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Interviews can produce qualitative insights, quantitative metrics, or both, depending on question format, response options, and how you process the data.
People ask this because “interview” sounds like one thing, yet it can behave like two different tools. You might be chatting in-depth about lived experiences. Or you might be reading a fixed script with rating scales and ticking boxes.
So the clean answer is this: an interview isn’t automatically qualitative or quantitative. The label comes from the choices you make before, during, and after the conversation. Question types, sampling, recording style, and scoring rules change what you can claim at the end.
This article helps you classify an interview design fast, avoid mismatches (like open questions with a stats-only plan), and build an interview that fits your research goal.
Are Interviews Qualitative Or Quantitative? What Decides It
Think of an interview as a container. What makes it qualitative or quantitative is what you put inside that container and what you do with it after.
What Makes An Interview Qualitative
An interview leans qualitative when answers are mostly open text, spoken narratives, or detailed descriptions. You’re collecting meaning, language, and nuance. The end product is usually themes, categories, or interpretations grounded in what people said.
- Question style: open prompts like “Tell me about…” and follow-ups that dig into detail.
- Response format: participants speak freely, with few fixed options.
- Outcome: themes, patterns in wording, explanations of why something happens.
What Makes An Interview Quantitative
An interview leans quantitative when the goal is comparable measurements. That usually means a fixed script, fixed response options, and a scoring plan that turns each response into a number you can summarize across many people.
- Question style: closed questions or standardized rating scales.
- Response format: a set list of options (yes/no, 1–5, multiple choice).
- Outcome: counts, percentages, averages, group comparisons.
Why Many Real-World Interviews Sit In The Middle
Plenty of interviews are mixed on purpose. A researcher might start with a short block of ratings, then shift into open prompts. Or they might ask open prompts, then later code the answers into categories and count how often each category shows up.
That’s why it’s smarter to label the interview by design and analysis plan, not by the word “interview” itself.
Interview Types And How They Usually Behave
Most interview designs fall into three familiar shapes. The names are common, but the details matter. A “semi-structured” interview with strict time limits and no follow-ups can feel far closer to a survey than people expect.
Structured Interviews
Structured interviews use a script with consistent wording and order. Interviewers keep things tight so each participant gets the same prompts. That consistency makes answers easier to compare.
If you’re building a structured interview for measurement, it helps to treat it like a spoken questionnaire: fixed response options, clear skip logic, and a scoring key that’s ready before the first participant shows up.
Semi-Structured Interviews
Semi-structured interviews use a topic guide with planned questions, plus room for follow-ups. The guide keeps coverage consistent across participants while still letting you chase detail when a response is rich.
This format often fits studies where you know the broad areas you need, yet you still want participants to speak in their own words.
Unstructured Or In-Depth Interviews
Unstructured interviews feel like a guided conversation built around a purpose. You might enter with a few prompts and then follow the participant’s lead. These interviews can yield deep context, but they can be harder to compare across people unless you build a careful coding plan later.
How Your Analysis Plan Changes The Label
Two teams can run the same interview guide and still end up with different “qualitative vs quantitative” labels. The split comes from what happens after the recording stops.
When Open Answers Stay As Text
If you keep responses as text and write up themes with quotes, you’re working in a qualitative style. You might still track how common a theme is, but the main product is meaning and context.
When Open Answers Get Turned Into Numbers
Text can be transformed into numbers through coding. You define categories, apply them consistently, then count the results. That gives you quantitative summaries built from qualitative material.
A clear description of this “data transformation” idea appears in the mixed methods literature, including the way teams convert coded text into numeric variables so they can merge it with a quantitative dataset. Achieving Integration in Mixed Methods Designs—Principles and Practices is a solid starting point for the concept and vocabulary.
When Numbers Need Words To Make Sense
Even in a measurement-heavy interview, you may end up adding a few open prompts to explain why a score is high or low. That layer can save a project from misleading conclusions. Averages can tell you “what.” Open responses often tell you “why.”
Choosing The Right Approach For Your Goal
The easiest way to choose is to start with the decision you want to make at the end.
If You Need Comparisons Across Many People
Pick a structured or strongly standardized design. Keep questions short. Use response options that match your planned statistics. Train interviewers to read questions the same way each time and to avoid extra commentary that could steer answers.
If You Need Reasons, Stories, Or Process Details
Lean into semi-structured or in-depth formats. Plan follow-ups that pull for examples, timelines, and concrete situations. Record and transcribe if you can, since notes alone can miss phrasing that later becomes central to your theme map.
If You Need Both
Use a mixed design. One clean pattern is “structured first, open second.” You gather comparable measurements, then ask targeted open prompts to unpack the numbers. Another pattern is “open first, structured later.” You learn the language people use, then build a fixed instrument that reflects it.
If you want an official, plain-language statement that interviews can collect qualitative data, quantitative data, or both, see the UK government guidance on interview studies: How to carry out an interview study (qualitative studies).
Common Design Choices That Push Interviews Toward Qualitative Or Quantitative
Small choices create big shifts in what your interview produces. Use this table as a quick classifier while you write your guide.
| Design choice | What you collect | Most common output |
|---|---|---|
| Fixed script, same order | Comparable responses | Quantitative summaries |
| Mostly closed response options | Counts and scale scores | Quantitative metrics |
| Open prompts with follow-ups | Detailed explanations | Qualitative themes |
| Short answers limited to a phrase | Brief text fragments | Either, based on coding plan |
| Audio recorded + full transcript | Exact wording and tone cues | Stronger qualitative work |
| Real-time scoring sheet | Immediate numeric ratings | Quantitative comparison |
| Post-interview coding into categories | Theme tags per segment | Mixed: themes + counts |
| Interviewer freedom to rephrase | Natural flow, varied wording | Qualitative, unless standardized later |
Practical Rules For Writing Interview Questions That Match Your Plan
This is where many projects drift. The guide is written one way, the analysis plan assumes another, and the results feel shaky.
Rules For Quantitative-Style Interview Questions
- Use one idea per question. If you ask two things at once, you can’t score it cleanly.
- Keep response options complete. Add “not sure” or “not applicable” when it’s realistic for your topic.
- Anchor your scales. Define what “1” and “5” mean in plain language.
- Write a scoring key before fieldwork. If scoring rules change midstream, comparisons get messy.
Rules For Qualitative-Style Interview Questions
- Invite detail. Prompts that ask for a situation, a sequence, or a specific moment tend to yield richer material.
- Plan your follow-ups. Keep a short list like “What happened next?” “What made that hard?” “What did you do then?”
- Stay neutral. Avoid praise or judgment in your wording so you don’t steer the story.
- Use a topic guide, not a script. Keep core questions consistent, then use follow-ups when needed.
If you want a clear teaching reference on interview methods and how structured and semi-structured formats differ, the UK Data Service has a dedicated resource: Teaching resource: Interview methods (PDF).
Sampling And Scale: Why Size Pressures The Method
Sample size doesn’t dictate the method by itself, but it nudges your choices.
Small Samples Often Favor Depth
With a small group, it’s realistic to record, transcribe, and code carefully. That makes in-depth or semi-structured formats attractive because each interview can carry a lot of meaning.
Larger Samples Often Favor Standardization
With many participants, you need consistency to keep interviewer drift under control. Structured interviews and tight guides can help you stay comparable across the full set.
The Middle Ground: Hybrid Designs That Stay Manageable
A useful compromise is to keep one section fully standardized (ratings, frequencies, yes/no), then keep one section open but time-boxed. You still get stories, yet you don’t drown in transcripts.
Second Table: Quick Classification Checklist
Use this as a last pass before you finalize your interview guide and your analysis notes.
| If you need… | Your interview should include… | Your output will look like… |
|---|---|---|
| Group comparisons | Closed questions, fixed order | Counts, averages, charts |
| Clear explanations | Open prompts, planned follow-ups | Themes with short quotes |
| Both patterns and reasons | Ratings + open section | Numbers plus themed write-up |
| Repeatable measurement over time | Same script each round | Trend lines, stable indicators |
| Language people use around a topic | Loose guide, room for detail | Theme map and wording patterns |
| Fast fieldwork with minimal coding | Mostly closed responses | Clean dataset ready for stats |
How To Write Your Methods Section Without Overclaiming
If you’re writing a paper, thesis, or report, the label you choose should match what you did.
Use Clear, Concrete Descriptions
Instead of trying to force a single label, name the pieces:
- “We used a structured interview with a fixed script and 5-point scales.”
- “We used semi-structured interviews with a topic guide and open prompts.”
- “We combined closed questions with open prompts, then coded open responses into categories.”
State How You Handled Coding
If you coded text, note who coded, how categories were defined, and how disagreements were handled. Readers trust method detail more than labels.
Be Honest About Limits
No interview method is perfect. Structured formats can miss nuance. In-depth formats can be harder to compare. A calm statement of trade-offs reads like real research work and helps your reader judge fit.
Common Mistakes That Blur The Method
These issues show up a lot in student projects, workplace studies, and user research.
Calling It Quantitative Without A Scoring Plan
If your interview is mostly open prompts and you don’t code into numeric categories, it isn’t quantitative in any meaningful way. It may still be rigorous, but the output is text-based.
Calling It Qualitative While Treating Answers Like Survey Data
If you ask closed questions and report percentages, you’re producing quantitative output even if the interview felt conversational. The method label should match the output.
Mixing Prompts Without Planning Integration
It’s fine to mix. The mistake is mixing without a plan for how the two parts will connect. Decide early: Will the open section explain the ratings? Will the ratings guide which participants you follow up with? Write that link down before you start.
If you want a plain, well-structured overview of interviewing as a qualitative method, an open textbook chapter can help you tighten your guide and follow-ups: Chapter 11. Interviewing (Oregon State University open text).
One-Sentence Takeaway You Can Use While Designing
An interview is qualitative when it’s built to capture meaning in people’s words, quantitative when it’s built to capture comparable measurements, and mixed when you plan both on purpose.
References & Sources
- UK Government (GOV.UK).“Interview study: qualitative studies.”Confirms interviews can collect qualitative data, quantitative data, or both, and outlines common interview formats.
- National Library of Medicine (PMC).“Achieving Integration in Mixed Methods Designs—Principles and Practices.”Explains mixed methods integration, including transforming coded text into numeric variables for merged analysis.
- UK Data Service.“Teaching resource: Interview methods (PDF).”Describes structured and semi-structured interview types and how design choices affect the kind of data collected.
- Oregon State University Open Textbook.“Chapter 11. Interviewing.”Provides practical guidance on interviewing techniques and building an interview guide for qualitative work.