200 tickets in the Monday-morning jam — today it’s 12.
The support inbox filled up over the weekend with standard requests — shipping, returns, invoice PDFs. Monday morning the team faced 200+ open tickets. Today the agent resolves 94% of them before the team comes online.
- Year
- 2026
- Industry
- E-commerce · DACH
- Stack
- LangChain · RAG · Zendesk
- Duration
- 4 weeks
- Status
- Live · production
The client — a German e-commerce mid-sized company — had ~280 tickets/workday. 78% were Tier-1 standard requests (shipping status, return, invoice re-issue). The support team spent 65% of its time on questions whose answer was in the FAQ — which customers didn’t read.
- 280 tickets/workday · 78% Tier-1 · 22% complex
- 65% support time on FAQ answers (shipping · returns · invoices)
- 14 min avg handling time Tier-1 → 28 h/day staff effort
- CSAT 3.4 / 5 — because complex tickets waited too long
Support Agent · ticket resolution
Ø Zeit-Ersparnis
Avg. 13.8 min saved per Tier-1 ticket
Sechs harte Zahlen. Aus den Live-Dashboards des Kunden, gemessen über die ersten Monate nach Go-Live. Kein Marketing-Number-Massaging — Roh-Output aus dem Agent-Log.
Tier-1 resolved autonomously
of 78% of all tickets
avg. Tier-1 response time
was 14 min
CSAT
was 3.4
support time saved
available for complex tickets
Monday-morning hotline jam
first in 3 years
avg. savings
secured staff costs
My team had a 200-ticket backlog every Monday morning. Today the dashboard shows 12 tickets in the queue — all Tier-2, because the agent already handled the rest. My team isn’t just more relaxed — our CSAT is high too.