Industry-specific survey templates

A structured scorecard for interviewers to rate a candidate right after a screen, panel, or onsite round — covering core competencies, standout strengths, and a hire recommendation. An AI follow-up interview digs into the reasoning behind borderline scores so hiring committees get real evidence, not just a number.

Assesses how consistently frontline staff (food service, healthcare, childcare, hospitality) follow personal hygiene protocols, what gets in the way, and where facilities or training fall short. An AI follow-up interview reconstructs a real recent moment of non-compliance instead of relying on self-reported good intentions, giving managers concrete, actionable gaps to fix.

Measures how a team is actually performing — goal clarity, communication, accountability, and delivery speed — from the perspective of the people doing the work. Built for managers and HR/People teams running quarterly or post-project pulse checks. An AI follow-up interview digs into the specific incident behind the biggest rated gap instead of leaving it as a vague score.

Captures how current and former U.S. service members experience training, leadership, benefits, and the shift to civilian life. Built for veteran support organizations, military HR, and transition programs, with an AI follow-up interview that digs into the real story behind each respondent's recommendation score.

Measures how employees experience booking, policy, and support for company travel — flights, hotels, expense reimbursement, and duty of care — with an AI follow-up that reconstructs exactly what went wrong on a recent trip instead of a vague complaint. Built for HR, travel management, and finance teams evaluating their travel program.

Measures how people actually experience dating apps and sites — match quality, trust, safety, and what drives satisfaction — for dating product teams and researchers. An AI follow-up interview reconstructs a real recent match or date instead of relying on vague satisfaction ratings.

Tracks overall satisfaction, satisfaction with specific product and service attributes, and likelihood to recommend, then prioritizes which fixes matter most with a trade-off ranking. An AI follow-up interview digs into the real story behind each respondent's satisfaction score. Built for product, CX, and support teams running quarterly or post-interaction pulse checks.

Captures how shoppers rate a specific store visit — cleanliness, staff, stock, layout, checkout — plus overall satisfaction and likelihood to recommend or return. An AI follow-up interview digs into the real friction behind any low ratings, like a specific stockout or a bad checkout interaction, so store ops teams know exactly what to fix.

Measures how easy, clear, and trustworthy the rental application and verification process felt to a customer — from choosing a channel to submitting documents and reviewing terms — with an AI follow-up that digs into exactly where friction or confusion occurred. Built for car rental companies and booking platforms optimizing signup and verification flows.

Captures how people discover, choose, and feel about the online video and streaming content they watch — device usage, time spent, value perceptions, and decision drivers — with an AI follow-up that digs into the real story behind a recent subscription decision.

A flexible agree-disagree battery for measuring attitudes toward a product, policy, workplace practice, or service — built around a classic multi-statement rating grid. Swap in your own statements, then let the AI follow-up dig into the reasoning behind whichever statement swayed the respondent's opinion most, closed or neutral answers included.

Gauges interest in an upcoming workshop — topics, format, timing, and what would actually get someone to register — so organizers can finalize an agenda people show up for. An AI follow-up interview digs into the real reasons behind a respondent's likelihood-to-attend score, surfacing scheduling conflicts, unclear value, or content gaps that closed questions alone would miss.

Explores how travelers choose, book, and experience vacation trips — from destination trade-offs and price sensitivity to satisfaction with the actual experience. An AI follow-up interview digs into the real story behind a recent trip, surfacing moments of friction or delight that closed-ended ratings miss. Built for travel brands, tour operators, and hospitality teams.

Measures how much people trust, understand, and would actually use self-driving cars — covering safety concerns, pricing sensitivity for autonomous features, and adoption triggers. The AI follow-up interview digs into the real reasoning behind each respondent's trust score instead of settling for a number.

Maps who your target market is, what they need, how they weigh price against other factors, and where they currently go instead of you — with an AI follow-up that surfaces the real trigger behind their choice. Built for product, marketing, and research teams sizing up a market or segment before a launch, repositioning, or expansion.

Measures how satisfied listeners are with their primary streaming service, which features actually drive loyalty, price sensitivity for premium tiers, and how people discover new music — with an AI follow-up that digs into the real reasons behind switching or staying instead of surface-level satisfaction scores.

Captures how candidates actually experienced your hiring process, from finding the posting through interviews, communication, and outcome. An AI follow-up interview digs into the single moment that most shaped their impression of your company, surfacing friction that closed-ended ratings miss. Built for talent acquisition and HR teams benchmarking or improving their pipeline.

Measures how subscribers rate their cable or satellite TV provider on channel lineup, reliability, price, and support — and uses an AI follow-up to dig into the real reasons behind cord-cutting consideration. Built for pay-TV providers and MVPDs tracking churn risk and renewal drivers.

Collects player experience, format preferences, and logistics details from tournament registrants, plus an AI follow-up that digs into what would make the day feel worth their time and money. Built for charity, corporate, and club golf tournament organizers planning format, pairings, and add-ons.

Measures how easy, fair, and transparent employees find the process of requesting vacation, personal, or sick time — from submission method to manager responsiveness and decision speed. Built for HR and people-ops teams auditing their leave policy, with an AI follow-up that reconstructs exactly what happened on a recent request instead of relying on vague satisfaction ratings.

Tests two or more ad copy variants head-to-head for clarity, appeal, believability, and relevance before a campaign goes live. Built for marketers and copywriters choosing between headline or messaging options. The AI follow-up interview digs into which specific words or phrases drove the winning ad and what would need to change to make the others land.

Captures why someone reached out through a general inquiry or 'contact us' channel, how easy that process was, and what outcome they're hoping for — with an AI follow-up that digs into the specific need behind the inquiry so teams can route and respond faster. Built for support, sales ops, and customer service teams triaging inbound contact.

Captures the facts of a workplace accident or near-miss — what happened, where, how severe, and what conditions contributed — for safety officers and EHS teams. An AI follow-up interview reconstructs the sequence of events in the employee's own words and probes for root causes that a checklist alone would miss.

Tracks how people actually spend time across streaming, social, news, podcasts, and print, which factors drive platform and subscription choices, and how much they trust what they consume. An AI follow-up interview digs into the story behind a recent change in habits — a dropped subscription, a new app, or a shift away from a channel — instead of just the stated reason.

Captures real-world eating and activity patterns, what's blocking consistency, and what actually keeps people motivated — for wellness programs, coaches, and fitness apps designing support that matches how people actually live. An AI follow-up interview digs into the specific barrier behind someone's confidence score instead of settling for a generic checkbox.

Captures how passengers rated every touchpoint of a recent flight — booking, check-in, boarding, cabin service, and disruption handling — and prioritizes which improvements matter most. An AI follow-up interview digs into the specific moment that drove the passenger's overall rating, surfacing the concrete 'why' behind the score.

Captures how visitors reacted to a specific property right after touring it — first impressions, price perception, and likelihood to make an offer — for listing agents and sellers. The AI follow-up interview digs into the specific hesitations or dealbreakers behind a visitor's purchase interest instead of settling for a generic rating.

Gathers what participants actually want to give and receive in your Secret Santa exchange — budget comfort, gift categories, restrictions, and logistics preferences — plus an AI follow-up that digs into what made past exchanges feel great or fall flat, so organizers can set rules that actually work.

Assesses how much sleep loss is affecting your workforce's alertness, mood, and safety on the job — built for HR, EHS, and shift-operations teams. An AI follow-up interview digs into the real story behind a recent fatigue-related close call or bad day, surfacing root causes that a checklist alone would miss.

Maps how employees prefer to send and receive information at work — channel choices, clarity gaps, and communication traits that matter most to them — with an AI follow-up interview that reconstructs a real recent miscommunication instead of relying on abstract self-ratings.

Measures how well a school, museum, or organizational field trip delivered on learning value, logistics, and safety, gathered from teachers, chaperones, and parents — with an AI follow-up that reconstructs the specific moment the trip clicked or fell apart instead of relying on a single satisfaction score.

Captures how people rate their overall life satisfaction alongside specific domains — health, finances, work, relationships, and community — then uses an AI follow-up to dig into whichever domain is dragging scores down. Built for wellbeing researchers, HR teams, city planners, and health programs that need both the numbers and the lived reasons behind them.

Measures how often people read, which formats and genres they gravitate toward, and what drives their book choices — built for publishers, bookstores, libraries, and content platforms. An AI follow-up interview reconstructs the real decision behind a recent book pick or drop-off, not just the stated preference.

Assesses how big and reachable the opportunity is for a new product, service, or market entry — awareness, purchase intent, price tolerance, and competitive standing — for product and strategy teams, with an AI follow-up that probes the real reasons behind stated purchase intent.

Captures how attendees experienced a seminar or conference session — content quality, speaker delivery, logistics, and likelihood to return — with an AI follow-up interview that digs into the specific moment satisfaction rose or fell instead of settling for a generic rating. Built for event organizers, training teams, and association program committees.

Captures graduating students' satisfaction with their program, how prepared they feel for their next step, and where the institution should invest next — built for registrars, program directors, and career services teams closing out a cohort. An AI follow-up interview digs into the real reasons behind low preparedness or satisfaction scores instead of stopping at a number.

For students leaving a university — whether they graduated, withdrew, or transferred — this survey captures how they rate teaching, advising, support services, and overall value, then uses an AI follow-up interview to dig into the real story behind their satisfaction score instead of settling for a flat rating.

Tracks how the public rates the current President's overall performance, trust, and handling of specific issues like the economy and foreign policy — for pollsters, newsrooms, and researchers who need a quick pulse read. An AI follow-up interview digs into the specific event or issue actually driving each respondent's rating, not just the label they picked.

Captures how guests rated check-in, room quality, staff, and value after a recent stay, plus their likelihood to recommend and rebook. An AI follow-up interview digs into the real story behind their score — what made or broke the stay — so hotel teams get specifics, not just star ratings.

Captures how diners rate food, service, value, and atmosphere after a specific visit, plus their likelihood to recommend and return. An AI follow-up interview digs into the concrete moment behind their recommendation score — what stood out or went wrong — so the team gets specifics they can act on, not just star ratings.

Measures how well employees are able to separate work from personal life, where the biggest pressure points come from (workload, schedule unpredictability, always-on culture), and how supported they feel by managers. The AI follow-up digs into the single most disruptive factor each person names, surfacing a concrete recent example instead of a vague complaint.

Measures how satisfied faculty are with compensation, workload, research support, governance, and career advancement, plus how many are seriously considering leaving. Built for provosts, deans, and faculty affairs offices; the AI follow-up interview digs into the specific reasons behind low scores or leaving intentions rather than just the numbers.

Measures whether your team-building activities actually strengthen trust, communication, and belonging — and which formats are worth repeating versus retiring. Includes prioritization and budget-allocation exercises for planning future events, plus an AI follow-up interview that digs into the specific moment that most changed how someone works with their teammates.

Gathers structured peer feedback on a specific colleague's collaboration, reliability, and communication habits, plus a best-worst ranking of their standout strengths. An AI follow-up interview digs into a concrete recent example behind the ratings, so the feedback reads as evidence, not just scores.

Captures direct reports' candid ratings of their manager's communication, feedback, recognition, and follow-through, plus a best-worst trade-off on which leadership qualities most need development. The AI follow-up interview digs into the concrete story behind the lowest-rated behavior instead of settling for a number.

Measures how candidates experienced your hiring process — from application clarity through interview scheduling, communication, and final outcome — with an AI follow-up that digs into the specific moment that made or broke their experience. Built for talent acquisition teams benchmarking and improving candidate experience.

Tracks how often people watch movies, which formats and platforms they use, and what drives their viewing choices — built for studios, streaming services, and theater chains. An AI follow-up interview reconstructs the decision journey behind a respondent's most recent movie, surfacing friction points closed questions miss.

Explores how people taking GLP-1 medications (Ozempic, Wegovy, Mounjaro, Zepbound, etc.) actually order, eat, and evaluate restaurant meals now that their appetite has changed. Combines portion satisfaction, trade-off prioritization, and an AI follow-up interview that reconstructs a real recent meal to surface concrete menu and pricing fixes. Built for restaurant chains, menu R&D teams, and food-service researchers.

Captures how players actually experience difficulty tuning, progression pacing, monetization fairness, and moment-to-moment session enjoyment. Built for game designers and live-ops teams tracking post-launch sentiment, with an AI follow-up that digs into the specific moment a player felt cheated by difficulty or monetization instead of a generic complaint.

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.