Call Statistics
Queue monitoring, SLA tracking, wait time distribution, and call volume trends.
Overview
Call Statistics gives operations managers a deep-dive view of queue performance, SLA compliance, and call volume patterns over time. Unlike the Dashboard — which is optimised for real-time situational awareness — Call Statistics is focused on historical analysis to support staffing decisions, SLA reporting, and trend identification.
The screen is laid out as a single scrollable page with a period selector at the top. All charts, tables, and metrics on the page update simultaneously when you change the selected period. No tab-switching is needed — all statistics are visible on one canvas so you can cross-reference queue SLA against wait time distribution and volume trends without navigating between sections.
Dashboard vs. Statistics — Which to Use
Use the Dashboard when you need to know what is happening right now — agent headcount, current inbound volume, live KPIs. Use Call Statistics when you need to understand patterns over time — SLA compliance over the past month, which hours are consistently understaffed, how call volumes have grown week-over-week. Both screens complement each other.
Queue Monitor
The Queue Monitor is a live snapshot table at the top of the screen showing the current state of every configured queue in your PBX. It updates each time you click the Refresh button (or automatically every 30 seconds if auto-refresh is enabled in Settings).
| Column | Description | Alert Threshold |
|---|---|---|
| Queue Name | Name and extension number of the queue as configured in PBX Management | — |
| Calls Waiting | Number of callers currently holding in queue waiting for an agent | Highlighted red when > configurable threshold (default: 5) |
| Calls in Progress | Number of calls currently connected to agents in this queue | — |
| Agents Available | Agents in this queue currently in Available state (ready to take calls) | Highlighted amber when < 2 agents available |
| Total Agents | All agents assigned to this queue regardless of current status | — |
| Avg Wait Time | Average wait time for the current period for this queue (seconds) | — |
| SLA % | Percentage of calls answered within the queue's SLA target time | Colour-coded (see SLA Tracking section) |
Acting on Queue Data
If a queue shows 5+ calls waiting with only 1 agent available, navigate immediately to Supervisor Dashboard to see which agents are on break or available in other queues. You can reassign available agents to the overloaded queue from the Supervisor screen to drain the wait queue quickly.
SLA Tracking
Service Level Agreement (SLA) tracking is the cornerstone of call center performance measurement. TotalApp's SLA system measures how well each queue meets its target for answering calls within a defined time window.
SLA Definition
The default SLA target is: 80% of calls answered within 20 seconds. This means that in any given period, at least 8 out of every 10 inbound calls to a queue must be answered within 20 seconds of entering the queue. Both the percentage threshold (default: 80%) and the target answer time (default: 20 seconds) are configurable per queue in Virtual PBX → PBX Management.
SLA Colour Coding
Each queue's SLA percentage in the Queue Monitor table and the SLA Tracking chart is colour-coded for immediate visual assessment:
| SLA % | Status | Badge Colour | Interpretation |
|---|---|---|---|
| ≥ SLA Target (e.g. ≥ 80%) | On Track | Emerald green | Queue is meeting its SLA commitment. No intervention required. |
| 70% – target–1% (e.g. 70–79%) | At Risk | Amber | SLA slipping. Monitor closely; consider adding agent capacity during peak hours. |
| < 70% | Breaching | Red | SLA breach. Immediate action required: reallocate agents, activate overflow, review routing rules. |
SLA Breaches in Reporting
SLA breach data is included in the PDF export and is automatically flagged with red highlighting in the report. When presenting to senior management or clients, focus on the trend — is the breach a one-off spike caused by an external event (e.g. a product recall, a service outage) or a persistent pattern indicating a structural staffing gap?
Wait Time Distribution
The Wait Time Distribution histogram shows how long callers waited in queue before being answered, across the entire selected period. The x-axis shows wait time buckets; the y-axis shows the count (or percentage) of calls that fell into each bucket.
Wait Time Buckets
A well-staffed call center should have 80% or more of all calls in the 0–10 second bucket. If you see a significant portion of calls in the 31–60s or 60s+ buckets, that is a clear signal that queue capacity is insufficient relative to inbound demand during those periods.
How to Use This Chart
- Compare across periods — Toggle from Last 7 Days to Last 30 Days. If the distribution looks worse over the longer window, call center performance is trending in the wrong direction.
- Cross-reference with hourly data — Long wait times in the distribution chart, combined with the hourly volume chart showing specific high-volume hours, pinpoints exactly when your queue is overloaded.
- Filter by queue — If you have multiple queues (Sales, Support, Billing), compare their distributions to identify which team is struggling most with wait times.
- Set a staffing benchmark — Use the histogram as your staffing target. Run a trial week with an extra agent in your peak queue and compare before/after distributions to quantify the improvement.
The 80/20 Rule for Wait Times
Industry standard for most B2C call centers is the "80/20 SLA": 80% of calls answered within 20 seconds. If your histogram shows the 0–20s bucket (0–10s + 11–20s combined) at 80%+, you are broadly meeting this standard. If it's below 70%, the wait time distribution histogram is your primary evidence when making the case for additional headcount.
Call Volume Trends
The Call Volume Trends chart is a dual-line chart showing daily call volume across the selected time period. Two lines are plotted:
- Inbound — total inbound calls per day (sky blue line with data point markers)
- Outbound — total outbound calls per day (violet line with data point markers)
Hover over any data point to see the exact call count for that day. Click a data point to filter the Queue Monitor and Wait Time Distribution to show data for that specific day only.
Common Patterns to Watch For
- Monday spikes — Many call centers see a Monday inbound surge as customers call after weekend outages or with questions they accumulated over the weekend. If your Monday line is consistently 30%+ above other weekdays, consider heavier Monday staffing.
- Friday drops — Inbound volume typically drops on Friday afternoons. If your outbound line stays high on Fridays, this is normal (agents making proactive outreach when inbound is quiet).
- Seasonal trends — Use the Last 90 Days view to see month-over-month growth patterns. Consistent week-over-week growth may indicate product adoption growth that will require additional headcount in the next quarter.
- Anomaly spikes — A sudden single-day spike in the inbound line often corresponds to an external event: a service outage, a marketing campaign going live, or a news story affecting your product. Correlate with your operational calendar to confirm.
Call Type Breakdown
The Call Type Breakdown is a donut chart showing the proportion of each call type as a percentage of total calls for the selected period. Five segments are shown:
| Segment | Colour | Definition | Healthy Benchmark |
|---|---|---|---|
| Inbound | Sky blue | Calls received from external numbers that were answered by an agent | Largest segment for inbound-heavy centers |
| Outbound | Violet | Calls initiated by agents to external numbers | Varies by team type (sales teams: high; support teams: lower) |
| Internal | Slate | Extension-to-extension calls within the organisation | Should be small (<10%) for a customer-facing call center |
| Missed | Amber | Inbound calls that rang but were not answered by any agent | Target: <5% of total calls; above 10% indicates understaffing |
| Abandoned | Red | Callers who hung up while waiting in queue before being answered | Target: <5%; above 8% indicates long wait times or poor queue experience |
Each segment in the donut chart is clickable. Clicking a segment filters the Queue Monitor table and the Call Volume Trends chart to show data for that call type only, letting you drill into the data for a specific segment without leaving the page.
Period Selector
The period selector at the top of the Call Statistics screen controls the time range for all charts and the queue monitor table. Four options are available:
| Option | Data Range | Best Used For |
|---|---|---|
| Last 7 Days | Rolling 7-day window ending today | Weekly operations review; comparing this week to last week |
| Last 30 Days | Rolling 30-day window ending today | Monthly reporting; SLA compliance for the current month |
| Last 90 Days | Rolling 90-day window ending today | Quarterly review; seasonal trend identification; headcount planning |
| Custom Range | User-defined start and end date | Specific reporting periods (e.g. a campaign run, a specific month, an incident window) |
Custom Range for Client Reports
When preparing SLA reports for clients or internal stakeholders, always use the Custom Range option to match the exact contractual reporting period (e.g. 1st to 30th of the previous month). Rolling windows like "Last 30 Days" will not match a fixed calendar month unless you happen to be on the last day of the month.
Export
Call Statistics supports two export formats accessible from the Export button in the top toolbar. Both exports respect the currently selected period and any active filters.
PDF Report
A formatted multi-page PDF containing: cover page with period and date generated, Queue Monitor table with SLA colour coding, Wait Time Distribution histogram, Call Volume Trends chart, Call Type Breakdown donut, and a summary statistics table. Formatted for A4/Letter. Ideal for sharing in management meetings or with external stakeholders.
CSV Export
Raw data export containing: per-day call counts by type, per-queue SLA metrics, wait time distribution bucket counts, and agent-level summary statistics. Use in Excel, Google Sheets, or BI tools (Power BI, Tableau) for custom analysis, trend modelling, or integration with your existing reporting infrastructure.
AI Assistant
Call Statistics ships with a built-in AI Assistant. Click the vertical AI Assistant tab on the right edge of the screen (or the Sparkles toggle) to open a chat panel that reads the call log and wait-time summary (total, answered, missed) for the currently selected period (All / Today / Yesterday / Week):
- Volume & cost analysis — summarizes call volume, duration, and cost trends for the selected period.
- Missed-call analysis — flags extensions or periods with high missed-call rates.
- Recommendations — prioritizes follow-up actions based on the actual numbers shown.
Every reply can be saved with the Save as Report button, which stores it in My Reports under a title derived from your question and the current month/year. The panel respects the Writer Engine selected in Settings → Agentic (Local CLI, Hosted API, Local LLM, or Ollama) — Ollama and other local/in-browser engines run entirely on your own machine and never proxy through the server.