Analytics Guide

Every team needs a clear picture of what is happening in their support desk and community — how many requests are coming in, how fast the team responds, and where the bottlenecks are. Analytics is the module that turns that raw activity into reports you can act on, managed in Applications » Analytics.

Analytics is event-based: instead of just counting how things look right now, it records a snapshot of an object (a ticket, topic, article, chat, etc.) at the exact moment something happens to it — for example, when it's created, when a reply is sent, or when it's completed.

How Analytics Works

Event-Based Snapshots

When you apply a date filter to a report, you are telling Analytics which events to include, based on when they occurred — not what the object looks like today. For each matching event, Analytics shows the state of that object at the latest point within your selected time range , so you always see the most up-to-date picture available for that period.

Key Concepts

Default Reports

Once you enable Analytics in the Applications menu, a set of standard, ready-to-use reports appears automatically in the left-hand menu. You don't need to build these from scratch — you can start reading them right away, and personalize them later if needed.

You can personalize any pre-built report to your preference, or build your own from scratch — covered next. 

Metrics Reference

Every widget is built around a Metric. Think of the Metric + Filter combination as the question you want answered: How many tickets did my team complete? How many tickets do we have in each status? How much time does it take my team to respond to customers?

1. Object-Based Metrics

2. Reply & Response Metrics

3. Customer Satisfaction Metrics

4. SLA Metrics

5. Votes Metrics

Filters Reference

Filters let you narrow a widget down to exactly the slice of data you care about. Most filters apply to all metrics; a few don't make sense for certain metrics (for example, most object-level filters don't apply to Article Votes, since that metric is about articles, not tickets or topics).

Visualization Types, Group By & Sub-group By

Once a Metric and its Filters are set, choose how the data should be displayed. Analytics supports five visualization types, selectable from the icon bar at the top-right of the widget preview:

Where grouping is available, the dimensions offered depend on the metric, but commonly include:

• Object Type — split by ticket, topic, article, chat, etc.
• Assignee at Given Time — the agent assigned to the object at that point in time.
• Community — split by community/brand.
• Channel — the source channel of the object.
• Team / Responsible: Team — split by agent team.
• Days — split by day, useful for spotting daily patterns.
• Custom fields — Ticket or Topic custom fields, if configured.

Reply-based metrics add a few extra dimensions where relevant, such as Author, Status, and Agent: Team.

Calendar vs. Business: for time-duration metrics (First Reply Time, Average Response Time, Assignment to First Reply, Average Assignment to Reply, First/Full Resolution Time), the widget preview offers a toggle between Calendar time (24/7 clock time) and Business time (counting only the hours defined in your Working/Business Hours schedule). Use Business time if you don't want nights, weekends, or off-hours to inflate your response and resolution numbers.

Building a Report

Create a New Report

1. Click + Analytics: report.
2. Give your report a name.
3. Add your first widget.

Separate reports let you monitor performance across different communities, object types, or agent teams without cluttering a single dashboard.

Configure a Widget

Every widget has three components you configure together:

• Metric — the data you want to track.
• Filter(s) — how you narrow the data down.
• Visualization — how the result is displayed (Number, Line, Bar, Doughnut, Table), plus Group By / Sub-group By where supported.

1. Click + Add Widget on a report.
2. Enter a Widget title (by default, new widgets are named after the metric — rename them so your team can tell widgets apart at a glance).
3. Choose a Metric from the dropdown (see the Metrics Reference above for the full list, grouped by category).
4. Click Add Filter to narrow down the data — you can stack multiple filters; all conditions must match.
5. Pick the visualization icon (Number / Line / Bar / Doughnut / Table) in the top-right of the preview panel.
6. Pick a Group By (and, if available, a Sub-group By) dimension if you want the data broken down further.
7. For time-duration metrics, choose Calendar or Business time.
8. Click Submit. 

Manage Existing Widgets

Each widget has its own actions menu, available from the widget's header:

Best Practices for Building Reports

• Build one report per audience or goal — a daily workload dashboard for team leads, a monthly SLA review for management, a CSAT trend for QA — instead of one giant report mixing everything. Widgets are cheap to add; reports are what people actually open, so keep each one focused on a single question.
• Rename every widget. New widgets default to the metric's name (often literally "New"), which is meaningless once a report has more than one widget. A title like "Unassigned tickets — EU team" tells you what you're looking at without opening it.
• Use Business time, not Calendar time, for response/resolution metrics — unless you genuinely run 24/7 support. Calendar time silently punishes your team for nights and weekends and will make your response times look worse than they are.
• Pair a headline Number with a breakdown chart. A single "SLA Breaches: 12" card tells you there's a problem; a Bar or Doughnut chart grouped by Team next to it tells you where. Numbers are for status checks, charts are for diagnosis.
• Double-check "who" filters before trusting agent-level numbers. Metrics like Completed Objects or Average Assignment to Reply can include completions by the system or replies from non-assignees unless you filter Object: Completed By

  or similar to Agents / Selected Agent — otherwise a leaderboard will misrepresent individual performance.

• Trend, don't snapshot, anything you want to catch early. CSAT, backlog size, and SLA breaches are far more useful as a Line chart grouped by Days than as a single number for "This Month" — a single number tells you where you are, a trend tells you where you're heading.

Example Widgets

The five widgets below are single, self-contained answers to specific questions team leads ask most often. Each one follows the same pattern: the question → the best-practice reasoning → the exact Metric / Filters / Group By / Visualization recipe to build it as one widget.

Example 1 — "How many tickets does each agent close per day?"

Best practice: filter out system auto-completions first — Metric Completed Objects without Completed By: Agents filter will count tickets the system closed automatically (e.g. after inactivity) as if an agent had handled them, inflating everyone's numbers. 

Use Days as the main grouping so you get a daily trend, not a single monthly total, and Sub-group By Assignee to break each day down by agent in one chart.

Tip: if you only need one agent's number and don't need the daily breakdown, add a second, simpler widget: same Metric and Filters, plus filter Object: Completed by Selected Agent, visualized as a Number Card

Example 2 — "What is the average SLA per agent?"

There isn't a single metric called "SLA" in Analytics today — SLA performance per agent is best read as two widgets:
SLA Breaches shows how often an agent's tickets breach SLA, and Full Resolution Time shows how fast that agent actually resolves tickets.
Together they tell you what a single "SLA score" would try to summarize.

Tip: put both widgets in the same report, next to each other — an agent with low breach count and low average resolution time is genuinely fast; an agent with a low breach count but a high resolution time may just be working tickets that don't carry a strict SLA rule.

Example 3 — "What is the average First Reply Time by team?"

Best practice: First Reply Time is almost always the metric quoted in SLA agreements, so measure it in Business time — otherwise a ticket that came in at 11 PM and got a reply at 9 AM will show as a 10-hour reply time instead of a near-instant one at the start of the shift.

Tip: duplicate this widget with Group By set to Days instead of Team to see whether reply times are drifting over time, independent of which team is involved.

Example 4 — "What's the average CSAT score per agent?"

Best practice: pair the average score with the number of ratings it's based on — a 5.0 average from 2 surveys is not the same signal as a 4.2 average from 200 surveys, and showing only the average invites the wrong conclusion.

Tip: sort the Table by survey volume first — an agent at the bottom of the CSAT ranking with only 3 ratings needs more data before you act on it, not immediate attention.

Example 5 — "Which tickets are currently waiting on an agent, unanswered?"

Best practice: this is a live risk list, not a historical chart — you want the actual tickets, not a count, so you can act on them today. Keep it as a Table without grouping and filter it down to one team or queue at a time so the list stays short enough to actually work through.

Tip: pin this widget at the top of a "Today" report rather than a monthly one — its value is in being checked and cleared throughout the day, not reviewed at month's end.

Sharing and Permissions

By default, only Administrators can manage Analytics reports.

You can customize which agents have access to View or Edit  Analytic reports in User Permissions.

1. Navigate to User Profile → Permissions.
2. Enable or disable the View Analytics or Manage Analytics permissions as needed.

Analytics permissions can be managed on the team level as well. 

When creating a new team, select the required permissions to grant or restrict access to Analytics. Once users are added to the team, their permissions will be updated automatically based on the team's settings.