Industry-Specific

Captures how satisfied customers are with a recent vehicle service or repair visit — covering communication, wait time accuracy, price transparency, and repair quality — plus an AI follow-up that reconstructs what really happened when an issue wasn't fixed the first time. Built for dealership service departments and independent repair shops tracking retention and trust.

Captures how guests rate every stage of a resort stay — booking, check-in, rooms, amenities, staff, and value — and benchmarks loyalty with a recommendation score. An AI follow-up interview digs into the specific moments that drove each guest's score, surfacing what turned a detractor sour or what would push a passive guest into a promoter. Built for resort GMs and hospitality research teams.

Captures how people and teams actually spend their time building or redesigning websites — which tools they rely on, where friction piles up, and how satisfied they are at each stage. An AI follow-up interview digs into the single biggest bottleneck respondents hit, reconstructing what happened and what workaround (if any) they used.

Captures how graduating students rate their academic program, career preparation, and overall value as they leave — with an AI follow-up that digs into the specific moments behind their satisfaction score. Built for registrars, program directors, and student success teams who need both a benchmark number and the story behind it.

Gathers structured performance ratings and behavioral feedback on a supplier's delivery, quality, and responsiveness, for procurement and vendor management teams conducting periodic reviews. An AI follow-up interview digs into the specific incident behind the lowest-rated area so scorecards reflect what actually happened, not just a number.

For organizations in high-risk professions (first responders, healthcare, social services, journalism) to understand how often staff are directly exposed to traumatic events on the job and whether current support systems actually help. An AI follow-up interview explores what support was present or missing after a recent difficult incident, without asking anyone to relive graphic details.

Captures how donors experienced your giving process, what motivates their generosity, and how they'd allocate funds across programs. Built for development and fundraising teams, with an AI follow-up that digs into the real story behind a donor's satisfaction or likelihood to give again.

Measures agreement with a set of statements using an even-numbered rating scale that removes the neutral midpoint, forcing respondents to lean agree or disagree rather than sit on the fence. Built for HR, product, and policy teams who want to reduce central-tendency bias in attitude research. The AI follow-up digs into the concrete reason behind each respondent's strongest lean and what would change their mind.

Captures why homeowners adopt or hesitate on solar, how they rate their installer and system performance, and how confident they are in projected savings. Built for installers, utilities, and researchers tracking adoption drivers — the AI follow-up interview reconstructs each respondent's real decision journey and any gap between what was promised and what they actually experienced.

A psychographic battery that segments respondents by how they think and feel about shopping — browsing for fun vs. necessity, planning vs. impulse, price-driven vs. brand-loyal — paired with an AI follow-up that unpacks the story behind their most recent unplanned purchase. Built for retail, e-commerce, and CPG teams building shopper segments.

Measures how a patient experienced a specific provider visit — getting the appointment, provider communication, staff courtesy, and an overall rating — modeled on the CAHPS Clinician & Group Visit 2.0 survey used across medical practices and health systems. An AI follow-up interview digs into the exact moment or interaction that drove the patient's overall rating, turning a single number into an actionable story.

Captures how people are actually pursuing personal growth — which areas they're working on, how consistently they show up, and what's really stopping them — with an AI follow-up interview that digs into the real story behind their biggest obstacle. Built for coaches, app makers, and researchers studying habit formation and motivation.

Captures how candidates experience your job application process — from finding the posting to hitting submit — covering clarity, length, and communication. Built for recruiting and HR teams, with an AI follow-up that reconstructs the exact moment an applicant almost gave up or felt confused, rather than just averaging satisfaction scores.

Captures how applicants experienced your scholarship's application process — from discovery through submission — including clarity, effort, and sticking points. An AI follow-up interview digs into the single biggest obstacle each applicant hit, so program staff know exactly what to fix before the next cycle.

Gathers what a prospective client needs, why it matters now, and how ready they are to move forward — built for agencies, consultants, and professional services firms onboarding new business. The AI follow-up interview digs past the surface request to uncover the real problem, constraints, and definition of success behind it.

Explores how people taking GLP-1 medications (semaglutide, tirzepatide, and similar) approach exercise — workout frequency, strength training, muscle-preservation concerns, and goal prioritization — with an AI follow-up that digs into the reasoning behind their top fitness goal or biggest barrier. Built for gyms, fitness apps, and health researchers studying this fast-growing population.

Measures how undergraduates rate advising, coursework, facilities, wellness support, and belonging, plus overall satisfaction and improvement priorities. Built for provosts, deans of students, and institutional research teams. The AI follow-up interview digs into the story behind each student's satisfaction score, surfacing specific moments and unmet needs that ratings alone miss.

Explores how people choose, pay for, and feel about movie rentals — from kiosks to on-demand streaming rentals — covering catalog satisfaction, pricing thresholds, and feature priorities. An AI follow-up interview digs into the specific decision behind a respondent's most recent rental to surface real friction, not just stated preferences. Built for streaming platforms, kiosk operators, and video-on-demand teams.

Measures how customers rate an online retailer on price, selection, site experience, shipping, and service, plus what drives loyalty versus defection to a competitor. An AI follow-up interview reconstructs the specifics of a recent order to explain the ratings instead of leaving them as abstract scores.

Assesses whether employees can actually find, trust, and contribute to your organization's documentation, wikis, and knowledge base — with an AI follow-up that reconstructs a real moment someone got stuck instead of relying on abstract satisfaction ratings. Built for IT, L&D, and operations teams evaluating or improving a knowledge management system.