Analytics

The numbers a front desk could never give you

How many you served, how long people waited, what they thought of it, and how many never turned up — each against the period before, for one branch or all of them.

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What it is

Analytics

Analytics opens on four numbers — people served, average wait, satisfaction and no-show rate — each with the change against the period before it, so a figure is never just a figure. Under them the page answers the harder questions: which branch is doing better, how each person on your team is doing, where people give up waiting, whether you had enough staff on for the people who arrived, and which hours are actually your busiest. Pick last 7, 30 or 90 days, and one branch or all of them.

How it works

Step by step

1

Pick a range and a branch

Last 7, 30 or 90 days, all locations or one. Everything on the page re-answers for that window.

2

Read the four headline numbers

People served, average wait, satisfaction and no-show rate — each showing whether it is better or worse than the period before.

3

Let it tell you what it found

The page writes a short “what went well” and “what to improve” from your own figures, so you are not left to interpret a chart.

4

Then go one level down

Branch against branch, person against person, when people give up, and a heat map of when they arrive.

The honest edge

It says what to do about it, not just what happened

Most dashboards stop at a chart. This one names the finding — “82% of visitors left before being served, typically after about seven minutes” — and puts the abandonment curve next to it so you can read off the wait your customers will actually tolerate, and set your max-wait to it. The same section puts arrivals against how many people were signed in to a station, hour by hour: where the queue is long and nobody is on, that is where another pair of hands pays for itself.

Also included

Everything else on this page

Branch against branch

Served, average wait, rating and no-show rate for each location, side by side — the comparison a group owner opens first.

How each person is doing

Services completed, average service time, the rating visitors gave those services, and a fair share of the volume. Not shown to staff.

Hours and utilisation

Time signed in to a station against time actually spent serving — and how many shifts ended by something other than signing out.

When you are busiest

A heat map by hour and weekday, with the peak named in a sentence, so you can roster against it.

A satisfaction score that is real

The star figure is the average of the ratings your visitors actually left in that range, and the page says how many that is.

Your own numbers if you are on the floor

Anyone serving has a personal view of what they got through, separate from the owner’s dashboard.

Common questions

Can my staff see how everyone is performing?

No. The per-person tables are marked “not shown to staff” and live on the owner and manager dashboard. Someone who serves sees their own numbers and nobody else’s. Whether a manager sees analytics at all is one of the switches you control.

Do I have to set anything up to get this?

No. It is built from the queue you are already running — every join, call, serve and no-show is already recorded, so the dashboard fills itself in from day one.

Why does Analytics show a smaller total than Reports?

They count different things and both say so on the page. Analytics counts PEOPLE — one person, however many desks their visit passed through. Reports counts SERVICES, one per completed stop. On a multi-stage journey the reports total is higher, and neither is wrong.

Can I get the underlying rows out?

Yes — nine named reports download as CSV, Excel or PDF, filtered by branch, person and date range.

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