Industry-specific survey templates

Captures the dietary restrictions, allergies, and intolerances your customers or diners live with, how strictly they follow them, and where current food options fall short — with an AI follow-up that digs into a real recent incident where those needs weren't met and what would have prevented it.

Measures how disagreements and tensions actually get surfaced, escalated, and resolved on a team — covering frequency, fairness, psychological safety, and preferred resolution paths. Built for HR and people leaders; an AI follow-up interview reconstructs one real, recent conflict in detail instead of relying on abstract ratings alone.

Captures how clients experience individual coaching sessions — perceived progress, coach effectiveness across key behaviors, and likelihood to continue or recommend. An AI follow-up interview digs into the specific moment behind their recommendation score, surfacing what actually drove or undermined value in the session.

A structured post-lesson observation form for instructional coaches, administrators, and peer observers to rate teaching practices, student engagement, and instructional strategy — with an AI follow-up interview that reconstructs the specific moments behind the ratings so feedback is concrete enough to coach from.

Captures how confidently people managing food allergies navigate menus, ingredient labels, and staff interactions at restaurants and food brands — and where that trust breaks down. An AI follow-up interview reconstructs their most recent close call or unclear-labeling experience in detail. Built for restaurants, food manufacturers, and allergy-focused brands.

A periodic check-in that measures how often people reflect, how self-aware they feel, and what's actually blocking deeper reflection — paired with an AI follow-up that walks through one real moment of insight instead of vague self-ratings. Built for coaches, HR wellbeing programs, and personal-development tools tracking growth over time.

Captures how employees see their progress at the midpoint of the year — goal status, manager support, obstacles, and priorities for the second half — so managers and HR can course-correct before year-end reviews lock in. An AI follow-up interview reconstructs the real story behind each person's progress rating and top obstacle instead of just the label they picked.

Maps what people actually eat, which cuisines and attributes they favor, and what really drives a food choice in the moment — price, health, convenience, or taste. Built for food brands, restaurants, and meal-kit teams shaping menus or products. An AI follow-up interview reconstructs the last real meal decision instead of relying on stated preferences alone.

Measures how satisfied clients or stakeholders are with a completed or in-flight project — covering scope clarity, timeliness, budget adherence, communication, and deliverable quality — with an AI follow-up that digs into the real story behind the overall rating instead of a generic star score. Built for agencies, consultancies, and internal project teams running post-project or milestone reviews.

Measures how often people watch TV news and read newspapers, which formats and sources they trust most, and what factors drive their choice of news media — with an AI follow-up that uncovers the real story behind rising or falling engagement. Built for media researchers, broadcasters, and publishers tracking audience shifts.

Explores how customers actually use their debit card day to day — spend allocation, fees, fraud concerns, and feature priorities — with an AI follow-up interview that uncovers the real story behind a decline, surprise fee, or trust issue instead of stopping at a satisfaction score. Built for banks, credit unions, and fintechs evaluating their debit card experience.

Compares how current Apple and Samsung owners rate each brand on camera, battery, software, design, and value, then uses a best-worst trade-off and point allocation to surface what actually drives purchase decisions. An AI follow-up interview digs into the real trigger behind brand loyalty or a planned switch. Built for mobile brand and product teams.

Measures how deeply customers feel emotionally tied to your brand — beyond satisfaction or loyalty scores — covering identity, nostalgia, trust, and sense of loss. An AI follow-up interview surfaces the specific memory or moment that created the strongest bond, giving qualitative color behind the numbers.

Explores how people actually spend their free time, how satisfied they are with that balance, and what gets in the way of doing more of what they enjoy. Built for leisure, wellness, media, and lifestyle brands mapping real behavior, not stated preferences — with an AI follow-up that reconstructs a specific recent moment when leisure time fell short.

Measures how donors, volunteers, board members, and program participants feel about a non-profit's transparency, impact, and communication — with an AI follow-up that digs into the real reasons behind loyalty or hesitation instead of surface-level satisfaction scores. Built for development, program, and communications teams.

Measures how people access, experience, and think about STI/STD testing services — testing frequency, comfort with providers, and the practical or emotional barriers that keep people from testing regularly. Built for sexual health clinics and public health teams, with an AI follow-up that digs into the real reasons behind gaps in testing behavior.

Measures how LGBTQ+ audiences and allies encounter and judge queer representation in film, TV, and streaming — how often they see it, where, and whether it feels authentic — with an AI follow-up interview that digs into one specific portrayal that shaped their view. Built for media researchers, studios, and advocacy orgs.

A fast, in-the-moment feedback survey using simple smiley-face ratings across the key touchpoints of a visit (overall experience, staff, speed, environment) — built for retail, hospitality, healthcare, and other service settings. An AI follow-up interview digs into the 'why' behind the overall rating so low scores aren't a mystery and high scores reveal what to protect.

Explores how households think about switching to or expanding renewable energy — current usage, the trade-offs that matter most, and what's holding people back. An AI follow-up interview digs into the real story behind the biggest barrier or motivation a respondent picks, going beyond checkbox answers. Built for utilities, solar installers, and energy programs sizing demand and messaging.

Evaluates how customers research, compare, and buy consumer electronics from your store — covering website usability, price perception, and trust in shipping/support — with an AI follow-up that reconstructs the real decision journey behind their most recent purchase. Built for e-commerce and electronics retail teams optimizing conversion and retention.

Measures how prone employees are to feeling bored or understimulated at work, using a trait-style statement battery, situational triggers, and coping responses. Built for HR, L&D, and people-analytics teams. An AI follow-up interview reconstructs a real recent boring moment to separate personality-driven boredom proneness from fixable role-design problems.

Measures how motivated, supported, and connected colleagues feel day to day, benchmarks a recommend-to-a-friend engagement score, and identifies which drivers (recognition, growth, workload, manager support) matter most. An AI follow-up interview digs into the real story behind each person's score instead of settling for a number.

Evaluates how well your company's internal communications inform, engage, and reach employees across channels like email, town halls, and chat tools. Includes a statement battery and a prioritization exercise, plus an AI follow-up that digs into a specific recent example of a communication that worked or fell short.

Measures how much control people feel they have over key areas of their life — work, money, health, relationships, and time — plus what's driving that feeling. An AI follow-up interview digs into the one domain where control feels lowest, reconstructing a real recent moment instead of relying on abstract self-ratings.

Measures how easy, clear, and satisfying your product's interface is to use in real day-to-day tasks — combining a multi-element usability rating, a trade-off exercise on what to fix first, and an AI follow-up interview that reconstructs the exact moment a user got stuck instead of relying on vague complaints.

Measures how project teams actually use their construction project extranet for document control, RFIs, and drawing markup, and where version confusion or slow approvals cost time. An AI follow-up interview reconstructs a specific recent incident to surface the real workflow friction behind the ratings.

Uncovers which retirement housing features — cost, location, care access, privacy, community life — actually drive decisions, using trade-off exercises and price sensitivity questions instead of simple ratings. Built for senior living operators, developers, and planners, with an AI follow-up that probes what respondents would sacrifice to secure their top priority.

Qualifies and recruits candidates for a focus group by screening for category usage, conflicts of interest, prior research participation, and scheduling fit, then capturing core demographics. An AI follow-up interview asks candidates to describe their real experience with the topic in their own words, surfacing rehearsed 'professional respondent' answers and gauging how articulate and engaged they'll be in the room.

A guessing-game survey for partners, family, friends, or teammates to test how accurately they can predict someone's habits, preferences, and values — with an AI follow-up that unpacks the reasoning behind their most confident (and shakiest) guesses. Built to be customized with the actual subject's traits before sending.

Captures how shoppers choose, evaluate, and switch between grocery stores and channels — price sensitivity, loyalty behavior, and channel mix — for retail and CPG researchers. An AI follow-up interview digs into the real story behind a shopper's most recent store choice or channel switch, beyond what a closed question can capture.

Benchmarks your store against named competitors on price, selection, service, and convenience, then uses an AI follow-up to reconstruct the specific moment a shopper chose one store over another. Built for retail insights teams tracking share-of-wallet and competitive positioning.

Measures how often people actually buy organic food, which certifications and claims really drive the decision, trust in organic labeling, and price sensitivity — with an AI follow-up interview that reconstructs the real story behind a recent organic purchase (or skip) instead of a generalized attitude.

A relationship health check that scores satisfaction, trust, intimacy, communication, and love languages, then uses an AI follow-up interview to dig into whichever dimension scored lowest. Built for dating apps, matchmakers, and relationship coaches who need more than a vague compatibility score.

Uncovers what actually drives shoppers to pick and stay loyal to a supermarket — price, freshness, convenience, or rewards — using a best-worst trade-off exercise, a satisfaction battery, and an AI follow-up interview that reconstructs the real story behind a recent switch or near-switch. Built for grocery retail and category insights teams.

Measures how satisfied employees are with the substance of their job — the tasks, autonomy, variety, skill fit, and workload — separate from pay or manager quality. Built for HR and people-ops teams running role-design reviews, with an AI follow-up that digs into the specific task or moment behind their lowest-rated aspect of the work.

Measures how often employees experience or witness gender-based discrimination — in pay, promotion, meetings, and everyday treatment — and how safe they feel speaking up. An AI follow-up interview reconstructs a specific incident in the respondent's own words, revealing what actually happened and what response would have felt fair, for HR and DEI teams benchmarking climate and prioritizing fixes.

Maps how shoppers browse, search, and decide across in-store, online, and marketplace channels — where product searches succeed or break down, which purchase factors carry the most weight, and what an AI follow-up interview uncovers about the last time someone couldn't find what they wanted. Built for retail, e-commerce, and merchandising teams optimizing search, navigation, and discovery.

Measures how productive, focused, and supported employees feel while working remotely, and pinpoints the specific barriers eating into their day. An AI follow-up interview digs into the single biggest barrier each person identifies, reconstructing a real recent workday instead of relying on generalized complaints.

A point-factor job evaluation questionnaire for HR and compensation teams grading or re-grading a role — covering decision authority, supervisory scope, effort, and working conditions, with an AI follow-up that pressure-tests the scoring against a real high-stakes task the job has actually handled.

Captures how graduating students rate their academics, career readiness, and campus life as they head out the door, plus their post-graduation plans and likelihood to recommend the school. An AI follow-up interview digs into the specific moment or decision behind their lowest-rated aspect instead of settling for a generic score. Built for institutional research and student affairs teams running exit polls each term.

Surfaces what people genuinely value most — career, family, health, growth, community, freedom — and how closely their daily choices match those priorities. Useful for coaches, HR teams, and researchers studying wellbeing or culture fit. The AI follow-up interview digs into the story behind a respondent's top value and any gap between stated priorities and lived time.

Assesses how prepared people actually felt, what emergency communications and procedures worked, and where gaps showed up during a real event or drill. Built for emergency management teams, facilities, and HSE departments benchmarking readiness, with an AI follow-up that reconstructs exactly what happened during the respondent's most recent disaster or drill instead of relying on general perceptions.

Measures how students experience a professor's teaching across clarity, engagement, feedback, availability, and fairness, plus overall satisfaction and likelihood to recommend. Built for academic departments and course coordinators running end-of-term reviews, with an AI follow-up interview that digs into the specific moment or assignment that most shaped a student's rating.

Captures how patients experience a physician practice end-to-end — scheduling ease, wait times, physician communication, and likelihood to recommend — with an AI follow-up that digs into the 'why' behind recommendation scores, especially from patients who were lukewarm or dissatisfied. Built for practice managers and physician groups tracking patient experience.

Measures how often people drink energy drinks, which brands and formats they choose, what drives that choice, and what they'd pay for a new product. Built for beverage brand and category teams, with an AI follow-up interview that reconstructs the real story behind a recent brand switch or purchase decision instead of relying on stated preference alone.

Captures how easily visitors accomplish what they came to do on your site — navigation, speed, content clarity, and overall satisfaction — with an AI follow-up that digs into the exact moment a task succeeded or broke down. Built for product, UX, and marketing teams running ongoing site feedback.

Explores how people actually decide whether to drive after drinking — the alternatives they use, the barriers that get in the way, and how risky they think it really is. Built for road-safety agencies, employers, bars, and rideshare or insurance programs designing prevention campaigns. An AI follow-up interview reconstructs the last real decision point instead of hypothetical good intentions.

Measures awareness, support, and concerns among residents near a wind energy project — covering noise, visual impact, trust in the developer, and perceived local benefits. An AI follow-up interview digs into the real reason behind each respondent's level of support, giving developers and utilities the qualitative context behind the numbers before community meetings or permitting decisions.

Captures how satisfied people feel about their life overall, what they value most, and how their time and energy actually line up with those values. Built for researchers, coaches, and wellbeing programs who want more than a satisfaction score — the AI follow-up digs into why that score is what it is and where priorities and daily life have drifted apart.

Measures how people actually use a social networking platform — frequency, trust, feature value, time allocation, and loyalty via a recommendation score. Built for product, growth, and trust & safety teams at social platforms and community apps. The AI follow-up interview digs into the specific moment behind each promoter or detractor score instead of generic praise or complaints.