Consumer Interview & Qualitative Study Analysis
Turn a consumer interview or focus-group transcript into coded themes, sentiment, likes and dislikes, unmet needs, purchase intent, and cited insights - with a verbatim quote on every finding.
Coding a consumer interview - themes, sentiment, likes and dislikes, sensory reads, and cited verbatims that an analyst hand-tags line by line - produced in minutes per transcript, so a study's worth of interviews can be coded and rolled up in a fraction of the usual time
per interview
What it extracts
13 extraction fields
- Study Summary
- A one-look frame of the study - method, objective, category, the products or concepts tested, the test design (monadic or paired), context (CLT/HUT), guide topics, and language - so a reader can orient before the coded findings.
- Respondent Profile & Segment Signals
- The respondent in their own words - segment, category usage, self-reported attributes the study screens on, usage occasions, current brands, demographic cues, and purchase role - so findings can be read by segment without inferring beyond what was said.
- Thematic Analysis
- The transcript coded into named themes (reflexive thematic analysis), one per row, each tagged by category (unmet need, pain point, like, dislike, driver, barrier, usage, sensory, emotion), salience, product referenced, sentiment, and a representative verbatim quote.
- Overall Sentiment
- The respondent's net sentiment toward the tested product or concept, from very positive to very negative, weighing the whole transcript rather than counting positive versus negative words.
- Product Likes & Positive Drivers
- Everything the respondent liked, by attribute (fragrance, texture, efficacy, skin feel, packaging, value), with the strength of the positive and a verbatim - the attributes to protect and lean into.
- Product Dislikes, Concerns & Barriers
- Everything the respondent disliked, worried about, or hit as a barrier, by attribute, with a severity (dealbreaker/significant/minor), a verbatim, and any fix the respondent suggested - including safety or experience observations.
- Sensory & Attribute Evaluation
- Each sensory or product attribute read on a just-about-right direction (too little / just about right / too much), with the respondent's descriptive words, so attribute levels can be tuned toward the ideal (JAR-style optimization input).
- Unmet Needs & Jobs to Be Done
- Needs that current products fail to meet, framed as jobs to be done (functional, emotional, social), with the trigger, the respondent's current workaround, and the opportunity each need points to.
- Purchase Intent
- The respondent's stated intent to buy at the concept price, on a five-point definitely-to-definitely-not scale (Juster-style), or Not discussed - the demand signal for the concept.
- Concept & Price Response
- How the respondent reacted to the concept and its price - reaction, believability, expected price, the stated concept price, value for money, willingness to pay, and any price barrier.
- Product Preference & Ranking
- For paired or sequential-monadic tests, one row per product with the rank or rating the respondent gave, which was preferred overall, the reason, and a verbatim - single-product tests yield one row.
- Key Insights & Recommendations
- The interview synthesized into actionable insights, each with its supporting evidence, business implication, a recommended action, and a confidence rating - grounded in this respondent, with population roll-up left to the study.
- Analysis Coverage & Confidence
- Whether the transcript is a usable, fully analyzable interview, only partially analyzable, off-topic or unusable, or needs manual review - so a reviewer knows which rows to trust.
Where it fits
Qualitative consumer research analysis (Consumer R&D insights)
Upstream
Fieldwork - moderated interviews, focus groups, or product-test debriefs are conducted and transcribed (often central-location or home-use tests), producing one transcript per respondent or session
This step
Transcript analysis and coding (thematic analysis, sentiment, likes/dislikes, sensory reads, purchase intent)
Downstream
- Cross-respondent theme roll-up and study report
- Product optimization and reformulation decisions
- Concept, claims, and price refinement
- Segment and persona development
What it needs
Documents
- Interview or focus-group transcript (one per respondent or session)
- Discussion guide (for topic coverage)
- Concept or stimulus shown to the respondent (with any stated price)
Systems
- Transcription tool
- Qualitative analysis / coding platform
- Survey or fieldwork platform
Prerequisites
- A transcribed interview (the analyzable unit)
- The neutral test labels used for the products or concepts (for example Product A, Product B)
- The discussion guide and concept, so topic coverage and price response can be judged
What it produces
A coded interview analysis - a study summary and respondent profile, a thematic-analysis table with verbatims, an overall sentiment call, likes and dislikes tables, a sensory just-about-right read, an unmet-needs and jobs-to-be-done table, purchase intent, concept and price response, product preference and ranking, and a cited key-insights table
Delivered to
- Study report / insights deck
- Cross-respondent theme and frequency roll-up
- Product and concept development workstream
Review model
A consumer insights analyst reviews the coded themes, the sentiment call, and the verbatim quotes against the transcript before findings are rolled up across the study; single-interview insights are treated as directional, not population-level.
Who uses it
Volume fit
Works best for
teams analyzing dozens of interviews or open-ends per study, or running recurring product and concept tests, where hand-coding every transcript is the bottleneck
Too small for
a single short interview a researcher could read and code in one sitting
Grounded in
- Braun, V. & Clarke, V. (2006), 'Using thematic analysis in psychology', Qualitative Research in Psychology 3(2):77-101 - the six-phase thematic-analysis methodverified as of 2026-07-22
- ASTM MNL 63 - Just-About-Right (JAR) Scales: Design, Usage, Benefits, and Risks (ASTM International)verified as of 2026-07-22
- Juster, F.T. (1966), 'Consumer Buying Intentions and Purchase Probability', Journal of the American Statistical Association 61:658-696 - the Juster purchase-probability scaleverified as of 2026-07-22
- Monadic and sequential-monadic product-test design; central-location test (CLT) and home-use test (HUT) conventions (standard market-research methodology)verified as of 2026-07-22
- ESOMAR / ICC Code on Market, Opinion and Social Research and Data Analytics - respondent-data handling and no-fabrication principlesverified as of 2026-07-22
Changelog
- July 2026
based on a production deployment at a global consumer personal-care company
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