{"id":109,"date":"2021-11-17T09:30:16","date_gmt":"2021-11-17T09:30:16","guid":{"rendered":"https:\/\/blog.qualaroo.com\/?p=109"},"modified":"2026-03-20T10:33:36","modified_gmt":"2026-03-20T10:33:36","slug":"qualitative-vs-quantitative-customer-feedback","status":"publish","type":"post","link":"https:\/\/web-staging.qualaroo.com\/blog\/qualitative-vs-quantitative-customer-feedback\/","title":{"rendered":"Qualitative vs. Quantitative Research: How to Get the Best of Both Worlds"},"content":{"rendered":"

We often hear how listening to the voice of your customers is foundational to a sustainable business.<\/p>\n

But here’s the pickle – companies are always in a tug of war between Qualitative vs. Quantitative feedback research without analyzing what kind they need.<\/p>\n

We know quantitative research aims to quantify data points based on users’ journeys, like the NPS survey. In contrast, qualitative user research collects data on more niche attributes like user behavior, preferences, and more.<\/p>\n

The challenge is to pick the right methodology that fits your use case and requirements.<\/p>\n

So, stick to the end if you’re also trying to piece it together and barely succeeding at identifying which research method is best for your business.<\/p>\n

We’ll explore how to balance qualitative and quantitative research, their types, different analysis methods, and more.<\/p>\n

Let’s begin!<\/p>\n\n\n

<\/span>Qualitative vs. Quantitative Research: Understanding the Difference<\/span><\/h2>\n\n\n\n

Let\u2019s see how qualitative and quantitative research methods differ and how you can balance the two to achieve remarkable results.<\/p>\n\n\n\n

Here is a comparative overview of qualitative vs. quantitative feedback data and what sets them apart. <\/p>\n\n\n\n

Parameters<\/strong><\/td>Qualitative <\/strong><\/td>Quantitative<\/strong><\/td><\/tr>
Concept<\/strong><\/td>Aims to understand human behavior, preferences, and needs from an interviewee’s point of view.<\/td>Aims to understand human behavior, preferences, and needs from an interviewee’s point of view.
Focuses on collecting facts about social phenomena<\/td><\/tr>
Objective<\/strong><\/td>Concerned with discovering social phenomena, unconscious or conscious. 

Explores the psychological mechanisms via interaction with individuals or analyzing individual responses online.<\/td>		Collects quantifiable data, which is easy to visualize. 

Measures the past and predicts the future.

Help verify speculations and hypotheses made during qualitative research.<\/td><\/tr>
Methods to collect<\/strong><\/td>Ethnographic research
Heuristic inquiry
Online surveys (using Sentiment Analysis)
User testing
Phenomenology
Focus groups
Grounded theory<\/td>		Digital analysis
Technical analysis
Online survey research
Causal-comparative
Correlational (Descriptive research)<\/td><\/tr>
Pros<\/strong><\/td>Offers in-depth insights
Budget-friendly
Collects contextual data<\/td>		Highly objective
Easy to collect
Easy to analyze and visualize
Identifies trends<\/td><\/tr>
Cons<\/strong><\/td>Not reliable in all cases
Requires manual efforts (except for online surveys)
Highly subjective<\/td>		Lacks in-context data
High on cost<\/td><\/tr>
When to use<\/strong><\/td>To perform market research
To add a human touch to your research
To develop hypotheses<\/td>		To perform market research
To get general feedback
To validate Hypotheses<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
\n\n\n\n

To understand these concepts better, let\u2019s have a look at them in detail:<\/p>\n\n\n\n

<\/span>What is Qualitative Feedback?<\/span><\/h2>\n\n\n\n

As the name suggests, qualitative research<\/a> focuses on the quality of the data, the non-numerical aspect of the research. It provides insights based on non-statistical and semi-structured data.<\/p>\n\n\n\n

A report<\/a> published by Open University Press states \u2014<\/p>\n\n\n\n

\u201dQualitative analysis allows for ambiguities\/contradictions in the data, which are a reflection of social reality.\u201d<\/strong><\/p>\n\n\n\n

Qualitative research goes one step further than quantitative research and gauges the underlying factors of what the feedback data represents, such as opinions, motives, reasons, and so on. The insights from the qualitative analysis can be inferred to draw conclusions, which may be subjective in some cases. <\/p>\n\n\n\n

In simple words, it puts context to the quantitative feedback data and answers the \u2018why\u2019 behind the data. <\/p>\n\n\n\n

It establishes qualitative data as explanatory and aims to represent the topic instead of measuring it like the other data type. <\/p>\n\n\n\n

Although it helps understand the data in detail, it makes analysis harder, unlike graphs that are comparatively easy to decipher.<\/p>\n\n\n\n

Qualitative research is collected first-hand, like observation via interviews, and can be collected via Artificial Intelligence technology like Sentiment Analysis<\/a>. The verbatim feedback collected via surveys is easy to analyze with the Sentiment Analysis feature<\/a> to derive qualitative insights.<\/p>\n\n\n\n

<\/span>3 Types of Qualitative Feedback Data to Focus On<\/strong><\/span><\/h2>\n\n\n\n

There are three types of qualitative data you should be collecting in your feedback to get a holistic view of your user experience.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n
  1. Binary data<\/strong><\/li><\/ol>\n\n\n\n

    Binary qualitative data separates things into mutually exclusive (distinct) categories like yes\/no or true\/false. The main use case for this type of data point is to segregate the users into two groups for better control.<\/p>\n\n\n\n

    \"\"<\/figure>\n\n\n\n
    1. Nominal data<\/strong><\/li><\/ol>\n\n\n\n

      Nominal data is data that’s labeled or named without any numerical value. You can use this data to differentiate between data sets. For example, MCQ-type survey data can tell much about respondents’ preferences, behavior, and more.<\/p>\n\n\n\n

      1. Ordinal data<\/strong><\/li><\/ol>\n\n\n\n

        Ordinal data is the data set arranged in an order on a ranging scale. The order of the qualitative data matters the most in this data type. <\/p>\n\n\n\n

        For example, NPS surveys use a scale of 0-10 to gauge customers’ loyalty. Here, each number on the scale represents the loyalty of the respondents.<\/p>\n\n\n\n

        <\/span>Importance of Qualitative Feedback: The Good & the Bad<\/strong><\/span><\/h2>\n\n\n\n

        One of the obvious pros of qualitative research and data is that it aims to collect data that is not quantifiable, like preferences, attitudes, challenges, etc., which provide different insights than quantitative data. <\/p>\n\n\n\n

        Another benefit is that you can conduct qualitative research via one-on-one interviews to observe participants or use Sentiment Analysis which feedback survey tools like Qualaroo<\/a> offer.<\/p>\n\n\n\n

        Besides these benefits, here are some more points highlighting \u2018the Good<\/em>\u2019 about qualitative data.<\/p>\n\n\n\n

        The Good<\/h3>\n\n\n\n

        In-Depth Insights<\/h4>\n\n\n\n

        Since qualitative research includes conducting interviews, it is possible to get a gist of users\u2019 past experiences, feelings, and reactions towards new ideas about products<\/p>\n\n\n\n

        \"The<\/p>\n\n\n\n

        \n\n\n\n

        The results from the observation are helpful to discern what features users will appreciate in the product, what elements they should look for while designing the interface, and numerous such decisions which should and can be made user-centric. <\/p>\n\n\n\n

        Qualitative feedback also tells what customers\/users think about a product or service, where customers are getting stuck in the customer journey<\/a>, and more. Companies can act on such insights to improve in all aspects. <\/p>\n\n\n\n

        Not Heavy on the Budget<\/h4>\n\n\n\n

        Compared to quantitative, qualitative research provides in-depth feedback data at a much lower cost. It doesn\u2019t require surveying large groups; instead, it supports observing smaller targeted groups and derives relevant contextual data. It requires forming small focus groups and interviews, which are not demanding on the budget.<\/p>\n\n\n\n

        Gives Abundant Contextual Data<\/h4>\n\n\n\n

        Qualitative research is all about the context, so we had to mention this benefit separately. Qualitative survey questions are generally open-ended to allow users to express themselves and get in-context feedback.<\/p>\n\n\n\n

        The open-ended questions are followed up by more questions to gauge the hows <\/em>and whys <\/em>for their responses. The goal is not to confirm what is already known via quantitative feedback data but to explore the emotions and perceptions within the data. <\/p>\n\n\n\n

        Example<\/h4>\n\n\n\n

        You can tell that customers abandon their carts with quantitative feedback vs. qualitative feedback that will answer the reason behind the shopping cart abandonment<\/a>. <\/p>\n\n\n\n

        You can reveal trends, behavioral patterns, and indispensable insights to create unparalleled marketing and product development strategies.<\/p>\n\n\n\n

        Related Read<\/strong>: How to Use Qualitative Data to Improve Your Blog<\/a><\/p>\n\n\n\n

        The Bad<\/h3>\n\n\n\n

        To some, one of the biggest drawbacks of qualitative data is that it does not offer countable accurate data. How you see this point is entirely subjective and based on what you prefer. <\/p>\n\n\n\n

        So moving on, here are some cons of qualitative feedback that you should know to set reasonable expectations from your qualitative research.<\/p>\n\n\n\n

        Sometimes Unreliable<\/h4>\n\n\n\n

        In some practical scenarios, where qualitative insights are rendered unreliable, quantitative feedback data thrives. It is due to external factors which cannot be controlled but affect the data inevitably. <\/p>\n\n\n\n

        Some qualitative data methods don\u2019t signify the exact number of people surveyed, support extrapolating results, or fit when applied to a broader audience.<\/p>\n\n\n\n

        Demands Manual Efforts<\/h4>\n\n\n\n

        Similar to other drawbacks, this one is also applicable to some qualitative research methods. Some methods require you to analyze the data manually, which is a labor-intensive task. It includes interviews, data from focus groups, with the Sentiment Analysis method as an exception. <\/p>\n\n\n\n

        Highly Subjective<\/h4>\n\n\n\n

        \"Highly<\/strong><\/p>\n\n\n\n

        Feedback data extracted from the majority of the qualitative methods are not replicable. The results are subjective since the researchers, interviewers, or observers of data decide which piece of information is relevant or not. Thus, the interpretation of the data varies.<\/p>\n\n\n\n

        <\/span>How to Collect Qualitative Feedback Data<\/span><\/h2>\n\n\n\n

        Now that you know what qualitative research entails, let’s move forward to the \u2018How\u2019 <\/em>part of it i.e. How to collect qualitative data.<\/em><\/p>\n\n\n\n

        Below we have discussed the qualitative research methods that help collect qualitative feedback.<\/p>\n\n\n\n

        \"How<\/figure><\/div>\n\n\n\n

        Ethnographic research<\/h3>\n\n\n\n

        Popularized by Anthropology, the Ethnographic research method has now become a critical part of qualitative research. It studies trends, behaviors, pain points, and cultures in a real-life environment. <\/p>\n\n\n\n

        It is geography-driven, meaning it involves researching and observing in a particular geographical location. The geography is flexible and can range from a small entity to a country as a whole. <\/p>\n\n\n\n

        Let\u2019s take an example of how ethnographic research works:<\/h3>\n\n\n\n

        You can refer to this qualitative research method to study and collect data for usability<\/a>, service design, and user-centric design problems of a product.\u00a0<\/p>\n\n\n\n

        It helps designers develop a detailed understanding of design challenges, how to bypass those challenges, their target audience, processes, and more. The ethnographic method is undoubtedly time-consuming, and on top of it, cannot be limited to a specific timeframe.<\/p>\n\n\n\n

        Heuristic Inquiry<\/h3>\n\n\n\n

        A Heuristic analysis report<\/a> explains the approach as research aiming to find “meanings and essence in the significant human experiences.<\/em><\/strong>“<\/p>\n\n\n\n

        Although a crucial tenet of research is not to rely on opinions and assumptions and trust only factual data, this approach is an exception. Applying a heuristic approach to your qualitative research means conducting an experience-based experiment and analysis by a field expert.<\/p>\n\n\n\n

        An expert\u2019s opinion on something might be subjective, but it\u2019s still valuable as it can provide deep insights. It is because an expert will assess their own experience with your services or products to bring forth profound insights.<\/p>\n\n\n\n

        Example<\/h4>\n\n\n\n

        An expert\u2019s assessment of a mobile app or a website entails specific parameters on which they analyze their experience. <\/p>\n\n\n\n

        For example, while assessing a mobile app user experience<\/a>, a few questions frequently asked in the process are:<\/p>\n\n\n\n