Title: Customer Research — LearnCoachAssist

Q: What is customer research?
A: Customer research is the disciplined process of learning how customers think, behave, and make decisions so teams can design better products and messaging.

Q: Why is customer research valuable?
A: It reduces guesswork by grounding decisions in real customer evidence instead of assumptions.

Q: What is the difference between qualitative and quantitative research?
A: Qualitative research explores motivations and patterns in depth, while quantitative research measures scale, frequency, and statistical confidence.

Q: What is a customer interview?
A: A structured conversation used to understand needs, context, workflows, frustrations, and decision criteria.

Q: Why are open-ended questions useful in customer interviews?
A: They invite stories, examples, and nuance instead of limiting the customer to short predefined answers.

Q: What is a leading question?
A: A question that nudges the customer toward a preferred answer, which can distort the findings.

Q: What is a good interview question for discovering pain?
A: "Walk me through the last time you tried to solve this problem."

Q: Why should researchers ask about past behavior instead of future intent?
A: Past behavior is usually more reliable than hypothetical promises about what someone might do later.

Q: What is a user segment?
A: A user segment is a meaningful subset of customers who share similar goals, constraints, or behaviors.

Q: What is a participant screener?
A: A screener is a set of questions used to recruit the right participants for a study.

Q: What is observational research?
A: It is research where you watch users perform tasks in their real or simulated environment to uncover actual behavior.

Q: What is diary research?
A: A study method where participants record activities or feelings over time so researchers can see patterns across days or weeks.

Q: What is usability testing?
A: A method where users attempt realistic tasks while researchers observe friction, confusion, and success rates.

Q: What is the purpose of a research objective?
A: It clarifies what the team is trying to learn so the study stays focused and actionable.

Q: What makes a good research sample?
A: Participants should resemble the target audience closely enough that findings reflect the real users the product serves.

Q: What is triangulation in research?
A: Triangulation means combining multiple sources or methods to strengthen confidence in findings.

Q: What is synthesis in customer research?
A: Synthesis is the process of organizing notes into patterns, themes, and insights the team can use.

Q: What is an insight?
A: An insight is a meaningful conclusion that explains customer behavior and suggests how the team should act differently.

Q: What is a jobs-to-be-done interview?
A: A research conversation focused on what progress the customer was trying to make when they hired a product or workaround.

Q: Why should research capture exact customer language?
A: Real customer wording improves messaging, product copy, positioning, and internal understanding.

Q: What is response bias?
A: Response bias happens when participants answer in a socially desirable or otherwise distorted way rather than honestly.

Q: What is the value of follow-up probing?
A: Probing uncovers the story behind short answers and often reveals hidden motivations or trade-offs.

Q: What is an example of a probing question?
A: "What made that difficult?" or "What happened next?"

Q: What is a research repository?
A: A repository is a shared system where notes, recordings, tags, and insights are stored for reuse.

Q: Why should research findings be shared quickly?
A: Fresh evidence is more likely to influence priorities and decisions when it is circulated while the topic is active.

Q: What is an assumption map?
A: A simple framework for listing risky beliefs and deciding which ones need research evidence first.

Q: What is concept testing?
A: A study that checks whether customers understand and value a proposed idea before the team invests heavily in building it.

Q: What is a good output of customer research?
A: Clear findings, supporting evidence, implications, and recommended next steps for product, marketing, or sales.

Q: What is customer discovery?
A: Customer discovery is early-stage research focused on validating whether a meaningful problem exists and for whom.

Q: Why is recruiting quality participants so important?
A: Weak participant fit leads to misleading findings, no matter how polished the interview guide is.

Q: What is a discussion guide?
A: A discussion guide is a flexible plan of topics and prompts that keeps interviews consistent without making them robotic.

Q: Why should researchers avoid pitching during interviews?
A: Pitching changes the conversation from learning to selling and can contaminate what participants say.

Q: What is note-taking discipline in research?
A: It means capturing observations faithfully, distinguishing direct quotes from interpretation, and keeping evidence traceable.

Q: What is affinity mapping?
A: Affinity mapping groups observations into themes so patterns emerge more clearly during synthesis.

Q: What is a signal in customer research?
A: A signal is a repeated pattern, quote, or behavior that appears strong enough to influence decisions.

Q: What is a false positive in research?
A: A false positive is a conclusion that feels compelling but is actually based on weak or unrepresentative evidence.

Q: What is preference testing?
A: Preference testing compares options, such as designs or messages, to see which users favor and why.

Q: What is message testing?
A: Message testing evaluates whether customers understand, believe, and care about proposed positioning or copy.

Q: What is saturation in qualitative research?
A: Saturation is the point where additional interviews produce few genuinely new themes.

Q: What makes research actionable?
A: The output clearly links evidence to decisions, owners, and the next set of assumptions to test.

Q: What is a research plan and what does it typically include?
A: A research plan names the business question, the target users, the methods (e.g. interviews, surveys, field studies), the sample size and sourcing plan, the timeline, the owners, and the decision the findings are meant to inform.

Q: What is a primary vs secondary research source?
A: Primary research is collected directly from customers for the current question (interviews, surveys, usability tests); secondary research is existing data such as industry reports, prior internal studies, or public benchmarks.

Q: What is a behavioral vs attitudinal research question?
A: Behavioral questions ask what people actually did (last action, frequency, tool used); attitudinal questions ask what people say they believe, prefer, or intend — and the two often diverge.

Q: What is the "five whys" technique in customer research?
A: It is an interview probing method that asks "why?" repeatedly (typically around five times) to move from a surface complaint to the underlying cause or job the customer is trying to get done.

Q: What is a customer journey map?
A: A visual representation of the steps, touchpoints, emotions, and goals a customer experiences while trying to accomplish a goal with a product, service, or workaround.

Q: What is a touchpoint?
A: A specific moment of interaction between a customer and a product, brand, support agent, or channel during the customer journey.

Q: What is a Jobs-to-Be-Done (JTBD) job statement?
A: A short framing such as "When I [situation], I want to [motivation/progress], so I can [expected outcome]" that captures the progress the customer was trying to make.

Q: What is the difference between a functional, emotional, and social job in JTBD?
A: Functional jobs are the concrete tasks to accomplish; emotional jobs are how the customer wants to feel; social jobs are how they want to be perceived by others.

Q: What is a "push, pull, anxiety, habit" model in switching research?
A: It is a JTBD framing where "push" forces customers away from the current solution, "pull" attracts them to a new one, "anxiety" creates hesitation, and "habit" keeps them on the old path.

Q: What is the difference between needs, wants, and demands?
A: Needs are underlying human or job requirements; wants are culturally and personally shaped expressions of those needs; demands are wants backed by purchasing power and intent.

Q: What is a persona?
A: A persona is a research-grounded archetype of a user segment that summarizes goals, behaviors, context, and frustrations to help teams empathize and design consistently.

Q: What is the difference between a persona and a user segment?
A: A segment is a real group in the data, defined by shared attributes; a persona is a narrative composite built from real segment members to make that group memorable and actionable.

Q: Why is "the customer" usually not a single person in B2B research?
A: Buying decisions involve multiple roles (economic buyer, technical evaluator, end user, champion, gatekeeper) whose goals and criteria often conflict, so research must map each role separately.

Q: What is an economic buyer vs a champion in B2B research?
A: The economic buyer controls budget and signs off; the champion drives internal momentum and advocates for the purchase. Research must serve both, often with different messages.

Q: What is a screener question and what makes one good?
A: A screener question filters participants by relevant traits (role, behavior, recency). Good screeners are specific, behavior-based, hidden from the candidate, and disqualifying without being obvious.

Q: What is a "must-have" vs "nice-to-have" screening criterion?
A: Must-haves disqualify a participant if missing (e.g. makes purchasing decisions for the category); nice-to-haves improve fit but are not dealbreakers and help balance a sample.

Q: What is purposive sampling?
A: A non-probability sampling method where the researcher deliberately chooses participants who match pre-defined traits relevant to the research question.

Q: What is snowball sampling and when is it appropriate?
A: Recruiting participants through referrals from existing participants. It is appropriate for hard-to-reach or specialist populations but can amplify bias if referrals are homogeneous.

Q: What is convenience sampling?
A: Recruiting whoever is easiest to reach (e.g. coworkers, social followers). It is fast but rarely representative and should be flagged as a limitation in findings.

Q: What is sample size in qualitative research typically guided by?
A: Saturation, not statistics. Most interview studies reach thematic saturation somewhere between 5 and 30 well-chosen participants per segment, depending on segment heterogeneity.

Q: What is a power analysis and when is it used?
A: A statistical calculation that estimates the sample size needed to detect a given effect size with a chosen confidence level and power. It is used to plan quantitative studies, not qualitative ones.

Q: What is a confidence interval?
A: A range, derived from sample data, that is likely to contain the true population value at a stated confidence level (commonly 90% or 95%).

Q: What is margin of error?
A: The plus-or-minus figure (e.g. ±4%) that describes how much survey results are expected to vary from the true population value, usually at a 95% confidence level.

Q: What is a Likert scale?
A: A psychometric scale (commonly 5- or 7-point) where respondents indicate agreement, frequency, or satisfaction. Even-numbered scales force a direction; odd scales allow neutrality.

Q: What is a Net Promoter Score (NPS) and what does it measure?
A: NPS is a survey metric that asks how likely a customer is to recommend the product (0–10). It is calculated as %Promoters (9–10) minus %Detractors (0–6) and is used as a proxy for loyalty and growth.

Q: What is a CSAT score?
A: Customer Satisfaction Score: typically the percentage of respondents who rate a specific interaction (e.g. support ticket, checkout) as satisfied or better, captured right after the event.

Q: What is a Customer Effort Score (CES)?
A: A survey metric asking how easy it was for the customer to get something done (e.g. resolve an issue). Lower effort is associated with higher retention and referral.

Q: What is a structured vs semi-structured interview?
A: Structured interviews use a fixed script and order, producing comparable data. Semi-structured interviews use a guide of topics but allow flexible wording, order, and follow-ups — preferred for exploratory research.

Q: What is an "extreme user" and why interview them?
A: An extreme user is a customer at either end of a behavior spectrum (power user, complete non-adopter). Interviewing extremes surfaces unmet needs, workarounds, and constraints that average users blur.

Q: What is the "critical incident" interview technique?
A: Asking the participant to recall a specific recent event in detail (what happened, when, where, who was involved, what they did, what the outcome was) to anchor answers in real experience.

Q: What is a laddering interview technique?
A: An interview method that moves up or down levels of abstraction — from features to consequences to values, or from values back to concrete behaviors — to surface underlying motivations.

Q: What is the "think aloud" protocol?
A: A usability method where participants narrate their thoughts while performing a task, so researchers can observe reasoning, hesitations, and confusion in real time.

Q: What is a moderator's role in a research interview?
A: To guide the conversation neutrally, follow the discussion guide, probe non-leadingly, manage time, and create psychological safety so the participant shares honestly.

Q: What is a pilot interview?
A: A trial run of the interview guide with a representative participant, used to surface confusing wording, missing probes, time overruns, and ethical issues before the real study.

Q: What is informed consent in user research?
A: A process where the participant understands the purpose of the study, what will happen with their data, any risks, and their right to stop, and then voluntarily agrees — usually documented in writing.

Q: What is a research participant incentive calibrated for?
A: The expected time, effort, and emotional labor, plus the participant's role (e.g. executive vs end user). Too low reduces completion quality; too high can coerce or attract the wrong participants.

Q: What is the difference between a pain point and a need?
A: A need is the underlying job or outcome the customer wants; a pain point is a specific friction, cost, or risk that blocks that outcome. Pain points imply needs; needs do not require pain.

Q: What is an "unmet need"?
A: A need that current solutions — including workarounds — do not adequately address, usually revealed when customers report inventing their own tools or processes.

Q: What is a "hair on fire" customer?
A: A segment whose current problem is so urgent and costly that they actively seek out and pay for solutions. The strongest signal of a real market opportunity.

Q: What is a workaround in customer research?
A: A improvised process, tool, or behavior a customer invents to get a job done when existing solutions are inadequate. Workarounds are a strong signal of unmet needs.

Q: What is a frequency vs intensity framework for prioritizing insights?
A: Frequency asks how many customers experience something; intensity asks how severely it affects them. Insights are usually most actionable when high on both axes.

Q: What is the difference between a finding and a recommendation?
A: A finding is a pattern supported by evidence (e.g. "checkout fails when customers use saved addresses from two countries"). A recommendation is the team's proposed action in response ("make secondary address editable without re-saving").

Q: What is a "How Might We" question?
A: A reframing of a finding as an open, opportunity-focused question (e.g. "How might we let customers edit a saved address without re-entering it?") that opens solution space without committing to a design.

Q: What is a research read-out?
A: A structured presentation of findings to stakeholders, typically including goals, method, sample, themes, supporting quotes, implications, and recommended next steps.

Q: What is the "show, don't tell" rule for research presentations?
A: Back every claim with the underlying evidence — a quote, a clip, a chart of the data — so stakeholders can judge strength and re-derive the conclusion rather than just trusting the researcher's summary.

Q: What is thematic analysis?
A: A qualitative analysis method where transcripts or notes are coded and grouped into recurring themes, then refined into a coherent narrative of what the data shows.

Q: What is open, axial, and selective coding?
A: Open coding labels chunks of data with descriptive codes; axial coding groups codes into categories and explores relationships; selective coding integrates everything into a central theme or theory.

Q: What is inter-rater reliability in qualitative coding?
A: The degree to which independent coders apply the same codes to the same data, usually measured with a statistic such as Cohen's kappa. Higher values mean the coding scheme is more reproducible.

Q: What is a research artifact and what kinds exist?
A: A research artifact is any output other than a report that communicates findings — personas, journey maps, opportunity solution trees, service blueprints, highlight reels, or insight cards.

Q: What is a highlight reel in research?
A: A short, edited video compilation of anonymized participant clips that illustrate the most important moments (pain, surprise, delight), used to build stakeholder empathy faster than reading.

Q: What is the difference between segmenting by demographics and by behavior?
A: Demographic segments group by attributes (age, region, role) that are easy to observe but may not predict behavior; behavioral segments group by what people actually do (usage, workflow, triggers), which usually predicts value and need better.

Q: What is a JTBD "milkshake moment" and what does it illustrate?
A: A famous example where a fast-food chain discovered its morning milkshake sales were driven not by hunger but by commuters wanting a single-handed, long-lasting, legal-to-eat-in-the-car option — illustrating that the "job" can be situationally specific.

Q: What is an outcome-driven innovation (ODI) approach?
A: Stratford's ODI is a research method that defines customers by the outcomes they are trying to achieve and the constraints they face, then surveys them to find underserved outcomes that predict purchase intent.

Q: What is a Kano model and how is it used in research?
A: The Kano model categorizes features by customer satisfaction impact: basic (expectations), performance (more is better), and delighters (unexpected positives). Research classifies each candidate feature into a category.

Q: What is the difference between a feature request and a need?
A: A feature request is a specific solution the customer proposes; a need is the underlying job or outcome. The same need often yields many different feature requests across customers.

Q: What is a "voice of the customer" (VoC) program?
A: An ongoing, systematic practice of collecting customer feedback across channels (interviews, surveys, support tickets, reviews), analyzing it, and routing insights to product, marketing, and support teams.

Q: What is text analytics in VoC?
A: The use of automated techniques (keyword extraction, topic modeling, sentiment analysis) to categorize and quantify themes in large volumes of unstructured customer feedback.

Q: What is a service blueprint?
A: A diagram that maps the visible customer journey alongside the behind-the-scenes processes, systems, and actors required to deliver each step, exposing handoffs that often cause friction.

Q: What is the "moment of truth" in a customer journey?
A: A specific touchpoint where the customer forms or updates their opinion of the brand, often disproportionately influencing satisfaction, conversion, or churn (e.g. first use, support call, renewal).

Q: What is a North Star Metric in product research?
A: A single metric that best captures the value the product delivers to customers and is leading-indicator correlated with long-term business health; it is used to align research, design, and growth work.

Q: What is the difference between churn and retention?
A: Churn is the percentage of customers (or revenue) lost in a period; retention is the percentage kept. They are two sides of the same coin, and the most useful research explains which behaviors precede churn.

Q: What is a churn survey and what makes it useful?
A: A short survey sent to customers who have canceled or stopped using the product, asking the reason and what could have changed their decision. Useful when the response is voluntary and unbiased, and when paired with behavioral data.

Q: What is a "smoking gun" signal in churn analysis?
A: A specific behavioral or attitudinal signal that, when present, sharply raises the probability of churn within a defined window (e.g. login frequency dropping below once a week in a SaaS product).

Q: What is the difference between correlation and causation in research?
A: Correlation means two variables move together; causation means one actually produces the other. Customer research findings, especially from surveys, often show correlation that must not be claimed as cause.

Q: What is a "false negative" in user research?
A: Missing a real insight because the wrong participants were recruited, the questions were too leading, the sample was too small, or the analysis over-filtered for confirmation.

Q: What is confirmation bias in customer research?
A: The tendency for researchers (and stakeholders) to interpret ambiguous evidence as supporting what they already believed, leading them to ask leading questions, ignore counter-evidence, or stop at the first confirming interview.

Q: What is the recency effect in research synthesis?
A: A bias where the most recent interviews or data points weigh disproportionately in the synthesis, even if earlier participants had more relevant experience. Synthesis should re-read all notes, not just the latest.

Q: What is sampling bias?
A: When the recruited participants systematically differ from the target population (e.g. only power users, only English speakers, only one region), so findings cannot be safely generalized.

Q: What is survivorship bias in customer research?
A: Studying only customers who remained (survived) and ignoring those who churned or never adopted, which can make a product look much better than it is for the average or failing experience.

Q: What is the "happy path" vs "unhappy path" in usability research?
A: The happy path is the flow where everything works as designed; the unhappy path includes errors, edge cases, interruptions, and accessibility scenarios. Testing only the happy path hides the bugs users actually hit.

Q: What is a heuristic evaluation?
A: A usability method where trained evaluators inspect an interface against established usability principles (e.g. Nielsen's 10 heuristics) to flag likely issues, often used as a complement to user testing.

Q: What is the difference between a moderated and unmoderated usability test?
A: Moderated tests have a facilitator present in real time, allowing probing; unmoderated tests are completed by the participant alone, using a task script and recording, which scales better but limits follow-up.

Q: What is a tree test?
A: A unmoderated research method that evaluates a proposed information architecture by giving participants tasks and measuring whether they can find the right category using the navigation labels alone.

Q: What is a first-click test?
A: A usability method that records where users first click when given a task, used as an early indicator of whether the navigation and labels set them on the right path.

Q: What is a card sort?
A: A research method where participants group topics or features into categories that make sense to them — open (they name the groups) or closed (into predefined groups) — to inform information architecture.

Q: What is a survey design principle for reducing bias?
A: Keep questions short, specific, behaviorally anchored, single-barreled, balanced in wording, and pre-tested with the target audience; randomize option order for non-scaled items.

Q: What is a "double-barreled" survey question?
A: A question that asks two things at once (e.g. "Was the support agent friendly and knowledgeable?") so the respondent cannot answer meaningfully. It should be split into two questions.

Q: What is acquiescence bias?
A: The tendency for respondents to agree with statements regardless of content. It inflates positive scores on agree/disagree scales and is countered by reversing some items or using forced-choice formats.

Q: What is social desirability bias?
A: Respondents over-report behaviors they think the questioner will approve of (e.g. exercise, voting, careful driving) and under-report stigmatized ones. Anonymous, indirect, or behaviorally anchored questions reduce it.

Q: What is a non-response bias?
A: Bias that arises when the people who answer a survey differ systematically from those who do not. Heavy non-response can render a survey's results misleading even if the questions are perfect.

Q: What is a "day-in-the-life" study?
A: A research method where the participant is shadowed (in person or via diary / screen capture) through a typical day to surface context, interruptions, tools, and workarounds that interviews alone often miss.

Q: What is an "intercept" interview?
A: A short, opportunistic interview conducted with a user in the moment of an experience (e.g. at a checkout, after a support call), capturing impressions while they are still vivid.

Q: What is a "comprehensive" customer research repository?
A: A shared, searchable system that stores research goals, plans, transcripts, recordings, tags, insights, links to decisions, and the assumption map — so the organization does not repeatedly relearn the same things.

Q: What is tagging in a research repository?
A: Applying consistent labels (e.g. segment, topic, JTBD, feature area) to research artifacts so they can be filtered, counted, and re-used across teams and over time.

Q: What is a research participant NDA?
A: A non-disclosure agreement that protects confidential product plans, designs, or customer data shared during a study, while still allowing the participant to speak honestly about their own experience.

Q: What is the IRB / ethics review purpose in user research?
A: An Institutional Review Board (or equivalent) reviews research involving human participants to ensure risks are minimized, consent is informed, and vulnerable populations are protected, especially in academic and medical contexts.

Q: What is a research-backed opportunity sizing?
A: An estimate of how many target customers have a given unmet need, how often they encounter it, how much they currently spend on workarounds, and how much they would pay — used to prioritize which opportunities to pursue.

Q: What is the difference between "must-be" quality and "attractive" quality (Kano)?
A: Must-be quality is something customers expect by default and are dissatisfied without; attractive quality delights when present but is not expected. Each behaves differently in surveys and competitive comparisons.

Q: What is a "value proposition canvas"?
A: A two-sided tool pairing a customer's jobs, pains, and gains on one side with the product's pain relievers and gain creators on the other, used to test fit between an offering and a researched segment.

Q: What is a "proto-persona" vs a "research-backed persona"?
A: A proto-persona is a draft persona built from team assumptions, used to guide early research and align vocabulary; a research-backed persona is validated against real interview and behavioral data before driving decisions.

Q: What is the "rule of three" in interview synthesis?
A: Once three independent participants share a pattern with similar language or behavior, it is usually strong enough to surface as a theme rather than being treated as anecdote.

Q: What is an "anecdote" in customer research?
A: A single participant's vivid but unreplicated story. Useful for empathy and hypothesis generation, but not evidence for a finding on its own.

Q: What is the "Mom Test" principle?
A: A book framing that the only useful questions to ask customers are about specifics of their past life (when, where, who, what), not opinions, compliments, or hypotheticals — because those reliably mislead.

Q: What is the difference between "what people say" and "what people do" in research?
A: Stated preferences and intentions are often inconsistent with revealed behavior. Strong customer research pairs what customers say in interviews with what they actually do in observational or behavioral data.

Q: What is a "North Star" research question?
A: A single, prioritized research question for a study that, if answered, would most change the team's current decision — used to keep the discussion guide and analysis focused.

Q: What is "insight" vs "observation" in research?
A: An observation is a piece of raw data (a quote, a metric, a behavior); an insight is the meaning or implication that observation carries, often stated as "so what?" plus evidence.

Q: What is a "jobs diagram" in JTBD?
A: A visual breakdown of the main job, the related sub-jobs, the emotional and functional dimensions, and the context — used to scope a JTBD study and find the most underserved sub-jobs.

Q: What is a "forces" diagram in switching research?
A: A four-quadrant visual (push, pull, anxiety, habit) applied to a specific switching moment, used in interviews to map the forces that made the customer change (or refuse to change) solutions.

Q: What is the difference between exploratory, descriptive, and causal research?
A: Exploratory research investigates an unclear problem to generate hypotheses; descriptive research measures who, what, when, where; causal research tests whether one variable actually causes a change in another, usually via experiment.

Q: What is an A/B test in customer research?
A: A controlled experiment where users are randomly assigned to two (or more) variants of a product, message, or flow, and a defined outcome is compared to determine which performed better and by how much.

Q: What is the difference between statistical significance and practical significance?
A: Statistical significance means the observed difference is unlikely due to chance; practical significance asks whether the effect is large enough to matter for the business, the user, or the design decision.

Q: What is a "p-value" in a survey or experiment?
A: The probability, assuming the null hypothesis is true, of observing data as extreme as what was collected. By convention, p < 0.05 is often used as a threshold for declaring a result "statistically significant."

Q: What is a "minimum viable product" in research terms?
A: A deliberately small, shippable version of a product or feature used to test a specific riskiest assumption with real customers, before committing to full build.

Q: What is a "fake door" or "painted door" test?
A: A research method where a not-yet-built feature is advertised (e.g. on a landing page or in-product) and demand is measured by click-through or signup rate, used to gauge interest before building.

Q: What is a "concierge" test?
A: A research method where a small number of customers are manually served (often by the founder) through a non-scalable, high-touch version of the proposed experience, to learn the job and the edge cases before automating.

Q: What is the difference between B2B and B2C research sampling?
A: B2C research can usually draw on large, relatively accessible populations; B2B research must identify specific roles, industries, and seniority levels, often producing smaller samples and heavier dependence on recruiting partners and incentives.

Q: What is a "buying center" in B2B research?
A: The set of individuals in a customer organization who participate in a purchase decision, typically including initiator, user, influencer, gatekeeper, decider, and approver roles.

Q: What is the difference between "must know" and "nice to know" in research objectives?
A: Must-know questions are decision-blocking — the team cannot proceed without the answer; nice-to-know questions are helpful for completeness but will not stop the project. Research time should be allocated accordingly.

Q: What is a research "kickoff" and what should it cover?
A: A meeting that aligns stakeholders on the research question, methods, sample, timeline, deliverables, decision it will inform, and what is explicitly out of scope — to prevent mid-study scope creep.

Q: What is "scope creep" in a research project?
A: Uncontrolled expansion of the research question, sample, or methods after the study has started, usually because a stakeholder adds a "while you're at it" question, and the leading cause of late, diluted, or unfinished studies.

Q: What is "research velocity" and why does it matter?
A: The cadence at which a team produces fresh, decision-quality evidence. Low velocity leads to decisions made on stale or no data; high velocity requires lightweight methods, reusable instruments, and a strong repository.

Q: What is a "lightweight" research method?
A: A fast, low-cost method suitable for early or frequent use (e.g. 5-user usability test, single-question in-app survey, 3-customer interview sprint), used to inform decisions without the overhead of a full study.

Q: What is the "discount usability" method?
A: A pragmatic approach that uses small samples (often 3–5 participants) per user type, runs short, iterative test cycles, and prioritizes the most severe usability issues — trading statistical completeness for speed and cost.

Q: What is a "smoke test" for a new value proposition?
A: A small, low-risk exposure of a new positioning or product idea to a subset of the market (e.g. via ad copy, landing page, or sales script) to measure real response before broader rollout.

Q: What is a "conjoint analysis"?
A: A quantitative research method that asks respondents to choose between bundles of attributes at varying levels, statistically inferring the relative importance and trade-off value of each attribute.

Q: What is the difference between "stated importance" and "derived importance" in surveys?
A: Stated importance is what respondents say matters; derived importance is calculated from their actual trade-off behavior (e.g. via conjoint or MaxDiff). The two frequently disagree, and derived importance is usually a better predictor.

Q: What is "MaxDiff" (best-worst scaling)?
A: A survey technique where respondents pick the most and least important items from a small set, repeated across many sets, to produce robust, ratio-scaled importance scores.

Q: What is "van Westendorp" price sensitivity analysis?
A: A survey method that asks respondents four questions (too cheap, cheap but not unrealistic, expensive but not unrealistic, too expensive) to map a range of acceptable prices for a product.

Q: What is a "Willcox test" for new product concepts?
A: A concept test approach that asks respondents to rate a written concept on purchase intent, uniqueness, value for money, and believability, then segments the audience by enthusiasm to identify the most receptive early customers.

Q: What is a "user story" derived from research?
A: A short, role-and-goal-framed requirement such as "As a [segment], I want to [job], so I can [outcome]," grounded in observed customer behavior rather than assumed.