Define the ticket population
Give Nema the export period, included queues, status definitions, and known exclusions. State whether reopened tickets count once or as separate cases. If the sample covers only one region, plan, or channel, put that limit at the top of the report.
A rate needs a denominator. A count of login issues means little until the reader knows how many tickets were reviewed and how duplicates were handled.
Group issues with evidence
Ask Nema to cluster cases by the underlying customer problem and link representative tickets. Shared words are not enough. Two billing tickets may concern different policies, while differently worded reports may describe one product defect.
Keep uncertain matches visible. The support lead can confirm whether cases are duplicates or separate experiences before the report is shared more broadly.
Measure where work waits
Use supplied status timestamps and routing fields to show how long cases spent in each defined state. Separate customer waiting time, internal queue time, and active work if the export supports those distinctions.
Missing or inconsistent timestamps should become data-quality flags. Nema should not calculate a clean average by silently dropping the hardest cases. A median, range, or distribution may tell the story better than one headline number, depending on the team definition.
Turn patterns into review questions
The report can point to candidate documentation gaps, routing problems, or product investigations. It should not claim a deflection rate or root cause without the required evidence. Support and product owners choose the next investigation.
Review the report in Slack and let owners annotate misclassified cases. Nema can revise the grouping while preserving the original sample and report date.
Start with one queue
Choose a queue whose fields the support lead understands. Run one completed month, inspect cases from every major group, and recalculate key measures independently. Expand only after the team trusts the labels and time definitions.
Questions from support leaders
Can Nema find the root cause?
It can connect recurring case evidence and propose questions. Engineering or the responsible owner confirms technical or process causes.
How are duplicate tickets counted?
Provide a duplicate rule and ask Nema to show likely matches. The support lead validates them before using the count.
Does fewer tickets mean support improved?
Not by itself. Volume can change with usage, channel mix, outages, seasonality, and reporting. The review should state what the sample supports.