Qualitative Consumer Research

Introduction

Qualitative consumer research is the systematic study of how people experience, interpret, discuss, and use products, services, brands, and technologies. Whereas quantitative research is primarily concerned with measuring incidence, magnitude, and relationships among variables, qualitative research seeks to understand meanings, motivations, practices, tensions, and contexts. It asks questions such as: What problem is the consumer actually trying to solve? How does a product fit into everyday life? Why do users abandon a feature despite claiming to value it? What language do consumers use to describe an unmet need?

For product managers, qualitative research is especially valuable because product decisions are often made under conditions of incomplete information. Interviews, focus groups, observation, ethnography, diary studies, contextual inquiry, and online communities can reveal needs that consumers cannot easily express in a survey. They can also expose differences between stated attitudes and actual behaviour. However, qualitative research is not an informal conversation or a small-scale substitute for statistical research. It is a disciplined process involving research design, sampling, facilitation, recording, interpretation, coding, synthesis, and ethical judgement.

This chapter develops a practical and critical framework for designing and conducting qualitative consumer research and converting rich evidence into defensible product insights.

Learning Objectives

By the end of this chapter, a learner should be able to:

1. Explain the purpose, assumptions, and appropriate uses of qualitative consumer research.
2. Select among interviews, focus groups, observation, ethnography, diary studies, contextual inquiry, and online communities.
3. Develop a research brief, sampling plan, discussion guide, and fieldwork protocol.
4. Conduct qualitative sessions using effective questioning, probing, listening, and moderation techniques.
5. Code transcripts and field notes systematically and synthesize findings into themes, insights, and product implications.
6. Assess quality, bias, ethics, privacy, accessibility, and limitations in qualitative research.
7. Communicate qualitative findings without overstating what the evidence can support.

1. The Nature and Logic of Qualitative Inquiry

Qualitative research is generally associated with an interpretive orientation. It treats consumer behaviour as meaningful and situated rather than merely as a response to isolated variables. A consumer may purchase a premium product not only because of functional performance, but also because the product signals competence, reduces anxiety, supports identity, or creates a socially valued ritual.

Three characteristics distinguish qualitative inquiry:

• Depth: It explores how people explain experiences in their own words.
• Context: It examines behaviour in social, physical, cultural, and technological settings.
• Flexibility: The researcher can pursue unexpected but relevant issues that emerge during fieldwork.

Qualitative research commonly uses purposive sampling. Participants are selected because they possess relevant experiences, characteristics, or perspectives—not because they statistically represent the entire market. The aim is usually to achieve information richness and conceptual coverage. A study may include current users, lapsed users, non-users, extreme users, purchasers, decision-makers, or service employees, depending on the research question.

Exploratory, descriptive, and evaluative purposes

Qualitative methods can support several product-management purposes:

Qualitative evidence can generate hypotheses, explain quantitative patterns, improve survey instruments, identify language for positioning, and guide product discovery. It should not normally be used to estimate market incidence—for example, to claim that “62% of customers experience this problem”—unless a suitable quantitative design supports that claim.

Epistemological caution

Participants’ accounts are valuable evidence, but they are not transparent recordings of reality. Memory is selective, people may present themselves favourably, and consumers may rationalise decisions after the event. Behaviour is also influenced by the research setting. Consequently, the researcher should compare what participants say with what they do, examine contradictions, and treat findings as interpretations grounded in evidence rather than as unquestionable facts.

2. Choosing the Appropriate Method

The method should follow the decision problem, not researcher preference. A useful selection process considers four questions:

1. Is the behaviour primarily verbal, observable, routine, or socially negotiated?
2. Does the research require individual privacy or group interaction?
3. Must the researcher see the behaviour in its natural setting?
4. Is the study a single encounter or does it require evidence over time?

In-depth interviews

An in-depth interview is a guided conversation with one participant. It is appropriate for sensitive subjects, complex decision journeys, specialist users, and situations in which social influence may inhibit disclosure. Interviews allow the researcher to probe personal meanings and reconstruct sequences of events.

A good interview is semi-structured: it has a consistent topic framework but permits relevant follow-up. The interviewer should ask open questions, use neutral probes, and distinguish experience from opinion. “Tell me about the last time you used the service” is generally stronger than “Do you like the service?” because it invites concrete evidence.

Useful probes include:

• “What happened next?”
• “Can you give me an example?”
• “How did that affect your decision?”
• “What made that difficult?”
• “What were you expecting at that point?”

Avoid leading questions, multiple questions in one sentence, premature interpretation, and excessive silence-filling. Interviewers should not defend the product or correct the participant.

Focus groups

A focus group is a moderated discussion among several participants who share a relevant relationship to the research topic. Its distinctive value lies in interaction: participants can stimulate memories, challenge assumptions, reveal social norms, and show how language and opinions are negotiated publicly.

Focus groups are useful for exploring reactions to concepts, category language, cultural meanings, and shared experiences. They are less suitable for highly sensitive topics, detailed individual journeys, or behaviours that participants may conceal in front of others. Group dynamics can distort findings through conformity, status differences, dominant speakers, or moderator effects.

A skilled moderator establishes ground rules, balances participation, uses activities selectively, and distinguishes consensus from social pressure. Segmentation is important. Mixing expert and novice users, or managers and junior employees, may prevent candid discussion.

Observation and ethnography

Observation records behaviour, interactions, objects, routines, and environments. It is particularly valuable when consumers cannot fully articulate habitual or embodied behaviour. Ethnography extends observation through sustained engagement with the social and cultural context of consumption. It may involve home visits, workplace immersion, mobile observation, cultural analysis, and the study of artefacts such as screenshots, receipts, packaging, or workarounds.

Observation should record both description and interpretation, while keeping them separate. “The participant opened three applications before finding the account number” is an observation. “The participant is confused” is an interpretation requiring supporting evidence. Field notes should document time, setting, actors, actions, quotations, interruptions, material conditions, and the researcher’s own reactions.

Ethnography is demanding in time, access, analysis, and ethics. Short visits can provide useful contextual insight, but they should not be labelled as full ethnography if they do not support sustained cultural understanding.

Diary studies

A diary study collects participant-generated accounts over a period of time. Entries may be written, audio-recorded, photographed, or submitted through a research platform. Diary studies are useful for episodic, emotional, private, or distributed experiences such as commuting, caregiving, budgeting, medication routines, or repeated application use.

Diary tasks must be simple and specific. Participants may be asked to record each relevant episode, what they were trying to accomplish, what occurred, how they felt, and what they did next. A short pilot can identify burdensome instructions. Researchers should expect uneven compliance and use reminders without becoming intrusive.

Diary data provides longitudinal depth but is not automatically naturalistic: participants may alter behaviour because they are documenting it. Entries also vary in detail and literacy demands, so accessible alternatives should be offered.

Contextual inquiry

Contextual inquiry combines observation and interviewing in the environment where a task occurs. The researcher observes the participant performing a real activity and asks brief questions at appropriate moments. The method is especially useful for workplace software, service journeys, retail processes, and products involving tools, interruptions, or collaboration.

A common principle is “go and see,” followed by inquiry into actual actions rather than abstract preferences. The researcher should avoid taking over the task. Questions such as “What are you looking for here?” or “Why did you record that on paper?” reveal goals, assumptions, and workarounds.

Online communities and digital methods

Online communities may be temporary research spaces or longer-term panels in which participants discuss experiences, complete activities, upload images, and respond to one another. They can reach geographically dispersed participants and support reflection over several days or weeks. They are useful for exploring language, routines, emerging trends, and peer influence.

Researchers must distinguish recruited research communities from naturally occurring social-media data. Public availability does not automatically mean ethical permission for unrestricted use. Online identity may be uncertain, platform norms vary, and text may be decontextualised. Researchers should consider consent, traceability, screenshots, data retention, moderation, and the risk of exposing participants through quotations.

3. Designing a Qualitative Study

Begin with a decision-oriented research brief

A research brief should state:

• the product or business decision;
• the knowledge gap preventing that decision;
• the target population and relevant segments;
• the research objectives;
• the proposed method and rationale;
• recruitment criteria and exclusions;
• timeline, budget, risks, and deliverables;
• intended users of the findings.

A weak objective says, “Understand customers.” A stronger objective says, “Understand how first-time users decide whether to trust automated financial recommendations during onboarding, and identify moments that create reassurance or abandonment.”

Sampling and saturation

Qualitative samples are designed for relevance and variation. A sampling matrix can specify dimensions such as experience level, use frequency, need state, geography, accessibility requirement, or purchasing role. Researchers should include meaningful contrast rather than simply recruiting convenient participants.

Saturation is reached when additional data no longer adds important dimensions to the developing explanation. Saturation is not a mechanical sample-size rule. It depends on the narrowness of the question, participant heterogeneity, method quality, and analytic ambition. Researchers should document how saturation was assessed rather than claiming it automatically.

Recruitment screeners should identify eligibility without revealing so much about the hypothesis that participants rehearse desired answers. Incentives should compensate time and inconvenience, not pressure economically vulnerable people to disclose sensitive information.

The discussion guide

A discussion guide normally contains:

1. introduction, consent, and rapport-building;
2. participant background relevant to the topic;
3. recent concrete experiences;
4. detailed exploration of needs, decisions, barriers, and workarounds;
5. reactions to stimuli or concepts, if appropriate;
6. reflection and prioritisation;
7. closing questions and explanation of next steps.

The guide is a flexible instrument, not a script to be read mechanically. Questions should move from broad and non-threatening to specific and evaluative. Stimuli should be clear, comparable, and presented in a sequence that minimises bias. If concepts are compared, order should be rotated where practical.

4. Conducting High-Quality Fieldwork

The researcher’s role includes facilitator, listener, observer, and ethical steward. Rapport does not mean agreeing with the participant; it means creating conditions in which the participant can speak candidly.

Interviewing and moderation skills

Effective researchers:

• listen for both content and emotion;
• tolerate pauses;
• ask one question at a time;
• seek specific episodes rather than general claims;
• notice contradictions without accusation;
• use the participant’s vocabulary;
• separate personal curiosity from research relevance;
• monitor time without rushing important material.

A useful interviewing sequence is: broad invitation → concrete example → event reconstruction → meaning and consequence → improvement or ideal state. For example, a product manager investigating failed delivery attempts might ask what happened, what the participant expected, what they did next, how the event affected trust, and what a better process would look like.

Reflexivity

Researchers influence data through identity, assumptions, wording, status, and interpretation. Reflexivity is the deliberate examination of that influence. A reflexive memo may record expectations before fieldwork, moments of surprise, emotional reactions, possible leading behaviour, and alternative explanations. Team debriefs should challenge premature consensus.

Recording and field documentation

With consent, sessions may be audio- or video-recorded and transcribed. Notes should still be taken because context, gestures, environment, and nonverbal events may not be fully captured. Transcripts should identify speakers, meaningful pauses where relevant, and the level of transcription required by the analysis. Automated transcription must be checked, particularly for accents, technical terms, overlapping speech, and code-switching.

5. From Raw Data to Themes and Insights

Qualitative analysis is an iterative movement between data, codes, concepts, and the research question. It is not merely highlighting attractive quotations.

Data preparation

Organise transcripts, field notes, diary entries, photographs, artefacts, and metadata in a controlled system. Remove unnecessary personal identifiers. Assign participant IDs and maintain a separate access-controlled key if identity must be retained.

Coding

A code is a concise label attached to a meaningful segment of data. Codes may be descriptive (“uses spreadsheet to track orders”), process-oriented (“checks status repeatedly”), emotional (“anxious before confirmation”), or interpretive (“trust depends on visible accountability”).

A practical coding sequence is:

1. Familiarisation: Read or review the complete material.
2. Initial coding: Mark relevant segments with concise labels.
3. Codebook development: Define codes, inclusion rules, exclusion rules, and examples.
4. Focused coding: Consolidate overlapping codes and examine important patterns.
5. Categorisation: Group related codes into broader categories.
6. Theme development: Construct patterned meanings that explain the issue.
7. Negative-case analysis: Search for evidence that challenges the emerging account.
8. Synthesis: Link themes to decisions, opportunities, or hypotheses.

A theme is more than a topic. “Onboarding” is a topic; “Users interpret unexplained data requests as a test of institutional trust” is a potential theme because it expresses a patterned meaning and mechanism.

Quality of coding

Coding may be performed by one researcher or collaboratively. Multiple coders can expose blind spots, but agreement is not the same as validity. If a team calculates intercoder agreement, it should define the coding unit, code independently before reconciliation, and explain how disagreements were resolved. A numerical agreement score cannot replace conceptual discussion, and not every interpretive project requires formal agreement statistics.

The following evidence matrix supports synthesis:

From theme to insight

A useful insight connects an observed pattern to a meaningful human tension and an opportunity. One structure is:

Observation → Pattern → Underlying need or tension → Opportunity

Example:

• Observation: Participants save screenshots of confirmation pages.
• Pattern: They preserve evidence after high-stakes transactions.
• Tension: They want convenience but do not fully trust the system to remember or resolve errors.
• Opportunity: Design a searchable, durable record with clear recovery and support pathways.

The final claim should be proportionate to the evidence. “Participants in this study often…” is defensible. “Consumers always…” is usually not.

6. Ensuring Research Quality

Several criteria help assess qualitative quality:

• Credibility: Are interpretations well supported by the data and plausible alternatives considered?
• Transferability: Is enough context provided for readers to judge relevance elsewhere?
• Dependability: Is the research process documented and coherent?
• Confirmability: Can interpretations be traced to evidence rather than researcher preference?

Triangulation may involve comparing methods, participant groups, researchers, data sources, or theoretical perspectives. For example, interviews may reveal that users value speed, while observation shows that they repeatedly verify information before submitting. The discrepancy is not a failure; it is a product insight requiring explanation.

Member reflection—sharing an emerging interpretation with selected participants—can identify misunderstanding, although participants cannot be expected to validate every theoretical interpretation. Peer review, audit trails, reflexive memos, and negative-case analysis also strengthen quality.

7. Ethics, Privacy, and Governance

Qualitative research can expose intimate routines, financial information, health conditions, household relationships, workplace practices, and identifiable locations. Ethical practice therefore extends beyond obtaining a signature on a consent form.

Researchers should explain the purpose, activities, recording, risks, benefits, voluntary nature of participation, withdrawal procedures, incentive, data use, retention period, and contact for concerns. Consent should be understandable and appropriate to the participant’s language and accessibility needs. Consent for participation, recording, use of quotations, and reuse of data may need to be separated.

Important safeguards include:

• collect only data necessary for the research purpose;
• restrict access according to role;
• encrypt stored and transferred files where appropriate;
• remove direct identifiers and review indirect identifiers;
• avoid publishing quotations that make a participant easily traceable;
• establish deletion and retention schedules;
• obtain permission before entering private homes or workplaces;
• protect bystanders who appear in recordings;
• use additional safeguards with children or vulnerable groups.

Researchers must comply with applicable data-protection, consumer-protection, employment, intellectual-property, and institutional-review requirements. Participants should not be deceived about the sponsor when disclosure is ethically and commercially feasible. Product teams must also avoid using qualitative research to manipulate vulnerable users or justify predetermined decisions under the appearance of discovery.

8. Technology and AI in Qualitative Research

Digital platforms can support recruitment, remote moderation, transcription, translation, diary prompts, multimedia uploads, coding, and retrieval. AI tools may assist with transcription correction, clustering, summarisation, or identifying potentially relevant passages. These tools are aids, not substitutes for methodological judgement.

Risks include hallucinated summaries, loss of context, mistranslation, demographic bias, insecure transfer of sensitive data, and the conversion of ambiguity into false certainty. Before using an AI system, the research team should assess contractual data use, confidentiality, storage location, human review, model limitations, and whether participants consented to such processing. Sensitive transcripts should not be uploaded to an unapproved public service.

A defensible workflow preserves the original data, documents tool use, audits samples of automated output, and ensures that final themes can be traced to source evidence. Automation is most useful for reducing clerical effort while leaving interpretation, ethical decisions, and accountability with qualified researchers.

9. Applied Case: Improving a Grocery Delivery Application

The following is an illustrative case.

Background

A grocery delivery company observed that many first-time customers placed an order but did not place a second order within thirty days. Quantitative analytics showed that failed or late substitutions were associated with lower repeat purchase, but the organisation did not understand the emotional and practical mechanisms involved.

Problem and research design

The research question was: “How do customers experience substitutions and delivery uncertainty, and what would make the service feel dependable enough for repeat use?” The team recruited recent first-time customers who had experienced successful, substituted, late, or cancelled deliveries. It conducted twelve semi-structured interviews, six home-based contextual inquiries during unpacking, and a seven-day diary study with eight participants. The sample was purposive rather than statistically representative.

Analysis

Initial codes included “checks delivery window,” “screens for unavailable items,” “accepts substitute under time pressure,” “does not know who chose substitute,” “stores screenshots,” and “feels blamed by support.” Focused analysis identified three themes.

First, customers judged reliability before the delivery arrived. Repeated status checking was not simply impatience; it reflected the need to coordinate work, childcare, and meal preparation. Second, substitutions were acceptable when the customer felt in control, but unacceptable when the decision appeared arbitrary. Third, support interactions became a test of respect: scripted responses increased frustration when customers had already explained the problem.

Approach and solution

The team proposed a product concept combining: a substitution preference profile; an explicit explanation of why an item was replaced; a real-time option to approve or reject selected substitutes; and a persistent issue record visible to support staff. It also recommended testing notification timing and language before full development.

Outcome

In a subsequent quantitative experiment, the team measured acceptance of substitution controls, repeat ordering, support contacts, and delivery cancellations. The qualitative work did not prove that the proposed features would improve retention. It clarified the mechanism and helped design a testable intervention. The company avoided a narrow solution—adding more delivery-status notifications—and addressed the deeper issue of control and accountability.

Learning points

1. Behavioural data can identify where a problem occurs, while qualitative research can explain why.
2. A theme should connect observed behaviour to a human need or mechanism.
3. Contextual inquiry revealed coordination demands that interviews alone might have underexplored.
4. Qualitative findings should guide product hypotheses and experiments, not replace validation.
5. Contradictions—such as accepting a substitute while expressing dissatisfaction—can reveal trade-offs rather than poor-quality data.

Challenges and Limitations

Qualitative research is resource-intensive and vulnerable to recruitment bias, moderator effects, social desirability, recall error, selective analysis, and overinterpretation. Participants who volunteer may be more articulate or engaged than the wider market. Remote research can improve access but may exclude people with limited connectivity, private space, or digital confidence. In-person research can reveal context but may increase cost and observer influence.

Small samples provide depth but cannot establish prevalence. Findings may be culturally or contextually specific. Researchers should therefore state the boundaries of the evidence, distinguish participant language from researcher interpretation, and use quantitative research or behavioural data when decisions require estimation, forecasting, or causal measurement.

Best Practices for Product Managers

• Frame the study around a decision, not a vague desire for insight.
• Recruit for meaningful variation and document inclusion criteria.
• Ask about recent behaviour before asking for preferences or ideals.
• Observe workarounds, sequences, interruptions, and artefacts.
• Pilot the guide, diary tasks, technology, and consent process.
• Separate description, interpretation, and recommendation in analysis.
• Preserve negative cases and contradictions.
• Use quotations as evidence, not decoration.
• Trace every major insight to multiple supporting examples where possible.
• Communicate confidence and limitations clearly.
• Convert insights into testable product hypotheses.
• Protect participant dignity, privacy, and control over their data.

Chapter Summary

Qualitative consumer research investigates meanings, experiences, practices, motivations, and contexts that are difficult to capture through measurement alone. Interviews provide depth; focus groups reveal interaction and social language; observation and ethnography expose situated behaviour; diary studies capture experiences over time; contextual inquiry links action with explanation; and online communities support distributed, longitudinal participation.

High-quality studies begin with a decision-oriented brief and purposive sampling strategy. They use flexible guides, skilled facilitation, reflexive fieldwork, careful documentation, and ethical safeguards. Analysis proceeds from familiarisation and coding to categories, themes, negative-case analysis, and insight synthesis. A strong insight explains a meaningful pattern and identifies a product opportunity without claiming more than the evidence supports.

For product managers, the central value of qualitative research is not the volume of quotations but the quality of explanation. It reveals why behaviour occurs, how problems are experienced, and what conditions may enable change. Used alongside analytics and quantitative research, it supports more humane, precise, and testable product decisions.

Key Terms

Qualitative research: Systematic inquiry into meanings, experiences, practices, and contexts using non-numerical evidence.

Interpretive orientation: An approach that treats behaviour as meaningful and shaped by context.

Purposive sampling: Selecting participants because they possess characteristics relevant to the research question.

Information richness: The depth, relevance, and contextual detail contributed by research data.

Saturation: The point at which additional data adds little important conceptual information.

In-depth interview: A guided one-to-one conversation designed to explore experiences and meanings.

Focus group: A moderated discussion in which participant interaction is itself a source of data.

Observation: Systematic recording of behaviour, interactions, environments, and artefacts.

Ethnography: Contextual study of people and practices through sustained engagement with social settings.

Diary study: A longitudinal method in which participants record experiences as they occur.

Contextual inquiry: Observation and interviewing conducted while a participant performs a real task.

Online community: A digital research space in which participants contribute and interact over time.

Code: A concise label attached to a meaningful segment of qualitative data.

Codebook: A documented set of codes, definitions, inclusion rules, and examples.

Theme: A patterned meaning that explains important relationships across coded data.

Reflexivity: Examination of how the researcher influences data collection and interpretation.

Triangulation: Comparing different methods, sources, researchers, or perspectives to strengthen interpretation.

Negative-case analysis: Deliberate examination of evidence that challenges an emerging explanation.

Research insight: An evidence-grounded interpretation linking a consumer tension or need to an opportunity.

Review Questions

Short Answer Questions

1. What distinguishes qualitative research from quantitative research?
2. When is an in-depth interview preferable to a focus group?
3. Define purposive sampling and explain why it is used.
4. What is the difference between a code and a theme?
5. Why is reflexivity important in qualitative research?

Long Answer Questions

1. Compare interviews, observation, ethnography, diary studies, and contextual inquiry for product discovery.
2. Explain how a researcher can design and moderate a high-quality focus group.
3. Describe the complete process of moving from raw qualitative data to product insights.
4. Discuss ethical and privacy issues in research involving recordings, homes, workplaces, and online communities.
5. Explain how qualitative and quantitative research can be combined in a product-management research programme.

Analytical / Application Questions

1. A banking-app team finds that users claim onboarding is easy, but many abandon the process after identity verification. Design a qualitative study, including methods, sampling, key questions, and an analysis plan.
2. During interviews, participants say they value personalised recommendations, but observation shows them repeatedly ignoring recommendation modules. Develop at least two plausible explanations and propose research to distinguish them.
3. A product team wants to publish highly emotional quotations from a small online community to justify a major redesign. Critically evaluate the evidential, ethical, and governance issues and recommend a defensible decision process.

Multiple Choice Questions with Answers

Question 1

Which research method is most appropriate for understanding how a consumer performs a task in the environment where it normally occurs?

A. Contextual inquiry

B. A large-scale probability survey

C. Concept testing by email only

D. Secondary sales analysis

Correct Answer: A. Contextual inquiry

Question 2

What is the primary purpose of purposive sampling in qualitative research?

A. To produce a statistically representative estimate of the market

B. To select participants with experiences relevant to the research question

C. To eliminate all researcher judgement from recruitment

D. To ensure that every customer has an equal probability of selection

Correct Answer: B. To select participants with experiences relevant to the research question

Question 3

Which statement best describes a qualitative theme?

A. A list of every topic mentioned by participants

B. A numerical estimate of how common a behaviour is

C. A patterned meaning that explains an important relationship in the data

D. A quotation selected because it is rhetorically attractive

Correct Answer: C. A patterned meaning that explains an important relationship in the data

Question 4

Why are focus groups less suitable for some sensitive topics?

A. They cannot generate participant interaction

B. Participants may be inhibited by the presence of other group members

C. They always require statistical sampling

D. They cannot be moderated using a discussion guide

Correct Answer: B. Participants may be inhibited by the presence of other group members

Question 5

Which sequence best represents a sound path from data to product insight?

A. Recommendation → quotation → sample → theme

B. Observation → pattern → underlying tension or need → opportunity

C. Theme → recruitment → observation → hypothesis

D. Sample size → percentage → quotation → conclusion

Correct Answer: B. Observation → pattern → underlying tension or need → opportunity

Question 6

A researcher labels the statement “I save confirmation screenshots in case support denies the transaction” as “preserves evidence after high-stakes actions.” This label is best understood as what?

A. An interpretive code

B. A recruitment criterion

C. A consent condition

D. A sampling quota

Correct Answer: A. An interpretive code

Question 7

What does negative-case analysis involve?

A. Deleting data that does not fit the dominant theme

B. Searching for evidence that challenges an emerging explanation

C. Recruiting only dissatisfied participants

D. Replacing qualitative data with numerical data

Correct Answer: B. Searching for evidence that challenges an emerging explanation

Question 8

Which claim is most appropriate for a small purposive qualitative sample?

A. Exactly 48% of all customers have the problem

B. The finding proves the feature will increase retention

C. Participants in this study often experienced the problem in this way

D. Every user in the market shares the same motivation

Correct Answer: C. Participants in this study often experienced the problem in this way

Question 9

What is a major governance risk when using AI to summarise sensitive interview transcripts?

A. The transcripts may become longer than the original recordings

B. The tool may create inaccurate or decontextualised interpretations and expose confidential data

C. The researcher will be unable to recruit purposive samples

D. The method automatically converts qualitative research into an experiment

Correct Answer: B. The tool may create inaccurate or decontextualised interpretations and expose confidential data

Question 10

Which practice most directly strengthens the credibility of qualitative findings?

A. Using only the most dramatic quotation

B. Ignoring contradictory participant accounts

C. Tracing interpretations to evidence and considering alternative explanations

D. Increasing the number of survey response options

Correct Answer: C. Tracing interpretations to evidence and considering alternative explanations