Measuring Satisfaction: Turning Reputation into Managed Data
Two Myths
Myth one: “no complaints means satisfied” — silent clients simply vote with their feet at renewal. Myth two: “screenshots of praise equal satisfaction” — platform data carries heavy selection bias. Satisfaction needs active, structured measurement.
Design
- Timing: mid-course (correctable), at completion, and 30 days after (retention truth).
- Minimal scale: two questions — overall satisfaction 0-10, and “would you recommend us” 0-10 (NPS style).
- One open question: “the one thing to improve” — a gold mine.
- Channels: in-store tablet or messenger/survey follow-up; avoid face-to-face praise-soliciting pressure.
Three Uses of the Data
- Early warning: scores ≤6 get a manager callback within 24 h — the best interception window.
- Review: aggregate by operator and program; outliers trigger investigation (training? settings? expectations?).
- Closed loop: open answers summarized biweekly; publish the top three fixes — “you said, we changed”.
Compliance Note
Paid or incentivized praise violates most platform rules and carries advertising risk; the right posture is service worth praising plus interception before complaints go public.
FAQ
What NPS is healthy?
Reference ranges vary; trend and same-store comparison matter more than absolutes. A steady decline is more dangerous than a low score.
Are follow-ups intrusive?
Two touches, ten seconds each, are widely accepted — design the follow-up as service (care-node reminders) and it reads as professionalism, not pestering.