The main aim of qualitative research is to deeply look into the motivations, perceptions, and emotions that drive customer behavior. Learning about your customer is a must-do protocol for every organisation. Qualitative research learns about the “why” behind a customer’s complex decision making process. This human-centered approach unlocks rich insights that enable businesses to connect with their audience on a personal level.
What is Qualitative Research?
Qualitative research is a method that seeks to understand people’s experiences, thoughts, motivations, and emotions. It typically involves non-numerical data, gathered through open-ended methods such as interviews, focus groups, observations, and written or spoken customer feedback.
At Merren, we often define qualitative research as “the art of listening at scale.” It’s about creating space for customers to naturally express themselves in their own words, tone, and context.
In customer experience, qualitative research provides a window into the emotional and psychological drivers that shape customer decisions. It’s the difference between knowing what customers do and understanding why they do it.
Key characteristics of qualitative research
- Open-ended responses that capture nuance
- Exploratory approach to uncover patterns and motivations
- Smaller, targeted sample sizes focused on depth
- Contextual understanding placed within user journeys
- Narrative-driven data rich in real-world stories and experiences
Common Methods Used in Qualitative Research
Here are the examples of qualitative research that can be used for customer experience enhancement:
- Focus groups: A focus group has 6 to 8 customers who discuss collective opinions, emotional triggers, and conversational dynamics around a topic or experience. The group has a skilled moderator who guides the discussion to keep the topic relevant to the research objectives. A focus group stimulates dynamic discussions and provides a range of perspectives including emotional effects towards the topic.
- In-depth interviews: In-depth interviews (one-on-one) encourage deep exploration of individual experiences. These conversations can follow a theme or take a free-flow structure like a candid interview. These interviews are also conducted by a moderator in a structured or semi-structured format. It collects personal insights that might not emerge in group settings.
- Longitudinal observations: Longitudinal observations can occur over a long period of time. Longitudinal research observes customers interacting with products or services in real-time. This method helps researchers pick up non-verbal cues that other methods might miss due to subtleties.
- Ethnographic studies: Ethnography studies offer authentic insights on a select group of communities. Researchers immerse themselves in the customer’s environment to understand cultural and contextual factors influencing behavior. Ethnographic studies observe the day-to-day life of the customer and how the product or service fits into it. Ethnographic studies are particularly powerful in social studies where the objective is to understand the values, attitudes, and lifestyles of a social group.
- Open-ended surveys: Open ended customer feedback surveys can solicit candid feedback from customers via open-ended questions. Open ended responses can be in the form of expressive texts, audio recordings, videos (including photos for visual representation). Open-ended survey questions understand the “why” behind the quantitative score. However, they are effort intensive and often lead to short, vague, and incomplete responses. Merren CX has Smart AI probes which follow-up on open-ended question responses in such cases.
- Digital diary: In a digital diary, participants document their experience over time, revealing emotional shifts and evolving behaviors or feedback throughout their journey. Customers use a product and offer a regular review over a ‘digital diary’. A digital diary offers genuine insights from customers who are in direct interaction with the product. The onus is on the researcher to remind or nudge participants at particular times.
Qualitative Research In Customer Feedback
Integrating qualitative research for customer feedback gives more than just numbers:
- Understand emotional involvement of purchase: Explore a customers’ feelings and attitudes to identify the emotional factors influencing purchasing decisions.
- Identify pain points and opportunities: Discover specific areas where customers face challenges or have ‘customer delight’ opportunities. Use this data for targeted improvements.
- Align closely with customer expectations: Gaining a nuanced understanding of customer perspectives ensures that products, services, and communications align more closely with customer expectations.
Example:
A consumer electronics brand used Merren’s WhatsApp-based feedback survey asking customers:
“What was your biggest concern while buying our product?”
Responses revealed emotional themes around trust, support, and perceived value. Using these insights, the brand updated pricing messaging, customer support protocols, and warranty communication—resulting in reduced cart abandonment.
Curious about implementing similar surveys?
Visit Merren’s WhatsApp survey overview: How WhatsApp improves response rate.
Collect Qualitative Data with Superfast Survey Channels
Our AI-powered audio surveys let customers respond naturally capturing tone, emotion, and language in multiple formats and languages
Examples of Qualitative Research
1. Ad testing: decoding what resonates
Ever wonder why certain ad campaigns go viral? Qualitative research can reveal the answer. For instance, a skincare brand might learn that an ad’s humor landed well because it felt relatable, while another failed due to an unclear call-to-action. These insights help refine creative strategies that truly connect.
2. Concept evaluation: testing new ideas
Before launching a product or service, qualitative research gauges its appeal, clarity, and uniqueness. Imagine a tech company exploring a new app feature. Using in-depth interviews, they discover users love the idea but find the concept confusing without a tutorial. This feedback allows marketers to tweak messaging or design, ensuring a smoother rollout.
3. Customer journey mapping: highlight pain points and wins
Mapping the customer journey isn’t just about plotting touchpoints—it’s about understanding emotions at each step. Digital dairy, observational studies or shadowing, uncovers pain points (e.g., a confusing checkout process) and delight moments (e.g., a personalized thank-you note). A retailer might learn that free shipping delights customers more than discounts.
4. Price sensitive analysis: finding the sweet spot
Qualitative research digs into how customers perceive value and react to price points. For example, a subscription service might find through interviews that customers resist a $20/month fee not because it’s “too high,” but because they don’t see enough exclusive benefits. This insight can shift focus from cutting prices to boosting perceived value.
5. Brand perception: hearing the unfiltered truth
How do customers describe your brand? Using qualitative research, customers will tell you in their own words. A coffee chain might discover through focus groups that customers associate their brand with “cozy mornings” but wish for faster service. These authentic insights shape branding campaigns that align with customer sentiment.
6. Churn analysis: why customers leave
Understanding the reasons for customer churn can help prevent it. Qualitative research, such as exit interviews, might reveal that users abandoned a streaming service not because of price, but due to a clunky interface. Armed with data, customer experience teams can fix the issues.
7. Feature prioritization: what matters most
Not all features are created equal. Qualitative research helps identify which ones customers value and why. A fitness app company might learn through user workshops that a calorie tracker is a must-have, while a social sharing tool feels gimmicky. This clarity ensures development efforts align with customer priorities.
8. Packaging feedback: first impressions count
Packaging is often a customer’s first physical touchpoint with a product. Qualitative research explores reactions to design, appeal, and clarity. A snack brand might find that bold colors grab attention, but tiny font sizes confuse buyers about ingredients. These findings refine packaging for maximum impact.
9. Message testing: perfecting your pitch
Taglines, positioning statements, and marketing copy need to hit the mark. Qualitative research tests how these messages land with your audience. A car brand might discover that “Drive the Future” feels innovative to some but vague to others, prompting a sharper, more compelling alternative.
10. UX feedback: enhancing digital experiences
For digital products, qualitative research reveals how users navigate flows and interfaces. This includes usability testing or in-depth reviews. An e-commerce app might learn that a cluttered menu frustrates shoppers but a streamlined search bar delights them. These insights drive UX improvements that increase usage.
How to Analyze Qualitative Research
Analyzing qualitative data is about more than just reading customer responses: it’s about systematically observing patterns, emotions, and themes that drive behavior. Whether gathered from interviews, open-ended surveys, or voice notes, qualitative data requires thoughtful examination and interpretation.
Here’s a structured step-by-step guide to analyzing qualitative feedback for customer experience:
1. Gather all relevant data
Begin by collecting all relevant qualitative inputs such as:
- Open-ended survey responses
- Voice recordings and transcripts
- Field notes from interviews or focus groups
- Diary entries or chat conversations
Organize this data systematically so that each response is labeled, timestamped, and linked to its source (customer, journey stage, channel, etc.). If you’re working with video or audio, take note of non-verbal cues, tone, and pauses, which can enrich the context.
Tools like Merren’s audio surveys make this process easy by transcribing and categorizing spoken responses automatically.
2. Familiarize yourself with the data
Before jumping into codes or analysis, read or listen to the responses multiple times to acquaint yourself deeply with the content. This phase requires human interpretation and discretion.
Look for:
- Emotional tone
- Repeated phrases
- Unique customer stories
- Unexpected expressions of satisfaction or pain
3. Generate initial codes
Coding is the process of labeling segments of feedback based on the themes or concepts they represent. Codes can be:
- Inductive: Emerging directly from the data
- Deductive: Based on predefined frameworks, research objectives, or hypotheses
For instance:
- “Late delivery” → Logistics Issue
- “Loved the packaging” → Positive Unboxing Experience
Modern AI platforms like Merren can automatically generate codes based on frequently occurring topics, sentiments, and keywords, saving hours of manual work.
4. Review and refine themes
Once your data is coded, begin grouping similar codes under broader themes. Ensure that each theme is relevant to your research objective and is firmly grounded in the data.This step helps you uncover macro-level patterns in the data.
- Merge overlapping or similar themes
- Discard themes with weak evidence
- Use quotes or audio clips to support and illustrate each theme
Examples of themes might include:
- Frustration with product setup
- Delight with customer service
- Uncertainty about return policy
5. Analyze and Interpret the Data
Now it’s time to derive meaning from the patterns and connections you’ve uncovered. Ask:
- What relationships or contrasts exist between themes?
- How do different customer segments express different sentiments?
- What surprises or contradictions emerged?
Use methods such as:
- Thematic Analysis: For identifying recurring themes
- Narrative Analysis: For interpreting customer stories
- Grounded Theory: For developing theories directly from data
6. Produce the final report
Your analysis is only valuable if it’s communicated effectively. Create a structured report or dashboard that:
- Presents key themes and insights clearly
- Uses direct customer quotes or voice snippets as evidence
- Addresses your original research questions
- Offers practical takeaways for product, marketing, or CX teams
The goal is to tell a compelling story that connects customer voices to business impact.
Want to turn qualitative feedback into action? Book a free demo with Merren to see how our platform does it—automatically and at scale.
How to Report Qualitative Research Effectively ?
Use qualitative research when you want to deeply understand the “why” and “how” behind people’s attitudes, behaviors, and decisions. It’s most useful when you’re looking for depth over breadth, and especially in the following scenarios:
Ideal situations for qualitative research:
- Exploring a new or poorly understood topic
When there’s little existing data, qualitative research helps uncover nuances and unknown variables. - Understanding motivations and emotions
Perfect for diving into why consumers feel or act a certain way—especially for brand perception, product experiences, or social behaviors. - Generating hypotheses
Before running a large-scale quantitative study, qualitative methods help shape hypotheses and questionnaire design. - Testing new ideas or concepts
Great for early-stage product or campaign testing—to explore reactions, language, barriers, and areas of confusion. - Mapping decision-making journeys
Useful in complex purchases or behavior change situations—like buying a car, choosing a financial service, or adopting a new habit. - Uncovering language and semiotics
If you’re trying to get the right tone, communication style, or cultural meaning—qualitative gives you the real consumer voice. - Segmenting by mindset
Goes beyond demographics to understand attitudes, needs, and mental models that drive behavior.
Techniques Used in Qualitative Research
- Card sorting: In card sorting technique, participants organize topics or concepts into categories that make sense to them. This reveals their mental models and information architecture.
- Projective techniques:
- Word Association: Participants respond with the first word that comes to mind when presented with a stimulus word, uncovering subconscious associations.
- Sentence Completion: Participants complete incomplete sentences, revealing underlying thoughts and feelings.
- Word Association: Participants respond with the first word that comes to mind when presented with a stimulus word, uncovering subconscious associations.
- Laddering (why-why analysis): Laddering is an interviewing technique where researchers probe participants for deeper insights. It is designed to trace the underlying attitudes, feelings, and emotions about a subject
- Role-playing & simulations: Participants act out scenarios to project their thoughts, feelings, and attitudes. Researchers explore their behaviors in a controlled setting.
- Online communities & bulletin boards: Researchers use digital platforms to engage participants in discussions over time. You’ll obtain in-depth exploration of topics and community dynamics.
Combine Quantitative Research and Quantitative Research
Combining qualitative research and quantitative approaches enhances the validity of research findings by cross-verifying data through multiple methods. The combination is particularly powerful in measuring what (quantitative)and how much (quantitative) as well as the whys (qualitative).
Use Cases:
- Concept validation: Use qualitative insights to refine concepts before quantitative testing.
- Segmentation studies: Use qualitative methods to understand segment characteristics, followed by quantitative analysis to measure segment sizes.
- Customer Experience (CX) research: Combining methods to explore and quantify customer satisfaction and pain points.
Common Pitfalls to Avoid in Qualitative Research
- Leading or biased questions
Framing questions in this way can skew results.
Example: “Don’t you think this product is useful?” instead of “What do you think about this product?” - No clear research objectives
Without well-defined goals, data becomes haphazard and overwhelming. Always establish clear research questions before starting the study. - Over-generalizing conclusions
Qualitative research relies on small, non-representative samples. It makes it unsuitable for statistical generalizations. Instead, use qualitative insights to develop hypotheses or complement quantitative research. - Ignoring researcher bias
Researcher’s bias or personal interpretations can affect data analysis. Use multiple researchers for cross-validation to reduce bias. - Poor participant selection
Choosing the wrong participants or the number of participants who are not statistically significant can give misrepresented data. Calculate your survey sample size here with Merren’s sample size calculator. - Ethical considerations
Failing to obtain informed consent, protect confidentiality, or handle sensitive topics can compromise research integrity. Always prioritize participant rights and privacy. - Weak data analysis methods
Simply summarizing responses without thematic coding or deep interpretation can lead to superficial insights. Use structured qualitative analysis techniques like thematic analysis, grounded theory, or narrative analysis. - Over-reliance on a single method
Using only one qualitative technique (e.g., interviews) may limit perspectives. Multiple methods, such as focus groups, ethnography, and online communities, can enhance insights. - Failing to report insights effectively
Presenting findings without context, structure, or supporting quotes may weaken impact. Use storytelling, personas, journey maps, and visuals to communicate findings clearly.
Offline vs Online Qualitative Research: What’s the Difference?
Offline and inline qualitative research can have two different outcomes. However, both are valuable but they work very differently. The choice can significantly impact the speed, cost, depth, and reach of your research. Let’s break down what each method involves, and where one might work better than the other.
Offline qualitative research
Traditional qualitative research includes in-depth face-to-face interviews, focus groups in a facility, or ethnographic immersions in homes or workplaces. The human connection here is palpable: researchers can observe body language, build rapport, and probe in real-time.
Pros:
- Rich contextual understanding – You can observe surroundings, body language, and subtle cues that inform deeper insights.
- Better for complex tasks – Product trials, sensory testing, or usability studies work well when conducted physically.
- Ideal for building trust – Especially in emotionally charged or sensitive topics, in-person settings can foster openness.
Cons:
- Scalability is limited – Each session needs a physical setup, moderator, logistics making it time- and cost-intensive.
- Geographical constraints – You’re often limited to a few urban locations unless you have the budget and time to go truly wide.
- Hard to recruit niche audiences – Specialized segments (like early adopters or rural consumers) may be harder to bring into a facility.
Online qualitative research
Online qualitative research has grown dramatically especially in 2025. It includes video depth interviews, online focus groups, survey channels, and even mobile ethnography. Participants join from anywhere, and conversations are captured digitally.
Pros:
- Far more scalable – You can easily talk to people across cities and countries digitally.
- Faster turnaround – No travel or logistics. Recruitment and interviews can happen in days instead of weeks.
- Better for niche audiences – Hard-to-reach groups (like gamers, crypto investors, or rural youth) are more accessible online.
- Built-in transcripts and recordings – Saves time on analysis and lets multiple stakeholders observe without disrupting the session.
Cons:
- Loss of physical cues – You can’t read body language or observe physical context as easily.
- Tech issues – Connectivity problems or digital fatigue can affect session quality.
- May feel transactional – Some participants may not open up as easily in an online setting, especially without skilled moderation.
The Scale Trade-Off
The biggest trade-off between offline and online qualitative research is scale. Offline methods are great for deep, immersive insights—but can only be run with small samples, in limited locations, and at a high cost.
Online qualitative opens the door to geographic and demographic scale, enabling research teams to engage diverse, distributed audiences quickly and cost-effectively. While it may lack some of the tactile richness of offline work, smart tech and good moderation can close much of that gap.
The Use of Digital Methods for Qualitative Research
1. Mobile ethnography and remote diaries
Mobile ethnography can collect real-time, in-context insights. Participants document their experiences using smartphones. Remote diaries offer a longitudinal approach, capturing behavioral patterns, emotions, and decision-making processes over time. Mobile ethnography provides unfiltered data while minimizing researcher interference.
2. Voice and video-based feedback
Digital qualitative research leverages voice and video responses. Merren’s audio surveys can capture tone, emotion, and non-verbal cues that text-based methods often miss. Video diaries, asynchronous interviews, and voice notes enhance data quality. Using Merren, an AI-powered customer experience platform, researchers can analyze customer sentiment and behavior authentically.
3. AI-driven moderation and analysis
AI-powered tools streamline qualitative research by automating transcription, sentiment analysis, and thematic coding. Chatbots and virtual moderators facilitate real-time discussions. AI analysis can detect key patterns, highlight key terms and reduce the effort required for manual analysis.
4. Native WhatsApp surveys
WhatsApp has a high open rate- more than 90%. This makes WhatsApp a superfast platform to collect customer feedback across industries. Learn how to make WhatsApp surveys here in less than 5 minutes, free on Merren CX.
Frequently Asked Questions on Qualitative Research
What is qualitative research in simple terms?
Qualitative research is a way to understand how and why people think and feel using open-ended methods like interviews or voice feedback.
What are examples of qualitative research?
In-depth interviews, focus groups, Merren’s AI-powered audio surveys, WhatsApp surveys, and diary studies.
How does qualitative feedback help brands?
By revealing motivations, emotions, and perceptions—helping brands improve messaging, experience design, and loyalty.
What tools are used in qualitative research today?
Platforms like Merren that collect and analyze voice, chat, and written feedback at scale using AI and NLP.
Conclusion
In a marketplace crowded with options, understanding emotion—and context—is often what separates loyalty from churn. Quantitative data tells you what is happening. Qualitative research tells you why.
With Merren, brands can collect feedback across voice, chat, and survey platforms that customers prefer—and turn unstructured feedback into clear, actionable insights. It’s qualitative research, scaled and powered by AI.
Merren is an AI-driven customer experience tool that enables researchers, CX leaders and marketers to create campaigns that need no technical expertise. Create custom made qualitative research campaigns for free here.