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Back to guides Qualitative data uncovers valuable insights that can be used to improve the user and customer experience. But how exactly do you measure and analyze data that isn't quantifiable? There are different qualitative data analysis methods to help you make sense of qualitative feedback and customer insights, depending on your business goals and the type of data you've collected. PX insights and behavior analytics Before you choose a qualitative data analysis method for your team, you need to consider the available techniques and explore their use cases to understand how each process might help your team better understand your users. This guide covers five qualitative analysis methods to choose from, and will help you pick the right one(s) based on your goals. What is qualitative data analysis?Qualitative data analysis (QDA) is the process of organizing, analyzing, and interpreting qualitative data—non-numeric, conceptual information and user feedback—to capture themes and patterns, answer research questions, and identify actions to take to improve your product or website. 💡 Qualitative data often refers to user behavior data and customer feedback. Use product experience insights software—like Hotjar's Observe and Ask tools—to capture qualitative data with context, and learn the real motivation behind user behavior. Hotjar’s feedback widget lets your customers share their opinions 5 qualitative data analysis methods explainedHere are five methods of qualitative data analysis to help you make sense of the data you've collected through customer interviews, surveys, and feedback:
Let’s look at each method one by one, using real examples of qualitative data analysis. 1. Content analysisContent analysis is a research method that examines and quantifies the presence of certain words, subjects, and concepts in text, image, video, or audio messages. The method transforms qualitative input into quantitative data to help you make reliable conclusions about what customers think of your brand, and how you can improve their experience and opinion. You can conduct content analysis manually or by using tools like Lexalytics to reveal patterns in communications, uncover differences in individual or group communication trends, and make connections between concepts. Content analysis was a major part of our growth during my time at Hypercontext. [It gave us] a better understanding of the [blog] topics that performed best for signing new users up. We were also able to go deeper within those blog posts to better understand the formats [that worked]. Senior Demand Gen Manager, TestBox How content analysis can help your teamContent analysis is often used by marketers and customer service specialists, helping them understand customer behavior and measure brand reputation. For example, you may run a customer survey with open-ended questions to discover users’ concerns—in their own words—about their experience with your product. Instead of having to process hundreds of answers manually, a content analysis tool helps you analyze and group results based on the emotion expressed in texts. Some other examples of content analysis include:
Content analysis benefits and challengesContent analysis has some significant advantages for small teams:
On the downside, content analysis has certain limitations:
2. Thematic analysisThematic analysis helps to identify, analyze, and interpret patterns in qualitative data, and can be done with tools like Dovetail and Thematic. While content analysis and thematic analysis seem similar, they're different in concept:
How thematic analysis can help your teamThematic analysis can be used by pretty much anyone: from product marketers, to customer relationship managers, to UX researchers. For example, product teams can use thematic analysis to better understand user behaviors and needs, and to improve UX. By analyzing customer feedback, you can identify themes (e.g. ‘poor navigation’ or ‘buggy mobile interface’) highlighted by users, and get actionable insight into what users really expect from the product. Thematic analysis benefits and challengesSome benefits of thematic analysis:
And some drawbacks of thematic analysis:
3. Narrative analysisNarrative analysis is a method used to interpret research participants’ stories—things like testimonials, case studies, interviews, and other text or visual data—with tools like Delve and AI-powered ATLAS.ti. Some formats narrative analysis doesn't work for are heavily-structured interviews and written surveys, which don’t give participants as much opportunity to tell their stories in their own words. How narrative analysis can help your teamNarrative analysis provides product teams with valuable insight into the complexity of customers’ lives, feelings, and behaviors. In a marketing research context, narrative analysis involves capturing and reviewing customer stories—on social media, for example—to get more insight into their lives, priorities, and challenges. This might look like analyzing daily content shared by your audiences’ favorite influencers on Instagram, or analyzing customer reviews on sites like G2 or Capterra to understand individual customers' experiences. Narrative analysis benefits and challengesBusinesses turn to narrative analysis for a number of reasons:
However, this data analysis method also has drawbacks:
4. Grounded theory analysisGrounded theory analysis is a method of conducting qualitative research to develop theories by examining real-world data. The technique involves the creation of hypotheses and theories through the collection and evaluation of qualitative data, and can be performed with tools like MAXQDA and Delve. Unlike other qualitative data analysis methods, this technique develops theories from data, not the other way round. How grounded theory analysis can help your teamGrounded theory analysis is used by software engineers, product marketers, managers, and other specialists that deal with data to make informed business decisions. For example, product marketing teams may turn to customer surveys to understand the reasons behind high churn rates, then use grounded theory to analyze responses and develop hypotheses about why users churn, and how you can get them to stay. Grounded theory can also be helpful in the talent management process. For example, HR representatives may use it to develop theories about low employee engagement, and come up with solutions based on their findings. Grounded theory analysis benefits and challengesHere’s why teams turn to grounded theory analysis:
Some drawbacks of grounded theory are:
5. Discourse analysisDiscourse analysis is the act of researching the underlying meaning of qualitative data. It involves the observation of texts, audio, and videos to study the relationships between the information and its context. In contrast to content analysis, the method focuses on the contextual meaning of language: discourse analysis sheds light on what audiences think of a topic, and why they feel the way they do about it. How discourse analysis can help your teamIn a business context, the method is primarily used by marketing teams. Discourse analysis helps marketers understand the norms and ideas in their market, and reveals why they play such a significant role for their customers. Once the origins of trends are uncovered, it’s easier to develop a company mission, create a unique tone of voice, and craft effective marketing messages. Discourse analysis benefits and challengesDiscourse analysis has the following benefits:
But it also has drawbacks:
Which qualitative data analysis method should you choose?While the five qualitative data analysis methods we list above are aimed at processing data and answering research questions, these techniques differ in their intent and the approaches applied. Choosing the right analysis method for your team isn't a matter of preference—selecting a method that fits is only possible when you define your research goals and have a clear intention. Once you know what you need (and why you need it), you can identify an analysis method that aligns with your objectives. FAQs about qualitative data analysis methodsWhich of the following is not a qualitative data collection method?Hence, Thematic analysis case study and disclosure analysis are related to qualitative research except for the Survey method.
What are the 4 main methods in collecting qualitative data?The methods mentioned in the blog – interviews, surveys, group discussions, and observations are the most widely and commonly used qualitative data collection methods.
Which of the following is not a qualitative method?Loved by our community. What qualitative research is not: Quantifiable: Surveys, even those that include open‐ended questions, are never qualitative, neither is putting numbers to frequencies of word occurrences.
What are the 5 methods to analyze qualitative data?5 qualitative data analysis methods explained. Content analysis.. Thematic analysis.. Narrative analysis.. Grounded theory analysis.. Discourse analysis.. |