In the last article of our series, we turn to qualitative research. If quantitative research shows us what is happening, qualitative reveals why. In healthcare, where decisions affect patient outcomes, understanding motivations, attitudes, and lived experiences is critical. It’s not enough to know that uptake is slow or discontinuation is high; we have a responsibility to uncover the barriers, perceptions, and daily realities that have so much influence on those outcomes.
Just as quantitative methodologies are evolving, qual is also being reshaped by technology. From AI-enabled analysis to mobile diaries and hybrid designs, the tools available today are making qualitative research more flexible, scalable, and essential to modern market research. It says so much that five years on from the pandemic, virtual qual research, which the industry had been previously slow to adopt, is no longer even considered a ‘new’ technology.
Qualitative Methodologies
- Face-to-face interviews or focus groups: exploring perceptions and motivations in depth
- Telephone or web-enabled interviews: reaching participants in dispersed geographies
- Virtual focus groups: engaging HCPs or patients in digital environments
- Online bulletin boards and communities: allowing ongoing discussion over days or weeks
- Participant observation and ethnographies: observing behaviour in real-world settings such as clinics, homes, or pharmacies
- Product placement and testing: capturing direct reactions to new packaging, devices, or treatments
- Mixed methodologies: combining approaches to balance reach with depth
Qual also has limitations. Its findings are not statistically generalisable, which means they need to be validated at scale. Researcher bias and participant subjectivity can influence results, and there can be heavy cultural biases with this in some markets. Studies are often resource-intensive, requiring careful recruitment and moderation. Consistency is another challenge, as interviews and groups are difficult to replicate exactly. And because qual often depends on self-reported behaviour, it may not always align with actual actions.
- Rich – In depth data
- Contextual understanding
- Flexibility
- Capturing the “participant’s voice”
- Uncovering new insights
- Holistic perspective
- Build empathy and understanding
- Variety of data collection options
- Subjectivity and Researcher Bias
- Lack of Generalizability
- Time-Consuming and Resource-Intensive
- Difficult to Replicate
- Ethical Issues
- Over-Reliance on Participant Self-Report
- Difficulty in Comparing Across Studies
Future Trends in Qualitative Research
- Integration with Technology: Digital tools are expanding how qual is conducted and analysed. AI-driven text and speech analysis can process transcripts, identify sentiment, and surface patterns across large datasets. Video and audio analysis tools detect tone, pauses, and emotional cues, adding layers of interpretation that traditional methods might miss. Online bulletin boards and digital ethnographies extend reach, making it easier to include diverse voices without geographic limits.
- Mobile and Real-Time Data Collection: Smartphones and wearables now enable real-time qualitative research. Patients can record video diaries about treatment experiences from home, while HCPs can share immediate reflections after a consultation. Wearables provide biometric data such as heart rate or sleep patterns, which can be paired with participants’ narratives. This immediacy reduces recall bias and creates a more authentic picture of the healthcare journey.
- Mixed Methodology and Hybrid Designs: The future of qual is increasingly hybrid. Studies often combine quant and qual in sequence, using surveys to size needs, qual interviews to explore them, and follow-up surveys to validate insights. Online communities paired with one-to-one interviews are another example, balancing group dynamics with personal depth. AI-enhanced pre-tasks, such as digital journaling or voice notes, give researchers richer material before discussions even begin. These hybrid designs offer the best of both worlds: statistical confidence and human context.
Conclusion
As we conclude this three-part series on modern methodologies, the message is clear: no single approach is sufficient in today’s research environment. Quant provides scale and prediction, qual delivers context and empathy, and together they form a complete picture. By adapting methodologies to fit the research question, the lifecycle stage, and the complexity of audiences, market researchers can generate insights that are both reliable and meaningful.
