The world is increasingly run by data. Understanding and using qualitative data is a key part of getting valuable insights from customer behavior and preferences. Collecting qualitative data using techniques like observation, interviews, focus groups, and open ended surveys, are great places to start.
If you’ve collected a mountain of data, now’s the time to dig into the qualitative side. But what is qualitative data, and how can you use it to make impactful business decisions?
What is Qualitative Data?
Qualitative data is data that can’t be immediately represented with numbers. It focuses on the qualities, characteristics, and descriptions of a given topic. While quantitative data asks questions based on statistics and numbers, qualitative data seeks to understand the “why” and “how” of customer feedback and behavior. Qualitative data examples are often rich in detail and provide helpful context that gives deeper insight to customer experience and what motivates them. Data analysis processes like deductive and inductive reasoning play important roles in qualitative data collection helping to validate and organize data, while methods like sentiment analysis play key roles in understanding nuances within the data.
Differences Between Qualitative and Quantitative Data
Though both types of data (qualitative and quantitative) should be used in any deep analysis, the fundamental difference between them is:
Quantitative Data: Represents measurements and statistics in numbers. Answers questions like “how many” and “how much.”
Qualitative Data: Describes characteristics and delves into reasons for behavior and trends. Answers questions like “why” and “how.”
When you use both quantitative and qualitative data together, you can complete a more well-rounded analysis and make better research and business decisions.
Advantages and Disadvantages of Qualitative Data
While both types are important to understanding the full picture of your data, each has some important advantages and disadvantages.
Advantages
Deep Insights: Offers a nuanced and detailed understanding of customer opinion and experience.
Versatility: Enables you to follow new lines of thought and explore unexpected trends.
Understanding Context: Qualitative data captures the context behind data points making it easier to understand findings.
Disadvantages
Time Intensive: The process of collecting and analyzing qualitative data can take significantly more time than with quantitative data.
Subjectivity: Can be impacted by the researcher’s point of view and lead to biased interpretations.
Limited Generalability: Qualitative data findings may not always be applicable to wider populations.
Now that we know what qualitative data is, what types of qualitative data can we collect to get valuable insights to our customers? It’s important to remember that setting clearly defined research objectives helps in guiding the qualitative data collection and analysis processes, ensuring that the data collected effectively answers your research questions.
11 Types of Qualitative Data
Here are the top 11 types of qualitative data types:
Interviews
Focus groups
Surveys with open-ended questions
Observations
Social Media Posts
Customer Feedback
Case Studies
Diaries or Journals
Audio Recordings
Video Recordings
Textual Analysis
Many types of qualitative data can be collected. Let's take a closer look at each one.
1. Interviews
Interviews are structured or semi-structured conversations where a researcher asks open-ended questions to gather insights from participants. These can be conducted face-to-face, over the phone, or via video conferencing. Interviews are designed to explore participants’ thoughts, feelings, experiences, and motivations in detail.
Interviews are a data collection method used to gather in-depth customer insights from participants.
Example
Imagine you’re about to release a new product and want to understand potential customers’ expectations, motivations, and concerns about the thing you want to sell. You can conduct interviews with a diverse group of potential users to better understand their needs and preferences. For example, a technology company looking to develop a new smartphone might interview current users about their frustrations with their current devices and which features they wish to see in a new model. With the qualitative data collected, the company can tailor their product to better fit customer needs, thus improving user satisfaction and brand loyalty.
2. Focus Groups
Focus groups are guided group discussions that are led by a moderator. These sessions bring together several participants to exchange their views on a particular subject, product, or service and offer understanding into common perceptions, attitudes, and beliefs.
Qualitative data analysts often group qualitative data collected from focus groups to extract common themes and insights.
Example
Imagine you’re a beverage company that wants to launch a new flavor of a drink. You could conduct focus groups to collect reactions and preferences from participants. By listening to the discussions among the group, you can pinpoint common likes and dislikes among participants, uncover unexpected trends, and adjust your product before a widespread release.
3. Surveys with Open-Ended Questions
Surveys that include open-ended questions allow survey participants to respond in detail, using narrative answers instead of choosing from a set of predefined options. These types of surveys capture rich qualitative data that reveal the depth and complexity of a respondents’ thoughts.
There are various ways to collect qualitative data in surveys, using different methods and tools like open-ended questions, closed-ended questions, observations in natural settings, and even digital intelligence platforms that offer powerful research capabilities.
Example
An online retailer could use open-ended survey questions to ask customers about their shopping experience. The narrative responses may highlight specific areas of satisfaction or frustration, such as ease of navigation or problems with the checkout process, and can be used to make website improvements.
4. Observations
Observational research is the systematic observation and recording of behaviors and interactions in a natural setting. This type of qualitative data collection method captures data on how people behave in real-time, within a particular context or environment.
To extract deeper insights, qualitative data analysts often group qualitative data collected from these observations to understand behaviors and interactions.
Example
Imagine a retail store observes customers as they behave in their store, including noting how they navigate the space, which displays catch the most attention, and where they seem to encounter difficulties. These types of qualitative data collection methods can help stores adjust their layout to improve the shopping experience and increase sales.
5. Social Media Posts
Analyzing social media posts involves examining user-generated content on platforms like Twitter, Facebook, and Instagram. This qualitative data reflects public opinions, trends, and sentiments about brands, products, or topics.
Example
Imagine a fashion brand monitoring social media posts to see how customers react to a new line of clothing. Positive comments may point to elements they got right, while negative posts point to areas they could improve. Social media posts capture data in real-time, so responses directly from customers help brands stay responsive to their needs and emerging trends.
6. Customer Feedback
Customer feedback includes reviews, comments, and complaints that customers share via different channels, such as emails, support tickets, or feedback forms. This type of qualitative data collection method gives you direct feedback on how customers feel about your product or experience and areas you need to focus on.
Example
A software company might analyze customer support tickets to identify common issues users face. By addressing these recurring problems, the company can enhance its product, reduce support costs, and improve overall user experience.
7. Case Studies
Case studies are detailed investigations of a single subject, event, or organization. They provide in-depth insights into complex issues and can highlight best practices and lessons learned.
Qualitative research methods such as observations, in-depth interviews, and focus groups are often used in case studies to gather detailed insights.
Example
A marketing firm might develop a case study on a successful campaign for a client, detailing the strategies used, challenges faced, and results achieved. This qualitative data can guide future campaigns and demonstrate the firm's expertise to potential clients.
8. Diaries or Journals
Diary or journal studies ask participants to regularly record their thoughts, experiences, and activities over a period of time. This type of data capture changes and developments in their perspectives and behaviors over time.
Example
A healthcare provider might ask patients with chronic conditions to keep diaries documenting their daily symptoms and treatment responses. This qualitative data can reveal patterns and inform personalized care plans to improve patient experience and outcomes.
9. Audio Recordings
Audio recordings capture spoken words during interviews, focus groups, or customer service calls. They allow for detailed analysis of verbal communication and tone, and are a great lever to use when looking to optimize customer service metrics.
Example
A customer service department might analyze audio recordings of support calls to identify common issues and improve training programs. By understanding the language and tone used by both customers and representatives, the company can enhance its service quality.
10. Video Recordings
Video recordings capture visual and auditory data, providing a comprehensive view of behaviors, interactions, and non-verbal cues.
Example
A UX designer might use video recordings of users interacting with a prototype to identify usability issues. Observing users' facial expressions and gestures, along with their actions, helps pinpoint areas needing improvement.
11. Textual Analysis
Textual analysis involves examining written texts, such as emails, chat logs, and documents, to uncover themes and patterns. To make make this as streamlined as possible, you can choose a text analytics tool to quickly unlock insights from unstructured data.
Example
A company might analyze customer emails to identify frequently mentioned issues and suggestions. This qualitative data can inform product improvements and customer service strategies.
In Summary
Kapiche stands ready to assist you in harnessing the power of qualitative data. Our platform offers advanced tools to analyze and interpret qualitative data efficiently, helping you transform customer insights into actionable strategies. Watch an on-demand demo of Kapiche today to see how we can elevate your data analysis capabilities and drive impactful business decisions.
To illustrate the practical application of qualitative data analysis, we provide qualitative data analysis examples that showcase how different teams have successfully used these methods to gain customer insights, improve product decisions, and understand customer behaviors.
