Employee & HR survey templates

Measures how pet owners experience the front desk, technicians, and veterinarians during a visit — friendliness, communication, competence, and wait times — with an AI follow-up that reconstructs the specific interaction behind a client's rating. Built for veterinary practice managers who want actionable staff feedback, not just star ratings.

Measures how employees experience or witness racism and racial bias at work, how safe they feel raising concerns, and whether leadership follows through on accountability. An AI follow-up interview probes the real story behind low safety ratings or unreported incidents, surfacing details a scale score alone can't capture.

Captures how candidates actually experience your online hiring process — from finding the posting to receiving a decision — including friction points, communication gaps, and employer brand impact. An AI follow-up interview reconstructs the specific moment that shaped their impression, not just a generic rating.

Measures how employees use, value, and understand their benefits package — including a trade-off exercise to prioritize future investment and a budget-allocation question. Built for HR and Total Rewards teams; the AI follow-up interview digs into the specific moment a benefit helped or let someone down, surfacing detail no rating scale can capture.

Measures frontline retail engagement — scheduling fairness, manager support, recognition, staffing, and advancement — plus an employee-recommend score to benchmark culture health. An AI follow-up interview digs into the real story behind low scores and turnover risk, surfacing specifics closed questions miss. Built for retail HR and store operations leaders.

A CNBC|SurveyMonkey-style workforce pulse that tracks how happy, secure, and engaged employees feel right now — covering pay fairness, workload, leadership trust, and flight risk. An AI follow-up interview digs into the story behind low happiness or job-security scores so HR and leadership see the real drivers, not just the number.

Measures how employees actually feel about the branded merchandise they receive — quality, frequency of use, and which items feel worth keeping — plus a best-worst trade-off to prioritize future swag spend. An AI follow-up interview digs into the story behind their most memorable item to surface what actually makes swag feel meaningful versus wasted.

Measures how included, fairly treated, and heard employees feel across backgrounds, and prioritizes where DEI investment would have the most impact. An AI follow-up interview digs into specific belonging or fairness experiences behind the scores instead of leaving them as abstract ratings.

Tracks how employees experience the process of raising issues with HR — from reporting channel and response speed to fairness, confidentiality, and final resolution. Built for HR and People Ops teams auditing their issue-handling process, with an AI follow-up interview that reconstructs exactly what happened in a specific case instead of relying on averaged satisfaction scores.

Tracks how happy employees are right now, what's driving or dragging that happiness, and how it connects to retention risk. An AI follow-up interview digs into the story behind each person's happiness rating instead of settling for a number, giving HR teams concrete detail to act on.

Measures whether recent training actually changed what employees can do on the job — covering content quality, format preferences, and topic priorities — with an AI follow-up that digs into the real reasons behind low preparedness scores instead of settling for a number.

Tracks overall staff satisfaction, satisfaction across key workplace dimensions, and early flight-risk signals, then uses an AI follow-up interview to uncover the specific reasons behind low scores or turnover intent. Built for HR and people teams running quarterly or annual pulse checks.

A supervisor-facing evaluation of a call center agent's call quality, adherence, and soft skills, paired with a best-worst training-priority ranking and an AI follow-up interview that reconstructs a specific recent call to explain the reasoning behind the ratings. Built for team leads and quality analysts running periodic performance reviews.

Captures how effectively new employees are onboarded onto your company's core software tools in their first weeks — covering training quality, self-sufficiency, and time-to-productivity — with an AI follow-up that digs into the specific moment onboarding broke down. Built for HR and IT/People Ops teams refining new-hire tech ramp-up.

Measures how employees feel about their role, manager, and the organization overall — covering recognition, motivation, and intent to stay — with an AI follow-up that digs into the real story behind low or high scores instead of settling for a number. Built for HR teams running regular engagement pulses.

A structured self-assessment for performance review cycles, combining competency self-ratings, goal progress, and development priorities with an AI follow-up that draws out the specific evidence behind an employee's accomplishments and challenges. Built for HR teams and managers running annual or quarterly review processes.

Captures how interns experienced onboarding, mentorship, meaningful work, and team culture, then has them trade off which parts of the program mattered most. An AI follow-up interview digs into the real story behind their overall rating. Built for HR and program leads assessing internship ROI and full-time conversion potential.

Measures how included, respected, and fairly treated employees feel day-to-day — covering belonging, fairness in advancement, exposure to exclusionary behavior, and which DEI investments matter most. An AI follow-up interview turns the lowest-scoring signals into concrete, specific stories HR can act on. For HR and DEI teams running an annual or pulse climate check, about 8 minutes.

Captures a well-rounded nomination for an employee recognition award, combining structured ratings against your award criteria with an AI follow-up that pulls out the concrete story behind the nomination. Built for HR teams and award committees running quarterly or annual recognition programs who need comparable, story-rich nominations instead of vague praise.

Gathers confidential feedback from employees who recently went through a disciplinary action, measuring how clearly the reason was explained, how fair and consistent the process felt, and trust in the manager or HR handling it. An AI follow-up interview reconstructs what actually happened in the meeting rather than just the rating given. For HR and People teams auditing process quality and consistency.

Captures how an employee experienced a formal write-up or written warning — clarity of the issue, perceived fairness, and what support would help them improve. Built for HR teams and people managers auditing disciplinary conversations, with an AI follow-up interview that surfaces exactly what the employee understood, agreed with, or found unclear.

A confidential intake form for employees to document a workplace complaint or concern, capturing what happened, who's involved, severity, and desired resolution. An AI follow-up interview gently reconstructs the specific timeline and details so HR gets an actionable, well-documented account instead of a vague summary.

Gathers structured multi-rater feedback—from managers, peers, direct reports, and self—on an employee's core competencies and overall effectiveness. An AI follow-up interview digs into the concrete behavioral examples behind the ratings, turning vague impressions into specific, actionable evidence for development conversations.

Measures how smoothly new clients moved from signed contract to real value — covering communication, clarity of next steps, and time-to-value — with an AI follow-up that reconstructs exactly where friction happened instead of relying on a single satisfaction number.

Measures how safe employees feel day-to-day, how strong your safety culture and reporting habits actually are, and what stops people from speaking up — with an AI follow-up that reconstructs a real near-miss or incident and what would change how it's handled next time.

Captures how direct reports experience their manager's communication, feedback, recognition, and support — with a rating battery, a prioritization exercise on where to improve, and an AI follow-up that digs into the specific moment behind their satisfaction score. Built for HR teams and leaders running 360 or upward-feedback cycles.

Tracks how employees feel about their manager, workload, growth, and the organization overall, then uses an AI follow-up interview to surface the specific reasons behind low or lukewarm scores. Built for HR and people teams running quarterly or annual pulse checks who need both trend data and the 'why' behind it.

Tracks how employees are really doing — stress frequency, burnout symptoms, and which wellness benefits actually get used versus ignored — then uses a trade-off exercise and AI follow-up interview to uncover the specific causes of stress and the barriers stopping people from using support that already exists. Built for HR and People teams running quarterly wellbeing check-ins.

Measures overall job satisfaction, the specific drivers behind it (workload, manager support, growth, recognition, pay, work-life balance), and retention risk — with an AI follow-up interview that digs into the real reason behind each employee's satisfaction score instead of just the number. Built for HR teams running quarterly or annual pulse checks.

Measures how employees are experiencing the shift back to in-person work — attendance patterns, productivity and wellbeing impact, and retention risk — with an AI follow-up that digs into the specific friction points behind low satisfaction or flight-risk scores instead of generic complaints.

Measures how satisfied employees are with the physical conditions of their workspace — noise, lighting, temperature, ergonomics, and cleanliness — and which upgrades would matter most. An AI follow-up digs into the specific incident behind each person's lowest-rated factor so facilities teams get real stories, not just scores.

Captures how a new employee's first 30 days actually went — role clarity, manager support, tools access, and team integration — with an AI follow-up interview that digs into the specific moment onboarding fell short. Built for HR and people teams who want to fix onboarding before new hires disengage or leave.

Measures how aware, interested, and price-sensitive employees are toward employer-sponsored coverage of GLP-1 medications (e.g., Ozempic, Wegovy, Mounjaro). Built for HR and benefits teams weighing whether to add this coverage. The AI follow-up interview digs into the personal reasoning behind interest or hesitation — health goals, cost thresholds, and stigma — that closed questions can't capture.

A quick pulse for teams navigating AI-driven change — measuring sentiment, trust in leadership communication, skill-confidence, and the support employees actually want next. An AI follow-up interview digs into the real story behind each person's sentiment score, surfacing specifics a scale alone can't capture.

Measures how middle managers are experiencing AI-driven reductions in management layers — perceived job security, shifting responsibilities, and confidence in a flatter structure — for HR and leadership teams navigating restructuring. An AI follow-up interview digs into the specific incident behind each manager's top anxiety, separating genuine risk from vague unease.

Measures how confident employees feel using frontier AI tools like ChatGPT and Copilot across core workplace skills, where the biggest gaps sit, and what's blocking adoption. An AI follow-up interview digs into the real story behind each person's lowest-confidence skill area, not just the number they picked. Built for HR and L&D teams planning AI training.

Measures how comfortable employees are handing off specific work to AI agents, what's currently delegated, how closely output gets checked, and what would build more trust. Built for HR and AI-adoption teams rolling out agentic tools, with an AI follow-up interview that digs into the real reasons behind hesitation or over-reliance rather than generic attitude scores.

Measures how predictable, swappable, and fair hourly employees find their work schedules, plus early burnout signals like clopening shifts and exhaustion. Includes an AI follow-up that reconstructs a specific recent scheduling incident — a denied swap or a last-minute change — instead of relying on general impressions.

Measures the gap between the values a company says it holds and the values employees actually experience in day-to-day decisions, priorities, and leadership behavior. Built for HR and leadership teams auditing culture health, with an AI follow-up that reconstructs a real recent moment where a decision either honored or contradicted a stated value.

Measures whether reps understand how they're paid, whether quotas feel attainable, and how the comp plan shapes day-to-day selling behavior — built for sales leadership and RevOps. An AI follow-up reconstructs the specific moment a rep's trust in the plan was tested, going deeper than a top-line fairness score.

Measures whether sales training actually changes behavior in live deals — skill application frequency, content relevance to real customer situations, and rep confidence in reaching full ramp — with an AI follow-up that reconstructs a specific deal instead of relying on self-rated satisfaction with the training.

Measures where employees feel skill gaps, which learning formats and time investments actually work for them, and how their career goals should shape the L&D roadmap. Built for HR and L&D teams planning training budgets and programs. An AI follow-up digs into the specific skill gap and career goal each person names to surface concrete blockers, not just checkbox preferences.

Captures how candidates experienced your application process, interview fairness, and communication speed — collected from hired and rejected candidates alike — and how that experience shaped their view of your employer brand. An AI follow-up reconstructs the specific moment that most shaped their overall impression, whether a confusing application step, an unprepared interviewer, or silence after a final round.

Captures what drew a new hire to accept the offer, how the first weeks stack up against what was promised, and what would keep them long-term. Built for HR and people teams running structured 30/60/90-day check-ins, with an AI follow-up that digs into the specific moment expectations and reality diverged.

An upward-feedback survey where direct reports rate their manager on coaching, clarity of direction, fairness, and day-to-day support, plus behavioral questions about 1:1s and feedback frequency. An AI follow-up digs into a specific recent example behind the lowest-rated area so managers get concrete, actionable coaching notes instead of just a score.

Measures how often employees are recognized, how fair and meaningful that recognition feels, and whether it comes more from managers or peers. An AI follow-up digs into a specific recent recognition moment to surface what actually made it land — or fall flat — beyond the survey ratings.

Diagnoses what fuels and what erodes employee motivation across autonomy, mastery, purpose, recognition, and rewards, then uses an AI follow-up to uncover the specific moment motivation dropped and what would restore it.

Before a reorg, tooling migration, or new process lands, measure whether people understand it, believe in it, and feel equipped for it — the three things that decide adoption. The AI interviewer surfaces the concerns people won't put in a comment box, anonymously.

A voice AI exit interview departing employees can take privately, on their own time. The interviewer covers reasons for leaving, manager and culture experience, and what would have changed their mind — probing gently where a form gets one-word answers. Structured questions capture the benchmarkable basics.

Measures employee comfort with workplace monitoring practices, evaluates policy transparency, and identifies trust gaps to guide privacy, consent, and communication improvements.