Customer feedback loop and NPS tracking
Collect, categorize, and act on customer feedback at scale.
Many teams collect customer feedback but never act on it — surveys and reviews pile up, nobody's accountable for response, and customers feel ignored. This template maps the complete feedback loop: send a survey, classify responses by sentiment (NPS), tag customers by churn risk, and route to the right team (product, support, leadership) for follow-up. Closing the loop — telling a customer "we heard you, here's what we did" — turns feedback into loyalty.
The state diagram captures the three outcomes: promoters become advocates and referral sources; passives are at risk and need engagement; detractors are churn risk and need immediate attention. Each state has a clear next action.
When to use this template
- Feedback program design — before launching surveys or collecting reviews, walk the team through how you'll respond. A feedback loop without action is just noise collection.
- Churn investigation — map the cohorts (promoters, detractors) and ask: Which features or experiences push customers toward churn? What do promoters have in common? Use this diagram to guide the analysis.
- Customer success process — use NPS and feedback tags to segment customers for proactive outreach: call promoters to encourage referrals, check in with passives, and escalate detractors to leadership.
How to adapt it
Customize the categorization and routing to your team:
- Add open-ended categorization — after "Collect feedback", branch: "Bug or feature request?" Route bugs to engineering, feature requests to product backlog, complaints to support.
- Extend the action step — instead of generic "Route to product/support", add specific paths: "Critical bug?" → immediate triage; "Roadmap feedback?" → quarterly review; "Compliment?" → thank-you email with special offer.
- Add impact tracking — after "Close the loop", measure: "Did we fix the issue?" Customers whose problems were addressed have lower churn and higher loyalty than those who got no action.
Visual edits regenerate clean Mermaid code so you can build your feedback loop without syntax overhead.
Mermaid code
Copy it anywhere Mermaid is supported — GitHub, Notion, or your docs.
stateDiagram-v2
[*] --> Feedback_Sent: Customer submits feedback
Feedback_Sent --> Categorize: Auto-classify by topic
Categorize --> NPS_Survey: Send NPS question
NPS_Survey --> Promoter: Score 9-10
NPS_Survey --> Passive: Score 7-8
NPS_Survey --> Detractor: Score 0-6
Promoter --> Store: Tag as "advocate"
Passive --> Store: Tag as "at-risk"
Detractor --> Store: Tag as "churn-risk"
Store --> Analyze: Aggregate by feature/cohort
Analyze --> Action: Route to product/support
Action --> Close_Loop: Send follow-up
Close_Loop --> [*]
Frequently asked questions
- What is a customer feedback loop?
- It's the cycle from collecting customer feedback (surveys, reviews, support tickets) through analysis and action back to closing the loop with the customer. Without a documented loop, feedback sits in silos and nobody acts on it. A visible loop ensures feedback drives product decisions.
- Why track NPS instead of just collecting feedback?
- NPS (Net Promoter Score) is a single number that measures loyalty: promoters (9-10) are likely to recommend, passives (7-8) are satisfied but not loyal, detractors (0-6) are at churn risk. Tracking it over time shows whether your product is improving or declining. Raw feedback is valuable for details, but NPS is the leading indicator.
- How do I close the loop without overwhelming the team?
- Prioritize: high-volume feedback topics and detractors go to product; bugs go to engineering; experience issues go to support. Route using the category from step 2, and automate where possible — send template follow-ups to promoters, escalate detractors to a manager. Visual edits regenerate clean code.
- What metrics should I track for the feedback loop?
- NPS trend (month-over-month), average response time from feedback to action, percentage of feedback actioned, and churn rate by cohort (promoters vs. detractors). These metrics show whether your loop is fast, complete, and making a difference.