Data analysis techniques in Qualitative Research
Data Analysis Techniques in Qualitative Research
Transforming raw qualitative data into meaningful insights requires systematic analysis. Here are the key approaches.
Thematic Analysis
Identifying, analyzing, and reporting patterns (themes) within data.
Process:
- Familiarize yourself with the data
- Generate initial codes
- Search for themes
- Review themes
- Define and name themes
- Produce the report
With Qualz.ai: Our Thematic Analysis (Grounded Emergence) automates this process, generating codes, categories, and themes in minutes.
Content Analysis
Systematically categorizing and quantifying textual content.
Best for: Large volumes of text, comparing across sources.
Narrative Analysis
Examining how people construct stories to make sense of their experiences.
Best for: Understanding identity, life transitions, and meaning-making.
With Qualz.ai: Our Narrative Arc Lens maps story progression and emotional turning points.
Grounded Theory
Building theory from data through systematic comparison and coding.
Process:
- Open coding
- Axial coding
- Selective coding
- Theory development
Phenomenological Analysis
Understanding lived experiences and their meaning.
Best for: Exploring subjective experiences of phenomena.
With Qualz.ai: Our Phenomenological Essence Lens captures emotional truths and perceptual nuances.
Framework Analysis
Organizing data into a matrix based on pre-defined themes.
Best for: Applied research with specific objectives.
Qualz.ai Multi-Lens Analysis
Beyond single-method analysis, Qualz.ai offers 14 specialized lenses that apply different analytical frameworks to your data:
- Jobs-to-Be-Done Analysis
- Sentiment & Emotion Spectrum
- Customer Journey Pain Points
- Persona Stem & Task Flow
- And more...