Detect
A low rating or a chosen keyword lands on any channel — a negative Smile (SLI) tap, a 1–2★ star rating, an NPS score of 0–6, or a comment containing a word like “refund”. Every channel feeds the same pipeline.
Feature — Closed-loop ticketing
Closed-loop ticketing software for customer feedback
Closed-loop ticketing turns negative customer feedback into a tracked ticket, routes it to the person who can fix it, and follows up with the customer after resolution — so every complaint ends with an answer, not a shrug. Qmeter automates the whole loop: detection, assignment, SLA timers, escalation and a post-resolution CSAT survey.
Surveys tell you something went wrong. The ticketing loop makes sure someone fixes it — and proves the customer left satisfied. This is Qmeter’s flagship module.
1000+companies use Qmeter
2M+feedbacks collected
15+years in customer experience
Detect→Ticket→Route→Resolve→Follow up
The loop
From bad rating to recovered customer, in five steps
Collecting feedback is the easy half. The loop is what happens in the minutes after a customer taps the angry face.
Feedback arrives from every channel — kiosks, QR codes, SMS, email, web and app — and each negative response follows the same path. Here is the closed-loop feedback process, exactly as Qmeter runs it.
Ticket
Your generation rules are evaluated in order and the first active match fires: a ticket opens instantly with the rule’s default priority. Nobody has to spot the complaint in tomorrow’s report.
Route
The rule assigns from its agent pool — round-robin, first-available or random — and is scoped by branch and service, so a Riverside branch issue never lands with the airport team.
Resolve
The agent works a real lifecycle with SLA timers running. Closing requires a root cause and an action taken — “fixed” without a why does not count, and every change is audit-logged.
Follow up
A post-resolution CSAT survey goes to the customer and their answer becomes your recovery rate. If they reply unhappy, the ticket reopens. That follow-up is what closes the loop.
The ticket lifecycle: new → in progress ⇄ pending customer → escalated → resolved → reopened. Transitions are enforced server-side and every change writes an audit event.
Auto-generation rules
Tickets open themselves — rules decide in real time
No one scans a dashboard for complaints. You define the rules once; the first active match fires on every incoming feedback.
Triggers that match how you rate
Rating buckets per capture type — Smile (SLI) Negative / Neutral / Positive, Star 1–2★ / 3★ / 4–5★, NPS Detractor (0–6) / Passive (7–8) / Promoter (9–10) — plus keyword triggers on the comment text.
Conditions and scope
Fire on every match, or only when a comment and/or a contact detail is present. Scope each rule to specific branches and services — leave it empty and it covers everything.
Assignment strategy
Each rule owns an assignee pool and a strategy: round-robin, first-available or random. The ticket lands with a named owner the second it is created — plus a default priority (low, medium or high) that drives its SLA clock.
The Google reviews bridge
Reviews of three stars or fewer on your Google profile open tickets through the same pipeline — see Google Reviews management. One queue for every unhappy customer, wherever they spoke up.
Built for accountability
What keeps the loop honest
Five mechanisms — each one exists so a complaint cannot quietly die in a queue.
SLA timers that respect priority
You set two targets in hours — first response and resolution — and priority scales them with a fixed multiplier: high ×0.5, medium ×1, low ×2. An 8-hour resolution target means 4 hours for a high-priority ticket and 16 for a low one.
- Separate first-response and resolution timers per ticket
- SLA bar: green → amber at 80% elapsed → red on breach
- Escalated tickets always render a red bar
- Breach flags flip only while the ticket is still open
Escalation that names names
Every rule carries a numbered escalation chain. Each level lists specific users and how they are notified — email or Slack. When a ticket sits past the escalation step (scaled by the same priority multiplier), it advances a level, reassigns up the chain and notifies — automatically.
- Ordered levels: 1, 2, 3… — no vague “notify a manager”
- Email and Slack notifications per level
- Escalation badge (L1, L2…) visible on the ticket board
Resolving requires a why — and the why becomes analytics
A ticket cannot be resolved without a root cause and an action taken, both picked from taxonomies you manage. Those two fields turn closed tickets into operational data: top root causes by branch, most-used actions, reopen rates.
- Pivot report builder: drag dimensions into rows and columns
- Measures like resolution rate, average resolution time, CSAT %
- Save reports, share with teammates, export CSV / XLSX / PDF
Reply from the ticket — the customer just answers an email
Public replies go out over your own SMTP; customer answers come back through IMAP and thread into the right ticket as a customer comment. No portal, no login, no “please quote your reference number”.
- A reply on a resolved ticket reopens it automatically
- A reply while pending-customer flips it back to in progress
- Internal notes stay internal — only public replies are sent
The loop closes with a question, not an assumption
After resolution, the customer gets a short CSAT survey about how the issue was handled. The answers become your recovery rate — a number most feedback tools never measure, because they stop at collection. Unsure which metric fits where? See NPS vs CSAT vs CES.
- Post-resolution CSAT per ticket, trended over time
- Recovery rate by branch, agent and root cause
- Unhappy answer? The conversation is one reply away from reopening
AI on every ticket
AI reads every ticket first
Before an agent opens a ticket, AI has already classified it. Insights regenerate on demand — and AI sees ticket content only, never raw customer PII.
Sentiment & urgency
Every ticket is classified — positive, neutral, negative or angry — with a low / medium / high urgency call and an SLA-at-risk flag, so agents open the right ticket first.
Churn risk & theme tags
An estimated churn-risk percentage and AI theme tags sit on the ticket itself. Sort the queue by who you are most likely to lose, not by arrival order.
Suggested reply
AI drafts the public reply from the ticket’s content; the agent edits and sends. Drafts land in the composer — a human always makes the final call.
Summary & similar tickets
A short summary, a suggested action and clickable similar cases give an agent the context of previous fixes before they type a word.
The ROI
What closing the loop returns
No invented percentages — two independent findings, one piece of product mechanics, and our public price list. You supply the last variable: what one retained customer is worth to you.
Collecting feedback is the easy half; acting on it is where retention is won. The ticketing loop is the acting half — every recovered customer is churn you did not pay to replace with an acquisition campaign.
collect → act → keepFeedback gets ignored when it lands in a shared inbox nobody owns. Auto-generated tickets make ignoring structurally impossible: every negative response gets a named owner and a running SLA clock from the moment it arrives.
by designManual triage steps between a complaint and its owner. Rules assign every ticket the moment it is created — round-robin, first-available or random — so the hours teams typically spend forwarding complaints go into resolving them instead.
How auto-routing worksThe other side of the equation is public: Web Feedback from €500/year, Device License from €50/device/month. Set one recovered customer a month against that and the maths rarely needs a consultant — see transparent pricing.
FAQ
Closed-loop ticketing, answered
Short, honest answers with the real formulas. For anything else, talk to our team.
What is closed-loop ticketing?
Closed-loop ticketing is the practice of turning negative customer feedback into a tracked support ticket, resolving it, and then going back to the customer to confirm the fix actually worked. In Qmeter the loop is automated end to end: a low rating opens a ticket, rules route it to the right person, SLA timers keep it moving, resolving requires a root cause and an action taken, and a post-resolution CSAT survey measures whether the customer was recovered. Read the methodology in our closed-loop feedback guide.
How do SLA timers work in Qmeter?
How are tickets created from feedback automatically?
What happens if nobody resolves a ticket in time?
Can customers reply to ticket emails?
How do I know a complaint was genuinely fixed, not just closed?
Keep exploring
Where the ticketing loop fits your operation
Closed-loop feedback guide
The methodology behind this module — why closing the loop beats collecting more surveys.
→Google Reviews management
Reply to Google reviews with AI drafts — and let low-star reviews open tickets automatically.
→Qmeter for retail
Store-level feedback with kiosks and QR — and tickets routed to the right store manager.
→Qmeter for hospitality
Fix a guest’s stay while they are still in the building, not after the review goes public.
→Qmeter for banks
Branch feedback, complaint tickets and SLA discipline for multi-branch financial teams.
→Transparent pricing
Web Feedback from €500/year, Device License from €50/device/month. Public, no sales call needed.
→Get started
Close the loop on your next negative feedback
Start a 14-day free trial — no credit card. AI builds your first survey from your company profile, and your first ticket rule takes minutes to set up.
