vs qualitative data.
The collection methods of both quantitative vs qualitative data
For collecting both qualitative and quantitative research data, you need to use different methods. Quantitative data collection methods are controlled and record numerical information. Qualitative data collection methods are flexible and involve asking open-ended questions.
In this section, we have discussed the data collection methods of both quantitative data vs qualitative data.
Quantitative data collection methods
There are many quantitative data collection methods that you can utilize. We have mentioned some of the best quantitative data collection methods below:
A survey is a quantitative data collection method in which questions are asked to a large number of people. The questions are usually close-ended to get definite answers. If the questions don’t have clear options, the results will become difficult to evaluate.
Polls are similar to surveys and help to gather quantitative data. You take a poll from a number of people and ask them to choose from the provided options. This way you get a numeric value for how many people chose each answer.
An experiment is a quantitative data collection method that includes a control group and an experimental group. Usually, the experiments are conducted under controlled or manipulated conditions. You can get extensive data from this by combining quantitative and qualitative data.
The information that you gather from these will help you to get unique perspectives. You can get a collection of rich and reliable data. The A/B tests, controlled experiments, blind experiments, and many more come under this category.
Qualitative data collection methods
Qualitative data can help you to get a better understanding of your customers. Here, we have given some of the best qualitative data collection methods.
This is one of the most commonly used qualitative data collection methods. In this method, the researcher directly collects information from the interviewee by asking one-to-one questions. The interview is usually informal and conversational in nature.
The questions can be open-ended to find the reasoning and motivations that drive certain customer actions. The questionnaire can include as many questions that can help researchers get the information they want.
As the name suggests, it is done in a group discussion setting. The groups are formed and a moderator is assigned to carry out the discussion effectively. The members of the group usually have something in common and have sufficient knowledge of the subject.
In focus groups, each member shares their point of view and opinions. This way the researchers deduce some findings to make significant changes.
This is the process in which the researcher gets into the setting where their respondents are and keep a keen eye on them. They take note of how, what, and why anything is happening. Apart from notes, they can use other documentation methods like images, audio, and video recording.
Data analysis methods: Qualitative vs Quantitative research
Data collection is an important part of the research process. However, data collection is of no use if one can’t analyze it properly. There are various methods that you can use to analyze both qualitative and quantitative data.
Quantitative data analysis methods
Analyzing quantitative data is easy by using the following methods.
It is the most commonly used quantitative data analysis method as it uses a basic tabular form to draw insights from the collected data. It consists of data that is connected or mutually exclusive.
This is a statistical analysis method that looks at the quantitative data collected over a long period of time. It is a method that collects feedback about the data changes over a period of time. It helps in analyzing data by understanding the change in variables while considering one variable constant.
This is a quantitative data analysis method that measures customer preferences and factors that makes them purchase. This quantitative data analysis method is also called the “ best-worst” method.
This method involves assigning numerical values to strengths, weaknesses, opportunities, and threats of a product or service that provides a complete picture of the data. This type of data analysis is used to create effective strategies for business.
Qualitative data analysis methods
You can use the methods given below for qualitative data analysis.
In this method, the qualitative data is analyzed based on a structure that is predetermined by the researcher. The questions can be used as a guide for analyzing the data. This is an easy approach if the researcher has an idea about the responses he/she is likely going to receive from the population.
This method is not based on any framework or predetermined structure. It is a thorough qualitative data analysis approach that requires time. It is often used when a researcher doesn’t have an idea of the research phenomenon.
How WebMaxy Analyzer can help you in quantitative vs qualitative data analysis?
For marketers, it’s important that they analyze the quantitative and qualitative data to make alterations that make difference. WebMaxy Analyzer can help you to collect and analyze quantitative and qualitative data.
You can get the total number of website visitors coming to your website. You can see how they interact and navigate through your website. You can analyze their activity and find ways to make their user journey smooth.
From session recordings, you can also find out any technical issues or problems that your visitors might be facing.
Heatmaps are graphical representations of users’ clicks and tap on your website. You can know which website elements and CTAs your visitors are clicking. This information can help you understand if your CTAs are relevantly placed or not.
Scroll maps can aid you in knowing your customers’ attention span area. You can know if they are reaching the crucial information of your web pages or not.
Surveys & Polls
With WebMaxy Analyzer, you can conduct surveys and polls easily and quickly. You can ask important questions to your customers and collect qualitative data. You can know from your users directly, what they want and expect from your company.
You can get both quantitative and qualitative customer data from the WebMaxy surveys & polls feature. It comes with many different survey templates that you can launch directly by customizing the questions and options. The survey data analysis is also easy with graphical representations.
This feature can help you observe the customer journey on your website. You can know the conversion and drop-off rate of your website visitors throughout the funnel. See where most of the users drop and what might be the reason behind it. This way you can make changes that prevent your users from slipping.
Wrapping it up
Quantitative and qualitative user research, both are necessary for the product designing process and for further improvements. It can help you know your users’ needs, wants, and goals. Quantitative research is numerical in nature and can help you work on your business numbers like bounce or conversion rates.
Qualitative research focuses on finding the reasons behind why certain things happen the way do. It takes emotions, observations, and points of view of customers into consideration. By analyzing both quantitative and qualitative data, you can make data-driven changes that deliver results.
WebMaxy Analyzer can help you to gather and analyze quantitative and qualitative data. It has a wide range of features like session recordings, heatmaps, surveys & polls, feedback, funnel view, form analytics, user insights, push notifications, and many advanced integrations.
For more information and details about WebMaxy Analyzer, connect with our experts on call or email us at firstname.lastname@example.org.
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Frequently asked questions (FAQs)
Qualitative data refers to the data that describes traits or characteristics. It is non-numerical and descriptive in nature. It can be collected through various ways like interviews, observations, focus groups, etc.
Quantitative user research is about collecting and analyzing numerical user data from technical evaluation, digital analytics, and user testing. You can use different web analytics tools for this like Google Analytics and WebMaxy Analyzer. Some examples of quantitative user research are the total number of website visitors, page views, bounce rate, conversion rate, etc.
Qualitative user research is the method of collecting and analyzing data that helps you understand your users’ viewpoints, opinions, and motivations. There are various ways to do qualitative user research such as surveys and feedback. User behavior analytics tools like WebMaxy Analyzer can help you to do qualitative user research.
Quantitative data examples are the total number of visitors, page views, average time spent, bounce rate, conversion rate, and so on. Qualitative data examples are session recordings, heatmaps, funnel analytics, surveys, and feedback. WebMaxy Analyzer can help you to collect both quantitative and qualitative data.
Quantitative analysis is the process of analyzing measurable and numerical data. It focuses on numbers and statistics. Qualitative analysis is the process of gathering data that is less tangible. It looks at the characteristics, opinions, and meanings.
Quantitative data is fixed and universal whereas qualitative data is subjective and unique. Quantitative data is numerical and measurable data. However, qualitative data relies on observations or documents that describe how customers think or feel about a product or service.
A quantitative observation is an objective collection of data (numbers & values) based on their numerical and statistical attributes. Some of examples of quantitative observation are age, height, length, population, etc.
Quantitative data is measurable and numerical in nature whereas qualitative data is non-numerical and descriptive in nature. Quantitative data answers questions like how many, how much, and how often whereas qualitative data helps to understand what, how, or why it happened.