Qualitative vs Quantitative Data

For instance, the type of data you need when looking for insights into how your product sales have changed after a new marketing campaign may not be the same as the type of data you need to establish insights into how customers relate to your brand.

The primary objective of this post is to highlight some of the key differences between qualitative and quantitative data in the context of marketing and conversion rate optimization (CRO).

We shall also mention the tools you need to collect each type of data and how you can utilize it to enhance your decision making. So, let us get started.

What Is Qualitative Data?

Qualitative data refers to non-statistical data that is usually unstructured or semi-structured in nature. This data is mostly expressed using sentences and natural language. It is based on properties, labels, attributes, and other identifiers.

Qualitative data gives us the "why" and not statistics that can be graphed or charted. It helps you to establish why a customer buys your product/service (or doesn't). It provides you with the reasons behind the figures and takes the guesswork out of the picture.

In most cases, you get qualitative data by asking open-ended questions that may result in further hypotheses, interpretations, and theories. Here are some of the questions that qualitative data can help you answer:

• Who is my target audience (not just demographically but psychologically)?
• Why are my leads not converting?
• What do I need to test?
• What hesitations do people have when trying to purchase my product that I need to address?
• What specific language does my target audience use when describing the problems or pain points?
• Is my onboarding process efficient?

Typically if you are rigorous and asking the right questions, you will gather critical qualitative data that can help you solve some of the weirdest marketing problems. You will get to the emotions of users and understand how they feel about your brand.

When Should You Use Qualitative Data?

Let us cover some of the crucial scenarios that allow you to put qualitative data into practice.

• Defining user persona: You will need qualitative data when defining your ideal buyer or user persona. Going deep into the "why" will help you craft an eye-catching profile of your ideal client, and that is what you need to target the right people.
• Market research: Qualitative data also comes in handy when you want to pilot market research. It can be an effective way to get social media insights and perceived customer reception of specific goods or services.
• Market validation: You may have a genius idea, but how do you confirm if people will pay for it? You need to establish market validation, and the only way of doing so is by collecting qualitative data.
• Understanding your target audience better: To speak to your target customers and speak in their own language, you need to understand their concerns and exact pain points. What is troubling them, and how is your product/service going to offer a solution?

Tools and Methods Used To Gather Qualitative Data

There are many tools and methods you can use to obtain qualitative data. One of the most commonly used tools is heat maps and session recording software.

The primary objective of heatmap and session recording is to track interactions such as mouse movements, clicks, page changes, and form interactions. These user interactions can then be replayed as a video or visualized in a heatmap so you can establish what your visitors were really looking for on your site.

Heatmap and recording sessions are critical CRO tools that offer site owners a fast and visual way to understand their users. Other methods used in collecting qualitative data are:

• Case studies:They are more in-depth and provide stories from consumers and clients. From these stories, you get to understand how your product is performing and why people like or dislike it.
• Interviews: Allows you to collect user views and opinions with a one-on-one approach.
• Open-ended survey questions: They allow respondents to express themselves freely without limitation to specific responses.
• Focus groups: These are designed to allow multiple people to express their views/opinions on a product, service, or topic
• Observational research: Some marketers choose this approach because it is beneficial for understanding individuals in their regular routines and seeing how they interact and react to different scenarios.
• User tests: user tests involve watching users interact with your site or product in a specific way that you direct. User tests can be moderated or unmoderated, and you can choose to set broad prompts or specific prompts.

Quantitative Data

After covering qualitative data, let us now turn our focus to quantitative data and understand what it is and how it differs from qualitative data.

Quantitative data is statistical data that is highly structured in nature and can easily be graphed or charted. It is more rigid and defined and is usually measured in numbers and values, which make it more suitable for data analysis.

Unlike qualitative data, quantitative data is closed-ended and only answers questions such as “how much” or “how many.”

This type of data is obtained through closed-ended surveys, tests, experiments, market reports, and metrics.

Quantitative data is helpful when your primary objective is to make people take action based upon the insights you gather from the statistical data. This type of data is also meant to identify trends and patterns and critically analyze the behavior of your users.

Quantitative data can further be broken down into two subcategories, namely:

• Discrete data: This type of quantitative data is finite and cannot be broken down into smaller parts. It consists of integers that can be negative or positive. A few examples of discrete data would be how much traffic came to your site in the last month, the number of sales you achieved last week, or how much salary you earned last year.
• Continuous data: This type of quantitative data can be broken down into smaller parts and fluctuates constantly. A few examples of continuous data include the average speed of your car every morning, your weight, age, or how long it takes you to read this article.

When Should You Use Quantitative Data?

You should always turn to quantitative data when you are looking for unbiased analysis. For instance, if you want to establish how much profit you made in the last quarter or how many sales you are generating from your Google Ads campaign, then you need quantitative data.

Also, if you have developed a new site, and you want to measure the effects of one call-to-action against another, then you will need to perform A/B testing, which yields quantitative data that will influence your decision.

Measuring the overall satisfaction of your clients using metrics such as the Net Promoter Score (NPS), as well as the overall performance of your company through different metrics, is another excellent example of how to use quantitative data.

Basically, anything that is used to perform statistical analysis or in-depth research backed by numbers is quantitative. The results of a statistical analysis based on quantitative data always tend to be accurate and unbiased because you are working with a large set of data and are focused on specific figures. However, don’t get us wrong because we aren’t trying to say that quantitative data is superior to qualitative data. Each type of data is critical, and in most cases, the method you use to analyze your data will determine the outcome.

Tools and Methods Used To Gather Qualitative Data

A significant number of website tools, including Google Analytics, Google Search Console, and Mixpanel, collect quantitative data. Such tools provide you with an abundance of data, metrics, graphs, and dimensions, but they don't provide you with the "why" behind the data.

For instance, you can know the number of users who visited your site, but you cannot tell why they clicked on one button and not the other or why they decided to drop out even after they started filling a form.

Some closed-ended surveys and feedback tools also gather quantitative data because they usually give you the ability to ask for metrics and figures. In other words, they let you ask quantitative questions.

Qualitative or Quantitative Data: Which One Is Better for Analysis?

Even though these two types of data vary, not one of them is better than the other. They both serve different purposes and complement one another. In fact, each one of them has its own strengths and weaknesses that you need to understand.

Quantitative data is primarily numbers, and we all know how numbers can be convincing for stakeholders. However, the figures can be difficult to interpret since you know that something happened or didn't happen, but you don't understand the reasons behind it.

Therefore, if you want to rely on quantitative data only, you must have solid knowledge and vast experience in statistical analysis to avoid coming up with wrong conclusions.

On the other hand, qualitative data is perfect for illustrating the reasons behind certain actions. It helps you to uncover how people feel, their emotions, and reasoning behind their behavior. It is instrumental when you want to go beyond the numbers and understand your target audience better.

Final Thoughts

Sticking to just one type of data can harm your marketing effort. It is always a good idea to combine both of them and figure out how to apply them concurrently. This way, you can be sure to draw informed conclusions that will help you achieve your goals.