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What are queue analytics?
Queue analytics turns the queue into data: join time, wait time, service time, completion, no-show and walkaway, by queue and time of day. With that you can staff to demand and prove the effect of changes. See queue KPIs.
Measuring wait times
Measure actual wait (clock time) and perceived wait (how it felt). The gap between them is the experience you can fix without adding staff. Read measuring wait times.
Queue performance metrics
Core metrics: average wait, longest wait, service time, throughput per hour, walkaway rate and no-show rate. See queue performance metrics.
Capacity planning
Use historical peaks to schedule staff so the queue never overflows. Read capacity planning.
Customer flow analytics
Follow the customer from join to served to spot where flow breaks—reception, service desk or handover. See customer flow analytics.
Act on the data with features, pricing, industries or book a demo.
Frequently asked questions
What are the most important queue KPIs?+
Average wait time, longest wait, service time, throughput per hour, walkaway rate and no-show rate are the core queue KPIs.
How is perceived wait time measured?+
Perceived wait is best captured with a short post-service rating, then compared against the actual clock wait. The gap shows the experience problem.
How does analytics help capacity planning?+
Historical peaks show when demand lands, so you can schedule staff to keep wait times acceptable before the queue forms.