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Monitor queue depth, SLA compliance, and channel mix without exporting spreadsheets.
Helpdesk analytics
Support analytics that drive decisions Volume, CSAT, and agent performance
Track ticket volume, response times, resolution rates, CSAT, and agent workload from dashboards built for support leaders.
Last updated on 2026-07-08
Written by Malik S
Reviewed by Gandral V
Agent performance
See handle time, first response, and resolution rates per agent and team.
CSAT and feedback
Collect post-resolution ratings and tie scores back to tickets and agents.
Overview
Support analytics is a decision tool, not a scoreboard. Helpefi reports queue depth, response times, SLA compliance, CSAT, and workload per agent from the same ticket data agents work in. The useful question is never what the number is, it is what you would change if the number moved.
Operational dashboards for the daily standup
The morning view is about flow: open tickets by status, unassigned tickets older than a few hours, and anything approaching a breach. That is enough for a ten-minute standup to assign priorities before the queue drifts. Channel mix helps decide where the next hour of attention goes. Dashboards refresh as tickets change, so a lead does not need to export a CSV to answer whether the team is behind right now.
SLA reporting that holds up
Report compliance per policy, per queue, and per week, with the open count beside the percentage. Break breaches down by time of day and channel to find the pattern: a Friday afternoon gap looks like poor performance until you see it is the one hour with no coverage. Include paused tickets separately so waiting on a customer is not scored as a failure. Export the ticket rows behind any figure, because a leader will eventually be asked to justify it.
CSAT and quality analysis
A CSAT survey sends when a ticket is resolved and the rating attaches to the ticket, the agent, and the queue. Read the comments, not only the average: a five-question survey with a four-point average hides the specific complaint that repeats. Filter low scores by topic to separate product problems from support problems. Share positive comments with agents by name, since the public numbers rarely reflect the difficult conversations that ended well.
Agent metrics that are fair
Handle time and ticket count reward speed, which can reward closing early. Pair throughput with reopen rate, CSAT, and resolution quality so a fast close with a follow-up does not look like a win. Compare agents against the queue they work rather than against each other, because a specialist queue has different constraints. Use the data for coaching and capacity, and be explicit about what is not measured, such as the time spent helping a colleague.
Volume analysis and capacity planning
Ticket volume by hour and weekday turns a hiring argument into a schedule argument. Compare volume against staffing to find the gaps, and check whether the same issue keeps arriving: a spike in password resets is a knowledge base and product problem before it is a staffing problem. Seasonality matters for retail and travel, where a week can carry a month. Trend lines over a quarter are more useful than any single day, which is usually the day something broke.
Use case: Daily operations review
A ten-minute standup uses queue depth, breach risk, and unassigned age to set the day's priorities.
Use case: Weekly SLA review
Leads review compliance by queue and hour, then adjust the rota where the same gap keeps appearing.
Use case: Monthly quality review
Low CSAT tickets are read individually, common themes are grouped, and findings go to product or content owners.
Use case: Quarterly planning
Volume trends, resolution time, and channel mix support a staffing model that finance can review.
Use case: After an incident
The volume spike and recovery curve show how long customers were affected and where the queue broke first.
Numbers tied to a decision
Start with queue depth, response time, and CSAT. Add a metric only when someone will act on it. A short dashboard reviewed weekly beats a warehouse nobody opens.
Frequently asked questions
- Can we export analytics data?
- Yes. Dashboards export as CSV, and the API returns the same ticket-level data for a BI tool or warehouse.
- Is CSAT included?
- Yes. Surveys send on resolution and ratings attach to the ticket, the agent, and the queue. Survey copy is editable.
- Which metrics are available?
- Ticket volume, first response, resolution time, SLA compliance, reopen rate, CSAT, handle time, and channel mix, all filterable by queue and brand.
- Can we build custom dashboards?
- Saved views combine filters and metrics for a team or a review. The API covers anything a dashboard does not.
- How do you measure agent performance fairly?
- Compare agents within similar queues and pair throughput with reopen rate and CSAT, so speed alone does not read as good performance.
- Can non-support teams see the numbers?
- Role permissions can grant read-only access to a product or finance stakeholder without exposing customer conversations.
- Which plans include analytics?
- Core dashboards are available on every plan. API access and export depth depend on tier or the Integrations module.
References & sources
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