市場調査アンケートテンプレート

Tests how a set of logo or visual identity options perform on recognition, brand fit, emotional tone, and head-to-head preference. Built for brand and marketing teams comparing logo candidates or evaluating a redesign, with an AI follow-up that digs into the specific visual cues driving the winning choice instead of just recording a rank.

Captures what shoppers came to buy, how they navigated the store, what they did when an item was missing, and how checkout felt — with an AI follow-up that digs into the real reasoning behind substitution choices and navigation friction. Built for retail insights and category management teams.

Reconstructs the full journey behind a considered purchase — how customers first discovered the product, which sources shaped their decision, what nearly stopped them, and how confident they feel now. An AI follow-up rebuilds the actual sequence of events around the moment of hesitation, not just the tidy summary customers give afterward.

Measures which features customers want bundled together, how much value each feature category adds, and what they'd pay if features were sold à la carte — built for product and pricing teams designing tiered packaging. An AI follow-up unpacks the reasoning behind a respondent's top-ranked bundle instead of stopping at the ranking itself.

Measures how deal-driven your customers really are: what triggers a discount-motivated purchase, whether frequent promotions erode brand perception, and how willing shoppers are to pay full price. An AI follow-up reconstructs the last purchase decision they made under a discount to separate genuine price sensitivity from habit.

Measures how customers react to an upcoming or recent price increase — their acceptance thresholds, likelihood to churn, need to re-justify the value, and preferences for how the change is communicated. An AI follow-up digs into the specific reasoning behind each customer's churn risk score, surfacing what would actually change their mind versus what they say in the closed-ended scales.

Measures how prepared people feel for retirement — perceived savings adequacy, understanding of plan mechanics, and where they turn (or don't turn) for advice. Built for financial services, benefits, and wealth-management teams. An AI follow-up probes the reasoning behind the respondent's confidence score, surfacing the specific knowledge gaps and unmet advice needs that generic satisfaction scores miss.

A general-purpose consumer study covering category usage, brand awareness, buying criteria, and willingness to pay — the workhorse market research questionnaire, upgraded with unaided-first question order, a screener, and AI probing of the purchase story behind the checkboxes.

Map your brand's personality on classic semantic differential scales — traditional vs. innovative, corporate vs. human, premium vs. affordable — and compare against a competitor. The AI interviewer chases the associations behind the ratings, so you learn where the perception comes from.

Paste your landing page copy, ad, or email and see exactly which phrases pull people in and which lose them: respondents highlight the words that resonate and the words that create doubt, then an AI interviewer probes why. Sharper than a star rating on the whole block.

A voice AI debrief for closed deals — won or lost. Buyers tell an AI interviewer things they'd never tell the salesperson: the real decision criteria, who else was in the running, where the pitch missed, and what nearly changed the outcome. Structured questions make results comparable across deals.

A voice AI discovery interview that follows Mom Test rules automatically: past behavior, not hypotheticals; specifics, not compliments. It asks about the last time the problem happened, what it cost, and what they've already tried — the questions founders forget to ask when a polite prospect starts flattering their idea.

A choice-based conjoint that shows respondents realistic product profiles built from attributes and levels — plan tier, price, support, contract terms — and measures which combinations win. AI follow-ups capture the reasoning behind choices that a choice matrix alone can't explain.

Force real trade-offs with best-worst scaling: respondents pick the most and least valuable feature in rotating sets, then an AI interviewer probes the reasoning behind their top pick. Produces a true preference ranking instead of everything-is-important rating inflation.

Prioritize waitlist signups by qualifying use case fit, urgency, decision authority, and advocacy potential. Designed for pre-launch SaaS and tool-based products targeting founders and early-stage teams.

Measures how clearly, credibly, and compellingly a value proposition communicates to target audiences, identifying perceived benefits, barriers to action, and messaging improvements to optimize conversion.

Measures category usage patterns, occasion drivers, unmet needs, and brand perceptions to benchmark competitive positioning. Suitable for market researchers conducting brand health or category landscape studies.

Measures what motivates leisure travelers' destination choices, what constrains them, and how they allocate time and budget—designed for DMOs, tourism boards, and travel brands conducting market segmentation research.

Identifies operational challenges across cash flow, marketing, hiring, and software tools among small business owners and freelancers to inform fintech product strategy and feature prioritization.

Measures brand awareness, perception shift, and purchase intent following a corporate rebrand. Designed for market researchers benchmarking post-rebrand lift against baseline data and identifying messaging risks across key consumer segments.

Measures speed, accuracy, staff hospitality, and overall satisfaction for fast-food drive-thru visits to identify key experience drivers and improvement priorities.

Measures product-market fit among active users using the Sean Ellis 'very disappointed' framework, supplemented by usage patterns, competitive alternatives, and qualitative feedback to identify fit signals and improvement priorities.

A structured instrument for validating pain points, mapping current workarounds, and testing solution concept appeal with early adopter segments. Designed for product and market research teams conducting pre-launch validation in 6–9 minutes.

Identifies and ranks the most pressing operational challenges faced by startup founders and operators, measuring frequency, severity, and willingness-to-pay to inform product roadmap and pricing decisions.

Measures consumer price thresholds across single and multipack sizes using price sensitivity methodology. Identifies acceptable price ranges, purchase frequency, and pack-size preferences to inform pricing strategy.

A concept-testing instrument for restaurants evaluating new menu items. Measures appeal, perceived uniqueness, willingness to pay, and purchase intent across up to three concepts, with qualitative probing for optimization insights.

Screens and segments consumer respondents by recent purchase behavior, shopping priorities, and decision-making roles to qualify and profile audiences for targeted market research studies.

A diagnostic survey for startup founders to systematically evaluate evidence-backed certainty across customer, problem, channel, and revenue assumptions, enabling prioritized validation planning.

Evaluates how clearly a landing page communicates its value, how much trust it builds, and whether visitors intend to act. Ideal for UX researchers, product marketers, and CRO teams diagnosing friction and optimizing conversions.

Classifies product features into Must-Be, Attractive, One-Dimensional, and Indifferent categories using the Kano model methodology. Designed for product teams seeking to prioritize their roadmap based on how features drive customer satisfaction.

Maps unmet and over-served outcomes among current product users using Jobs-to-Be-Done methodology. Use it to calculate opportunity scores, prioritize features, and validate roadmap decisions.

Validates ideal customer profile assumptions by mapping tool triggers, value drivers, and purchase signals across founder and operator segments. Designed for B2B startups refining go-to-market targeting.

Identifies early adopter segments by measuring problem severity, experimentation behavior, bug tolerance, and adoption influence. Use with prospective beta testers or tool evaluation panels to prioritize product roadmap and recruit champions.

A psychographic and behavioral segmentation instrument for understanding how consumers discover, evaluate, and choose brands. Use it to build data-driven personas, size market segments, and inform targeting strategy.

Measures consumer feature preferences through forced-choice pairwise comparisons, attribute importance rankings, and purchase intent for portable consumer electronics. Designed for market researchers seeking to identify which product attributes most influence buying decisions.

Identifies why customers switch service providers, what barriers they encounter, and where conversion friction occurs — designed for product, marketing, and CX teams seeking to reduce churn and improve competitive win rates.

Measures unaided and aided brand awareness, image associations, value perceptions, purchase intent, and NPS against key competitors to benchmark brand health and identify competitive positioning opportunities.

Measures when and why shoppers enter a product category, the decision drivers behind brand selection, and the path to purchase—providing actionable insights for brand positioning, retail activation, and category growth strategy.

Measures unaided and aided brand awareness, category usage, consideration sets, first-choice preference, and perceptual brand equity attributes. Designed for tracking brand health over time across competitive sets.

Measures advertising recall, brand awareness (unaided and aided), consideration lift, and brand preference across major money and payment apps. Designed for market researchers evaluating fintech campaign ROI.

Measures unaided recall and recognition accuracy of brand logos, color palettes, and taglines to benchmark brand asset attribution strength across audience segments.

Measures top-of-mind recall, aided brand awareness, brand associations, and purchase consideration to benchmark a target brand against competitors. Suitable for market researchers tracking awareness across channels and audiences.

Measures unaided brand recall, aided recognition, and consideration-set drivers within a product category to benchmark brand awareness, track advertising impact, and inform campaign strategy.

Measures unaided brand recall, message clarity, ad relevance, call-to-action performance, and behavioral intent for e-commerce advertisements. Ideal for creative optimization and media-mix evaluation.

Measures how research teams plan projects, select and evaluate tools, and navigate procurement — providing quantitative benchmarks and qualitative depth on workflow efficiency and pain points.

A fast, fun icebreaker poll designed for teams, classes, or events. Collects lighthearted preferences and interests to spark conversation and boost meeting engagement in under 2 minutes.

A structured feedback instrument for evaluating meeting productivity, organization, psychological safety, and environment. Designed for post-meeting deployment to identify actionable improvements for recurring team meetings.

A methodologically sound NPS survey for measuring customer loyalty alongside overall satisfaction. Designed for post-interaction or periodic deployment to identify promoters, passives, and detractors, and to surface actionable drivers of customer experience.