Customer experience survey templates

Measures how clients experienced your firm across communication clarity, responsiveness, billing transparency, and case outcome perception. Built for law firms and legal ops teams doing post-matter or annual relationship check-ins, with an AI follow-up that digs into the gap between what clients expected and what actually happened — especially around outcomes and any billing surprises.

Measures how well contractors, plumbers, and cleaners deliver on quote accuracy, punctuality, workmanship, and trust after a completed job. Built for home service businesses tracking repeat-hire risk, with an AI follow-up that digs into the specific moment trust was won or lost rather than a generic satisfaction score.

Captures how buyers and sellers rate their agent on responsiveness, market knowledge, and negotiation, plus how likely they are to refer or reuse them. An AI follow-up reconstructs what actually happened during the negotiation and closing process, surfacing the specific moments that drove satisfaction or frustration.

Captures how easy it was to book, how clients rate the service and atmosphere, whether pricing felt fair, and how likely they are to return — with an AI follow-up that digs into the real reason behind low rebooking or pricing scores instead of leaving it as a number.

Tracks how members rate equipment, cleanliness, classes, and staff, and flags who's at risk of canceling. An AI follow-up digs into the specific moment or friction point behind low renewal intent, giving retention teams a reason to act on instead of just a number.

Measures how customers experience estimate transparency, timeliness, and work quality at your service department or repair shop, and how those add up to trust. An AI follow-up digs into the specific moment — often around cost or communication — where trust was won or lost.

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.

A repeatable diary entry participants complete each time they use your product in real life: a photo of the moment, what they were trying to do, and what got in the way — with an AI probe on the day's friction. Run it daily or weekly to see usage where it actually happens, not in a lab.

Find your biggest opportunities by measuring the same attributes twice — how much each matters, and how well you deliver it today. The gaps become your priority list, and slider matrices keep it fast enough that people actually finish. AI follow-ups dig into the biggest gap each respondent reports.

Measures customer perceptions of fairness, transparency, and wait-time accuracy across virtual and in-person restaurant and hospitality waitlists. Ideal for hospitality operators and CX researchers seeking actionable insights on queue management.

Evaluates customer satisfaction, resolution effectiveness, response time perceptions, and channel preferences for two-way SMS support interactions, providing actionable insights to optimize text-based service delivery.

Measures event attendees' perceptions of clarity, fairness, and friction in digital ticket transfer and resale processes to identify platform improvement priorities.

Measures customer satisfaction, resolution effectiveness, agent performance, and customer effort after a support interaction to identify actionable service improvements.

Measures the usability of the subscription cancellation process, perceived fairness of retention offers, and key churn drivers. Designed for current or recently canceled subscribers to inform win-back strategy and CX improvements.

Measures user satisfaction with content discovery, recommendation relevance, personalization, and playback quality across streaming platforms to identify UX improvement priorities.

Measures customer perceptions of ETA clarity, status update frequency, and service commitment communication following a recent service interaction. Use to identify communication gaps that drive escalations and erode trust.

Measures customer satisfaction with delivery speed, order communication, and returns/refund processes. Designed for ecommerce teams seeking actionable CX insights to reduce friction and increase repurchase intent.

Measures customer satisfaction, perceived fairness, and friction points across the retail return and refund process to inform policy improvements and reduce post-purchase churn.

Identifies churn signals, switching intent, and high-impact retention levers among at-risk B2B accounts to inform targeted save strategies and renewal planning.

Measures how clearly customers understand promotional offers, how well incentives match their preferences, and their likelihood of referring others — identifying friction points to improve referral rates and conversions.

A recurring pulse survey for active SaaS product users that measures satisfaction, captures bugs, and prioritizes feature improvements over a rolling 14-day window.

Measures customer effort, satisfaction, and loyalty immediately after a support interaction. Designed for CX teams seeking actionable CSAT, CES, and NPS benchmarks in under 3 minutes.

Measures customer satisfaction across the full post-purchase journey — checkout, shipping, delivery, and product quality — to identify friction points and drive retention improvements.

Measures Net Promoter Score and identifies key drivers of recommendation among recent customers, providing actionable insights to improve retention, referrals, and overall customer experience.

Measures customer experience across product clarity, task speed, and documentation usability to identify friction points and prioritize improvements for product and CX teams.

Measures member satisfaction, benefit relevance, redemption experience, and tier engagement for retail loyalty programs. Designed for enrolled or lapsed members to identify drivers of retention and program optimization opportunities.

Measures loyalty program members' satisfaction with reward relevance, redemption ease, and perceived value relative to competitors to identify retention drivers and improvement priorities.

Captures end-user evaluations of translated content across fluency, cultural fit, intent accuracy, and tone. Designed for LQA teams seeking structured feedback to prioritize localization improvements.

Measures translation quality, tonal appropriateness, and terminology consistency for multilingual digital products. Designed for product and localization teams seeking diagnostic feedback to improve global user experience.

Measures customer preferences, satisfaction, and response-time expectations across live chat and asynchronous messaging channels to guide support channel investment and design decisions.

Measures article findability, clarity, completeness, and task-completion outcomes for knowledge base users. Use to identify content gaps and prioritize help center improvements.

Measures policyholder satisfaction across the full claims journey — from submission through resolution — using CSAT and NPS metrics to pinpoint friction points and improvement opportunities.

Evaluates customer perceptions of service uptime, availability confidence, pricing clarity, and security trust. Designed for product and CX teams seeking actionable diagnostics on reliability and transparency pain points.

Measures guest satisfaction across food quality, service, ambiance, and value while capturing Net Promoter Score. Designed for restaurant operators seeking to identify loyalty drivers and prioritize operational improvements.

Measures end-to-end delivery experience from order placement through last-mile handoff, capturing satisfaction, communication quality, issue incidence, and NPS for e-commerce and logistics teams.

Measures overall satisfaction, Net Promoter Score, and key experience drivers across the end-to-end shopping journey. Designed for retail and ecommerce teams seeking actionable insights on product, delivery, checkout, and support touchpoints.

Measures ease, satisfaction, and pain points across each stage of the customer and prospect journey. Designed for CX researchers seeking to identify drop-off risks, high-impact touchpoints, and conversion barriers.

Measures perceived effort across each stage of the online checkout journey using the standard CES framework. Designed for ecommerce teams seeking to identify specific friction points, prioritize UX improvements, and track effort reduction over time.

Collects structured feedback from Customer Advisory Board members on strategic alignment, meeting cadence, format preferences, and perceived value to drive board engagement and planning decisions.

Diagnoses cancellation intent, surfaces the primary drivers of churn, and identifies which retention offers resonate most with at-risk financial product users. Designed for product, CX, and retention teams seeking actionable save-desk insights.

Identifies at-risk B2B customers through usage patterns, perceived value, and churn intent, then surfaces the retention levers most likely to prevent cancellation. Designed for product, CS, and growth teams managing subscription-based accounts.

Captures structured cancellation feedback from recently churned customers to identify primary churn drivers, unmet value expectations, and win-back levers for product and retention teams.

Diagnoses specific checkout drop-off points across payment processing, address entry, and form validation to identify the highest-impact fixes for reducing cart abandonment.

Measures perceived fairness, transparency, and trust impact when customers encounter a chatbot before reaching a human agent. Designed for post-interaction feedback to diagnose friction in chatbot routing and escalation workflows.

Evaluates customer experience across three core digital banking touchpoints—sign-in, money movement, and notifications—to surface usability pain points, feature demand, and alert-preference data for product teams.

Evaluates customer satisfaction and friction points during chatbot-to-human-agent transfers, measuring ease of transition, context retention, agent effectiveness, and reuse intent to guide support escalation optimization.