Support Operations Strategic support operations expertise for customer-facing teams — from ticket management and SLA design to escalation workflows and self-service optimization. Philosophy Great support isn't about closing tickets fast. It's about solving customer problems permanently while building scalable systems. The best support operations teams: Prevent before they support — Self-service and proactive help reduce ticket volume Measure what drives loyalty — Resolution quality beats response speed Escalate with context — Every handoff preserves customer history Feed insights upstream — Support data drives product and success improvements How This Skill Works When invoked, apply the guidelines in rules/ organized by: ticket- — Ticket management, prioritization, queue optimization sla- — SLA design, compliance monitoring, escalation triggers tier- — Support tier structure, skill-based routing, specialization knowledge- — Knowledge base strategy, self-service, deflection metrics- — CSAT, FRT, TTR, FCR, quality scoring escalation- — Severity definitions, escalation paths, incident management tooling- — Support stack optimization, integrations, automation feedback- — Support-to-CS handoffs, product feedback loops, voice of customer Core Frameworks The Support Operations Hierarchy Level Focus Metrics Owner Tickets Individual resolution Handle time, CSAT Agents Queue Flow optimization Wait time, backlog Team leads Channel Channel effectiveness Deflection, containment Managers Operations System performance Cost per ticket, NPS Directors Strategy Business impact Retention, expansion VP/C-level The Support Tier Model ┌─────────────────────────────────────────────────────────────────┐ │ TIER 3 (L3) │ │ Engineering escalation, code-level issues, custom development │ │ Target: <5% of tickets | SLA: Best effort │ ├─────────────────────────────────────────────────────────────────┤ │ TIER 2 (L2) │ │ Technical specialists, complex troubleshooting, integrations │ │ Target: 15-25% of tickets | SLA: 4-8 hours │ ├─────────────────────────────────────────────────────────────────┤ │ TIER 1 (L1) │ │ First response, common issues, documentation guidance │ │ Target: 60-80% resolution | SLA: 15-60 minutes │ ├─────────────────────────────────────────────────────────────────┤ │ SELF-SERVICE (L0) │ │ Knowledge base, chatbots, community forums, in-app help │ │ Target: 30-50% deflection | SLA: Instant │ └─────────────────────────────────────────────────────────────────┘ Ticket Priority Matrix Priority Business Impact Response SLA Resolution SLA Examples P1 Critical Complete outage, data loss 15 min 4 hours System down, security breach P2 High Major feature broken 1 hour 8 hours Key workflow blocked P3 Medium Feature impaired 4 hours 24 hours Partial functionality P4 Low Minor issue, cosmetic 8 hours 72 hours UI bug, minor inconvenience P5 Request Feature request, how-to 24 hours 5 days Enhancement, training Support Metrics Framework Metric Definition Target Warning CSAT Customer satisfaction score 90%+ <85% FRT First response time <1 hour
4 hours TTR Time to resolution <24 hours 72 hours FCR First contact resolution 70%+ <50% NPS Net promoter score 30+ <10 Ticket Volume Tickets per 100 customers 5-15 25 Deflection Rate Self-service success 30-50% <20% Escalation Rate Tickets escalated 10-20% 30% Reopen Rate Tickets reopened <5% 10% Agent Utilization Productive time 70-80% <60% or >90% The Ticket Lifecycle ┌─────────────────────────────────────────────────────────────────┐ │ │ │ NEW → TRIAGED → ASSIGNED → IN PROGRESS → PENDING → RESOLVED │ │ │ │ │ │ ▼ ▼ │ │ ESCALATED WAITING │ │ │ (Customer) │ │ ▼ │ │ ENGINEERING │ │ │ └─────────────────────────────────────────────────────────────────┘ Channel Strategy Matrix Channel Best For Cost Scalability Personal Self-service Common issues Lowest Highest Lowest Chatbot Quick questions Low High Low Live chat Real-time help Medium Medium Medium Email/Ticket Complex issues Medium Medium Medium Phone Urgent/sensitive High Low High Video Technical demos High Low Highest Severity Levels Severity Definition Escalation Path Communication SEV1 System-wide outage Immediate to engineering + exec Status page, proactive email SEV2 Major feature broken 1 hour to L3 Affected users notified SEV3 Feature degraded 4 hours to L2 Standard ticket updates SEV4 Minor impact Normal queue Standard ticket updates Key Formulas Cost Per Ticket Cost Per Ticket = (Total Support Cost) / (Total Tickets Handled) Target: $5-25 depending on complexity Support Capacity Planning Required Agents = (Ticket Volume × Handle Time) / (Available Hours × Utilization Rate) Example: (500 tickets × 20 min) / (8 hours × 60 min × 0.75) = 28 agents Self-Service ROI Savings = (Deflected Tickets × Cost Per Ticket) - Self-Service Investment Anti-Patterns Speed over quality — Fast wrong answers create repeat contacts Ticket tennis — Multiple handoffs without resolution Knowledge hoarding — Solutions in heads, not documentation Metric gaming — Closing tickets prematurely to hit targets Escalation avoidance — L1 struggling when L2 is needed Channel forcing — Making customers switch channels unnecessarily Copy-paste responses — Generic answers that don't address the issue Invisible backlog — Tickets aging without visibility No feedback loop — Support insights never reach product Over-automation — Bots handling issues that need humans