Qualitative Data Analysis

The Main Types of Qualitative Data Analysis IMPACT RATING (IR) 6/10

Content Analysis

Content analysis is a qualitative 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.

Conduct content analysis manually (which can be time-consuming) or use analysis tools like Lexalytics to reveal communication patterns, uncover differences in individual or group communication trends, and make broader connections between concepts.

How content analysis can help your team?

Content 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 analyse and group results based on the emotion expressed in texts.

Some other examples of content analysis include:

• Analysing brand mentions on social media to understand your brand's reputation

• Reviewing customer feedback to evaluate (and then improve) the customer and user experience (UX)

• Researching competitors’ website pages to identify their competitive advantages and value propositions

• Interpreting customer interviews and survey results to determine user preferences, and setting the direction for new product or feature developments

Thematic Analysis

Thematic analysis helps you identify, categorise, analyse, and interpret patterns in qualitative study data, and can be done with tools like Dovetail and Thematic.

While content analysis and thematic analysis seem similar, they're different in concept: 

• Content analysis can be applied to both qualitative and quantitative data, and focuses on identifying frequencies and recurring words and subjects

• Thematic analysis can only be applied to qualitative data, and focuses on identifying patterns and themes

NB There are different types of Thematic Analysis.  The method you use MUST be referenced for transparency

How thematic analysis can help your team

Thematic analysis can be used by pretty much anyone: from product marketers, to customer relationship managers, to UX researchers.

For example, product teams use thematic analysis to better understand user behaviors and needs and improve UX. Analysing customer feedback lets you identify themes (e.g. poor navigation or a buggy mobile interface) highlighted by users and get actionable insight into what they really expect from the product. 

Notable authors: Virginia Braun & Victoria Clarke (2006), Nowell, Norris, White, & Moules (2017)  

Interpretative Phenomenological Analysis (IPA)

IPA occupies a specific niche within qualitative data analysis. It's not a general analysis method like thematic analysis or content analysis, but rather a focused approach designed to explore a particular aspect of qualitative data. IPA is a powerful tool for qualitative researchers who want to gain a deep understanding of how individuals experience specific phenomena. It's particularly valuable when exploring subjective meanings and individual interpretations within the context of lived experiences. 

Here's how IPA fits into data analysis for qualitative research:

• Focus on Lived Experiences: IPA prioritises understanding participants' subjective experiences of a phenomenon. It delves into how individuals make sense of and interpret their own experiences.

• Idiographic Approach: IPA emphasises the unique nature of each participant's experience. While it might identify common themes across participants, the core focus remains on individual interpretations and meanings.

• Detailed Analysis: IPA involves a rigorous and detailed analysis of interview transcripts. Researchers carefully examine the language used, emotional tones, and narrative flow to understand the participant's perspective.

• Double Hermeneutics: IPA employs a concept called "double hermeneutics." This refers to the process of interpreting the participant's interpretation of their experience. The researcher adds their own interpretation based on their understanding of the phenomenon and relevant theory.

When to Use IPA:

• Exploring Subjective Meanings: If your research aims to understand how individuals make sense of a specific experience, such as coping with a chronic illness or dealing with job loss, IPA is a well-suited approach.

• In-Depth Understanding: When you need to go beyond surface-level descriptions and delve into the rich tapestry of individual experiences, IPA offers a valuable lens for analysis.

Key differences between IPA and Thematic Analysis

Narrative Analysis

Narrative analysis is a method used to interpret research participants’ stories—things like testimonials, case studies, focus groups, interviews, and other text or visual data—with tools like Delve and AI-powered ATLAS.ti.

Some formats don’t work well with narrative analysis, including heavily structured interviews and written surveys, which don’t give participants as much opportunity to tell their stories in their own words.

Narrative analysis general looks at experiences over time where as IPA is more about individual emotions indepth experiences over events.

Notable authors: Catherine Kohler Riessman, Jerome Bruner 

Discourse Analysis

Discourse analysis is a valuable tool for researchers who want to understand the deeper meaning behind language use in a social context. Here are some key reasons to use discourse analysis:

• Uncover Hidden Meanings: Language often conveys more than the literal meaning of words. Discourse analysis helps reveal underlying assumptions, power dynamics, and ideologies embedded within language use.

• Analyse Social Issues: Discourse shapes how we understand social issues like race, gender, and class. Analysing how these issues are discussed in different contexts can expose inequalities and power structures.

• Critique Representation: Discourse analysis helps critique how social groups and ideas are represented in media, political discourse, and other forms of communication.

• Understand Power Dynamics: Language use can reflect and reinforce power dynamics. Discourse analysis helps identify how power is exercised through language choices and silences.

• Explore Cultural Contexts: Language use varies across cultures. Discourse analysis helps understand how cultural values and beliefs are reflected in communication styles and practices.

Grounded Theory

When to Leverage Grounded Theory: A Strategic Choice

Grounded theory offers a unique approach to qualitative research, particularly valuable in specific scenarios:

• Exploring Uncharted Territory: When existing theories are scarce or the research area is entirely new, grounded theory allows you to build theory directly from the data. It's ideal for uncovering fresh insights and generating novel theoretical frameworks that can guide future studies.

• Understanding Complex Processes: This method excels at untangling intricate processes or phenomena. For instance, you could use it to understand how individuals make financial decisions or how social media platforms influence political movements. By systematically analysing data, grounded theory helps identify key stages and contributing factors within the process.

• Generating New Knowledge: If your research aims to break new ground and offer fresh perspectives, grounded theory is well-suited. It prioritises developing original insights based on the data, potentially leading to groundbreaking theoretical contributions to your field.

Here are some illustrative examples where grounded theory shines:

• Studying the experiences of patients navigating a newly discovered disease.

• Demystifying the decision-making process of entrepreneurs when launching startups.

• Unraveling how social media platforms impact the way people engage in political activism.