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Average time taken for an agent to send the first reply after a ticket is created. Critical for measuring responsiveness.
Mean duration from ticket creation to final resolution, helping identify efficiency bottlenecks.
Post‑interaction rating collected via surveys, expressed as a percentage of satisfied customers.
Measures customer loyalty by asking how likely they are to recommend the service on a 0‑10 scale.
Daily/weekly/monthly count of incoming tickets, visualized to spot spikes or seasonal patterns.
Shows tickets grouped by age (e.g., <1 day, 1‑3 days, >3 days) to highlight overdue work.
Real‑time view of SLA adherence per priority, channel, and agent, with breach alerts.
Percentage of an agent’s logged work time versus scheduled capacity, useful for workforce planning.
Proportion of tickets resolved in the first interaction, indicating issue‑handling effectiveness.
Frequency at which resolved tickets are reopened, flagging potential quality issues.
Breakdown of ticket volume by source (email, chat, phone, social, portal) to allocate resources wisely.
AI‑driven scoring of customer messages to gauge mood and prioritize negative experiences.
Drag‑and‑drop interface for creating role‑based dashboards with any combination of metrics.
Set recurring email deliveries of PDF/CSV reports to stakeholders on daily, weekly, or monthly cadence.
Visual heatmap displaying peak handling times per agent, aiding shift optimization.
Tracks views, helpful votes, and deflection rate of self‑service articles.
Measures how easy it was for customers to get their issue resolved, collected via post‑ticket surveys.
Predictive analytics that estimate required headcount based on ticket volume trends and SLA targets.
Links ticket outcomes back to the originating channel and campaign for ROI measurement.
Reports on tickets that were escalated, including time to escalation and resolution after escalation.
#22 Agent Scorecard
Composite KPI view per agent (FRT, ART, CSAT, FCR, utilization) for performance reviews.
Live view of open tickets per queue, average wait time, and SLA breach risk.
Pie or bar chart showing proportion of incidents, requests, problems, and changes.
Aggregates recurring issue categories to surface systemic problems.
Visualizes each touchpoint a customer experiences across support channels.
Average duration customers spend on hold before speaking to an agent.
Compares pre‑ and post‑training performance metrics to quantify learning ROI.
Long‑term tracking of SLA/SLO compliance percentages to assess service reliability.
Percentage of contacts resolved via self‑service or automation without creating a ticket.
Calculates operational cost per resolved ticket, factoring labor, software, and overhead.
Aggregates free‑form feedback, sentiment, and survey comments into actionable insights.
Tracks hand‑offs between support, engineering, and product teams, including time to hand‑off and resolution.
Provides immutable logs of ticket actions for regulatory compliance (e.g., GDPR, HIPAA).
Allows users to define CSV/Excel export schemas for downstream BI tools.
Machine‑learning engine surfaces anomalies, predicts ticket surges, and recommends staffing adjustments.