マーケティング・グロース向けアンケートテンプレート

Captures how shoppers actually behave during Black Friday and Cyber Week: planned versus impulse buys, channel choice (in-store vs. online), deal-research habits, spending mix, and post-purchase regret or returns. Built for retail and e-commerce marketers benchmarking seasonal campaigns, with an AI follow-up that reconstructs the real story behind each shopper's most impulsive or regretted purchase.

Measures whether consumers want brands to weigh in on current events, on which types of issues, in what tone, and what backlash risk they tolerate — for marketing and comms teams weighing when to speak up. The AI follow-up reconstructs a specific recent instance the respondent remembers, uncovering the real reaction behind their ratings.

Measures how recipients actually notice, read, and act on direct mail pieces — postcards, catalogs, letters — versus digital channels, with a best-worst exercise on what drives response and an AI follow-up that reconstructs what happened after a specific piece landed in someone's mailbox. Built for marketing teams and direct mail agencies evaluating campaign performance.

Measures how well your website or marketing chatbot resolves visitor questions, builds trust, and moves people toward a purchase or signup. An AI follow-up interview reconstructs the respondent's most recent chatbot conversation in detail, surfacing exactly where it helped or broke down. Built for marketing and CX teams evaluating a live chatbot deployment.

Measures whether a specific influencer or creator campaign actually changed awareness, trust, and purchase behavior — not just impressions. Built for brand and growth marketers evaluating a campaign, with an AI follow-up that reconstructs the real moment a customer decided (or chose not) to act after seeing the content.

A self-assessment for marketers, founders, and agency teams to check how complete, resourced, and confidence-inspiring their current marketing plan actually is — covering goals, audience, budget, channels, and measurement. The AI follow-up interview digs into whichever plan component the respondent flags as weakest, uncovering the real blocker instead of a generic 'needs work' answer.

Assesses how clearly a business can articulate what makes its brand different, how consistent that identity feels across touchpoints, and where a rebrand or refresh should focus first. Built for brand consultants and marketing leads kicking off an engagement. An AI follow-up interview digs into the exact moment differentiation breaks down, surfacing concrete examples instead of vague brand talk.

Screens content writer applicants on experience, content types, self-rated skills, working style, and rate expectations. An AI follow-up interview reconstructs how a candidate actually approached a real writing sample or assignment, surfacing genuine process over rehearsed self-praise. Built for hiring managers and recruiters filling writing roles.

Screens applicants for a brand ambassador program by capturing their platforms, audience size, content style, and motivation for joining — then uses an AI follow-up interview to probe authentic brand fit and how they'd actually talk about the product, rather than just what they claim on a form. Built for marketing and influencer teams vetting candidates at scale.

Evaluates how recipients actually experience your marketing or product emails — layout, readability, mobile rendering, and visual hierarchy — rather than just open and click rates. An AI follow-up interview digs into what made a specific recent email easy or hard to act on, surfacing design friction that analytics alone won't show.

Measures how fashion marketing content — social posts, influencer collabs, email, in-store displays — actually shapes discovery and purchase decisions, not just brand recall. Includes a best-worst trade-off on content types and an AI follow-up interview that reconstructs the real moment a shopper decided to buy (or didn't).

Measures which digital marketing channels customers actually notice, trust, and act on — from social ads to email to influencer content — and how they'd prioritize messaging and budget. An AI follow-up reconstructs the specific ad moment that shaped their perception, surfacing the 'why' behind trust or annoyance that closed questions miss. Built for marketing teams evaluating channel mix, creative, and spend.

Maps how people actually spend time on social platforms, which content formats earn a follow, and how that behavior translates into purchases — with an AI follow-up interview that reconstructs a real recent purchase decision instead of relying on self-reported influence scores. Built for marketing and growth teams sizing up social strategy.

Maps how your brand actually lives in customers' minds — unaided recall, aided awareness, familiarity, image attributes, consideration, and recommend intent — plus a best-worst trade-off on what drives choice in the category. An AI follow-up interview digs into the reasoning behind low scores or shaky consideration instead of leaving it as a number. Built for brand and marketing teams tracking health over time.

Gauges how customers and prospects actually experience a company's marketing — which channels land, whether the message is clear and differentiated, and how the brand's qualities come across. An AI follow-up interview digs into the 'why' behind clarity and differentiation scores instead of stopping at the number.

Captures why donors gave to a specific fundraising or political campaign, how smooth the giving experience felt, and how likely they are to give again — with an AI follow-up that digs into the real reasons behind a donor's likelihood-to-repeat score instead of a generic satisfaction rating. Built for nonprofits, campaigns, and cause marketers running donation drives.

Tests how a specific ad lands — attention, message clarity, believability, likability, and purchase intent — plus which creative elements actually stick. An AI follow-up interview digs into the 'why' behind the intent score so you're not left guessing from numbers alone. Built for brand and creative teams pre- or post-launch.

Tests a single ad — video, print, or social creative — for clarity, appeal, relevance, and purchase impact before it goes live. An AI follow-up interview digs into the specific moment respondents got confused, bored, or excited, surfacing the 'why' behind the ratings so creative teams know exactly what to cut, keep, or clarify.

Tracks the full brand funnel — unaided and aided awareness, consideration, trial, usage, and recommendation — benchmarked against named competitors. An AI follow-up interview digs into where respondents actually drop out of the funnel and why, going beyond the numbers to the specific moment consideration stalled. Built for brand and marketing teams running quarterly brand health trackers.

Tracks where prospects and past buyers stand in the path from awareness to purchase, what drives or blocks that decision, and how price perceptions factor in — with an AI follow-up that reconstructs the specific moment someone almost bought (or almost switched away) instead of relying on generic attitude ratings.

Tracks how your brand is remembered, perceived, and chosen versus competitors — awareness, attribute ratings, and recommendation likelihood — then uses an AI follow-up to uncover the real reasons behind each respondent's recommendation score. Built for marketing teams running quarterly or annual brand health checks.

Measures the core drivers of brand strength — unaided and aided awareness, familiarity, consideration, attribute perceptions, and likelihood to recommend — benchmarked against named competitors. An AI follow-up interview probes why respondents rate the brand as they do, surfacing the perceptions behind the numbers for marketing and brand teams running health trackers.

Measures how safe, respected, and free from harassment or spam your followers feel when engaging with your brand's social media community — comments, replies, and DMs. Built for social media and community managers who need more than sentiment scores; the AI follow-up interview reconstructs a specific safety experience so you know exactly what to fix in moderation.

Tests how believable, relevant, and differentiating your candidate marketing claims are, using a best-worst trade-off to force priority among competing lines and an AI follow-up that digs into why the top claim landed or fell flat. Built for brand, product marketing, and comms teams validating messaging before a campaign launch.

Explores how comfortable customers are when brands reshare their photos, tags, reviews, or comments in marketing — and what would make them more willing to say yes. Built for marketing, social, and legal teams shaping user-generated-content and permission policies, with an AI follow-up that digs into the specific moment someone felt uneasy or declined.

Explores how parents currently manage their child's email account — what it's used for, what worries them most, and which safety features they'd actually value. An AI follow-up interview digs into the real story behind a recent scare or close call, surfacing details a checklist question can't capture. Built for teams designing kid-safe email or parental-control products.

Tracks how your brand is perceived on key attributes like trust, quality, and value, and identifies which of those attributes actually drive choice through a best-worst trade-off exercise. An AI follow-up interview digs into the story behind the respondent's lowest-rated attribute. Built for brand and marketing teams running recurring pulse checks.

Tracks unaided and aided awareness of a specific ad campaign, where people saw it, what stuck, and whether it moved them to act — for brand and media teams running always-on pulse checks. An AI follow-up interview digs into what respondents actually remember and why, surfacing the story behind the recall numbers.

Measures how subscribers actually read and value your newsletter — open habits, section-by-section ratings, and content priorities — with an AI follow-up that digs into the specific reasons behind promoter or detractor scores instead of generic satisfaction talk. Built for newsletter editors, content marketers, and community teams refining a recurring send.

Measures whether a specific ad gets noticed, understood, and acted on — covering recall, message takeaway, creative appeal, and purchase intent — with an AI follow-up that digs into the real reasons behind stated purchase intent instead of taking the number at face value. Built for marketers testing a campaign, creative concept, or media placement.

Captures gut-level reactions to a logo (or set of logo options): first impression, word associations, attribute fit, and relative preference — plus an AI follow-up that digs into which specific design element (color, shape, type, symbol) is actually driving the reaction. Built for brand, design, and marketing teams validating a new or refreshed mark before launch.

Tracks unaided and aided awareness, consideration, and perceived positioning of your brand versus named competitors among B2B buyers and influencers. Includes a best-worst trade-off on what actually drives vendor choice, plus an AI follow-up that unpacks the reasoning behind recommendation scores. Built to run quarterly for longitudinal tracking.

Gathers feedback from your followers on which platforms they use, what content they value, and whether your social presence influences real purchase decisions. An AI follow-up interview digs into the specific post or content type that stuck with them and why, going beyond generic 'I like your posts' answers.

Measures how often and how favorably customers encounter your brand when they ask AI tools like ChatGPT or Gemini for recommendations, versus competitors. An AI follow-up reconstructs the actual prompts, answers, and buying decisions behind a recent AI-assisted search.

Identifies what actually pushes users toward 5-star versus 1-star app store reviews — crashes, speed, ads, pricing, support — and what specifically would change their rating. Built for product and growth teams; the AI follow-up reconstructs the real incident behind each respondent's rating instead of generic complaints.

Identifies which topics, formats, and channels your audience actually wants more of versus what you're currently producing. Combines trade-off methods like MaxDiff and constant-sum allocation with an AI follow-up that reconstructs a real content moment — what someone consumed, why they stopped or finished it, and what's missing.

Measures whether subscribers actually open, skim, or read your newsletter, what content keeps them subscribed, their ideal send frequency, and what pushes them toward unsubscribing. The AI follow-up digs into the real moment a reader almost unsubscribed, not just the stated reason.

Captures how listeners actually consume your podcast — ideal episode length, topic preferences, ad tolerance, and what would push them to subscribe or share it — with an AI follow-up that digs into the real reason behind their loyalty score instead of a generic satisfaction number.

Measures whether a celebrity or influencer endorsement actually transfers credibility to a brand — covering perceived authenticity, trustworthiness, and purchase influence — with an AI follow-up that unpacks why the pairing does or doesn't feel believable to this specific respondent. Built for brand, marketing, and partnerships teams testing a specific spokesperson or creator campaign.

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.

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.

Find out why visitors came, whether they got it done, and what nearly stopped them. A short intercept-style survey with task success, effort, and trust measures — plus an AI follow-up that turns 'couldn't find it' into the exact page and word they were looking for.

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.

Structured stakeholder or customer feedback on a design, mockup, or creative asset: first impressions, a click on what draws attention, ratings against the brief, and file upload for marked-up versions. The AI interviewer converts 'I just don't like it' into usable direction.

Where do people click first when given a task on your design? First-click success is one of the strongest predictors of task completion. Upload your screenshot, set the task, and let the AI interviewer ask what they expected to happen — turning a click map into a usability diagnosis.

Measures consumers' willingness to share personal preferences with brands, identifies key barriers and trust drivers, and quantifies the incentive thresholds needed to increase opt-in rates. Ideal for marketing, CRM, and privacy strategy teams.

Measures perceived product value, identifies conversion blockers, and assesses upgrade intent among free trial users to inform retention and conversion optimization strategies.

Identifies perceived risks, unmet needs, and key barriers among prospective buyers to inform messaging strategy and conversion optimization.

Measures consumer comfort with personalized content, identifies privacy boundaries and data-sharing thresholds, and pinpoints messaging frequency limits to help marketing teams calibrate personalization strategies without triggering fatigue or backlash.