Finance & insurance survey templates

Captures how borrowers experienced applying for a mortgage — from documentation and communication to rate transparency and closing timeline — for lenders and brokers who want to cut friction out of the process. An AI follow-up interview digs into the single biggest pain point each borrower hit, reconstructing exactly what happened instead of a vague complaint.

Measures how business borrowers experienced applying for and repaying an equipment loan — from why they picked the lender to how clear the terms felt — for lenders and finance teams tracking borrower experience. An AI follow-up interview reconstructs the actual decision journey and the moment borrowers almost walked away.

Measures how customers actually use your mobile banking app — login, transfers, bill pay, deposits — and where friction shows up, paired with a prioritization exercise for what to fix next. An AI follow-up interview reconstructs a real recent session in detail, surfacing the exact moment things broke down instead of vague complaints.

Captures how people actually budget, save, and handle debt month to month, how much financial stress they carry, and how they prioritize competing money goals. Built for banks, fintech apps, and financial coaches benchmarking real behavior instead of stated intentions. An AI follow-up interview digs into the story behind their stress level and top goal — what's blocking progress and what's actually working.

Measures how policyholders perceive their fire insurance coverage, pricing, and claims experience, and what drives renewal or switching decisions. Built for insurers and brokers benchmarking product-market fit, with an AI follow-up that reconstructs the real story behind a claim or a low renewal score instead of just the rating.

Measures how homeowners and renters perceive flood risk, what actually drives them to buy, renew, or skip flood insurance, and how they react to different premium price points. An AI follow-up interview reconstructs the real story behind each respondent's most recent coverage decision instead of just the policy status they select — ideal for insurers, agents, and public risk-communication teams.

기업 보험이 실제로 회사를 얼마나 잘 보호하는지 — 보험료 가치, 약관의 명확성, 브로커의 응대력, 청구 처리 등을 측정합니다. 고객 경험을 벤치마킹하는 보험사, 브로커, 리스크 관리자를 위해 설계되었습니다. AI 후속 인터뷰는 청구나 갱신 결정 과정에서 실제로 무슨 일이 있었는지를 재구성하여, 만족도 점수를 넘어 구체적인 사항까지 파악합니다.

Measures how policyholders experience their insurance agent — responsiveness, product knowledge, coverage fit, and claims support — with an AI follow-up that digs into the specific moment that shaped their trust (or distrust) in the agent. Built for agencies and carriers running periodic agent scorecards.

Measures how policyholders feel about their coverage, premium value, and claims experience, and gauges renewal intent before it turns into churn. An AI follow-up digs into the real story behind a recent claim or renewal decision, surfacing friction points a rating scale alone would miss. Built for insurers and brokers tracking retention and satisfaction.

신청자가 대출 절차를 어떻게 경험했는지 — 서류 제출부터 결정 통보까지 — 명확성, 속도, 노력, 만족도를 측정합니다. AI 후속 인터뷰를 통해 불만을 느꼈거나, 거절되었거나, 노력이 적었던 신청자에게 절차가 정확히 어느 지점에서 무너졌는지를 재구성하여, 대출 기관에 모호한 불만 대신 구체적인 해결책을 제공합니다.

Measures financial confidence, budgeting habits, and money stress for everyday consumers, with an AI follow-up that digs into the real story behind their biggest financial worry instead of a generic rating.

Measures how households actually track spending, allocate income, and cope with shortfalls — not just what they intend to do. Includes a spending trade-off exercise, a priority ranking of financial goals, and an AI follow-up interview that reconstructs the last time the budget broke down and what would have prevented it.

Maps what insurance policies people carry, how much they spend and on what, and how they perceive value and price fairness — with an AI follow-up interview that uncovers the real trigger behind a recent or considered provider switch, not just the stated reason.

Measures awareness, trust, usage, and barriers around stablecoins and instant payment options like Zelle, FedNow, and crypto wallets — built for banks, fintechs, and payment providers assessing product-market fit. An AI follow-up interview digs into the real experience behind each respondent's trust score and top-ranked barrier, revealing what would actually move them to adopt or switch.

사람들이 은퇴에 대해 얼마나 준비되어 있다고 느끼는지 — 저축 적정성에 대한 인식, 연금 제도 작동 방식에 대한 이해, 그리고 조언을 구하는 곳(또는 구하지 않는 곳) — 을 측정합니다. 금융 서비스, 복리후생, 자산관리 팀을 위해 설계되었습니다. AI 후속 질문은 응답자의 자신감 점수 이면에 있는 이유를 탐색하여, 일반적인 만족도 점수로는 놓치는 구체적인 지식 격차와 충족되지 않은 조언 니즈를 드러냅니다.

Measures how clients experience their financial advisor relationship — communication cadence, clarity of the financial plan, understanding of fees, and confidence in the guidance received. An AI follow-up digs into the reasoning behind confidence scores so advisory firms can see exactly what builds or erodes trust, not just a number.

Measures how clients rate your firm's advice quality, deadline reliability, fee transparency, and year-round value beyond tax season. Built for accounting and bookkeeping firms running annual or post-engagement check-ins, with an AI follow-up that digs into the specific interaction behind a client's satisfaction score instead of generic praise or complaints.

Measures new and early-stage crypto users' comprehension of gas fees, blockchain networks, and wallet/dApp permissions to identify knowledge gaps and UX friction points in Web3 onboarding flows.

Assesses treasury risk visibility, counterparty exposure management practices, and control effectiveness. Designed for treasury, risk, and front-office professionals to benchmark current capabilities and prioritize improvements.

Measures auto insurance policyholders' attitudes toward usage-based insurance (UBI) programs, covering perceived fairness, privacy comfort, feature preferences, discount expectations, and enrollment intent across current, former, and prospective telematics users.

Measures policyholder understanding of parametric triggers and trust in automated payout mechanisms, identifying key trust drivers, barriers, and basis-risk tolerance to inform product design and communication strategies.

Measures borrower satisfaction across loan statement clarity, escrow account transparency, and customer support quality to identify key drivers of retention and service improvement opportunities.

Measures consumer awareness, usage behavior, perceived barriers, use-case interest, and price thresholds for digital micropayments. Designed for market researchers studying payment innovation adoption across consumer segments.

Measures ease, clarity, trust, and drop-off points across KYC/AML identity verification flows. Designed for compliance, product, and UX teams seeking to reduce verification abandonment and improve onboarding completion rates.

Assesses team confidence in operational forecast accuracy, input quality, and scenario planning practices across functions. Designed for cross-functional teams to identify forecasting gaps, process bottlenecks, and planning improvement priorities.

Measures household financial confidence, savings buffer adequacy, debt stress, and behavioral coping strategies. Designed for consumer research panels to track financial resilience and segment by financial health.

Measures banking customers' channel usage and satisfaction, financial guidance needs and format preferences, and investment risk tolerance to inform CX strategy and product development.

Measures member satisfaction with proposal processes, voting experience, and treasury transparency in decentralized communities. Designed to identify participation barriers, trust gaps, and priority improvements for governance leads.

Evaluates self-custody wallet onboarding friction, seed phrase recovery confidence, and on-chain transaction clarity to identify UX improvements. Designed for crypto wallet product teams targeting active wallet users.

비수탁형 지갑 설정 과정, 시드 문구 복구, 네트워크 수수료 투명성에 대한 사용자의 이해도, 자신감, 선호도를 평가하여 UX 마찰 지점을 파악하고 이탈을 줄이고자 합니다.

Measures cardholder satisfaction, effort, and friction across the end-to-end dispute lifecycle—from initiation through resolution—to identify process improvements and support retention.

Measures Buy Now, Pay Later adoption patterns, provider preferences, spending thresholds, trust drivers, and consumer concerns. Designed for fintech product teams, lenders, and market researchers seeking segmentation and attitudinal insights from adult consumers.