Pool Maintenance Service Customer Feedback Survey

Professional Pool Maintenance Feedback That Drives Service Excellence

Running a pool maintenance business means juggling chemical deliveries, equipment repairs, seasonal schedules and customer expectations—all while keeping dozens of pools crystal clear. When feedback comes through scattered texts, phone calls, or never at all, it's nearly impossible to know what's working and what needs attention.

This Pool Maintenance Service Customer Feedback Survey template gives pool service companies a professional, mobile-friendly way to collect structured feedback after every service visit, seasonal opening/closing, or equipment repair. Instead of guessing which technicians are building trust and which routes need coaching, you'll get clear ratings on water quality results, equipment repair satisfaction, chemical balance accuracy, technician reliability, and pricing transparency.

Built for pool service workflows

Paperform makes it easy to embed this survey in follow-up emails, text it after appointments, or share it via QR code on invoices. Conditional logic shows different questions based on service type—so customers who only had a chemical check aren't asked about equipment repairs. You can track satisfaction trends by technician, route, or season, and use AI Insights to automatically summarize open-ended feedback into themes like "customers love the reliability but want better communication about chemical adjustments."

Turn feedback into faster action with Stepper

Once a survey is submitted, Stepper can route low ratings to your service manager in Slack, add follow-up tasks to your CRM or project tool, and flag recurring issues by technician or service type—all with no code. That means you can close the loop faster, coach your team with real data, and turn satisfied customers into referrals.

Trusted by pool maintenance companies, landscaping services, and home service providers, this template helps you deliver the dependable, high-quality service your customers expect—and prove it with data.