Plan requirement
| Subscription | x-hoppers SuperHopper + AI |
Which call points get used, how long customers wait, and how stores compare. Here is what to do with those numbers.
Where it lives
Open x-hoppers on the web and go to the Analytics tab. It needs WMS 7.0X or higher as well as the subscription above.
What you are looking for sits in one of five tabs, and knowing which saves the hunt:
| Users | Who is online now, how long each person has been in the broadcast, and daily figures per store. |
| Notifications | The requests themselves, which is where call point usage and waiting times live. |
| Hardware | The state of the headsets: battery levels, which are charging, which are running low. |
| Telephony | Call statistics. |
| Liveboards | Reports you build yourself when the standard ones do not answer your question. |
The Hardware tab is the one nobody opens and the one that prevents a bad morning. A headset that never leaves the charger, or a battery that no longer holds, shows up here before somebody starts a shift without a working headset.
What you can see
| Requests per call point | Which spots customers use. |
| Response times | How long between a scan and someone accepting. |
| Time on the floor | Per staff member. |
| Store comparison | Across your estate. |
You can have it sent to you
Reports can be scheduled, so the weekly look at response times arrives by itself rather than depending on somebody remembering to open a tab. For anything you intend to act on regularly, schedule it.
The two numbers that matter most
Call points with no requests
A call point nobody uses is in the wrong place, or badly signposted, or people do not know what it does. Move it or improve the sign; leaving it there teaches customers that the QR codes do nothing.
Requests that waited too long
Consistently slow response in one zone means staffing rather than technology. That is a rota conversation, and this is the data that makes it a factual one instead of an argument.
Look at the busiest hour, not the daily average. A store that responds in thirty seconds on average may take four minutes on Saturday afternoon, and Saturday afternoon is when it costs you a sale.
Comparing stores fairly
Footfall, layout and staffing differ, so raw comparison is misleading. Compare a store to itself over time first, and only then to others. A store improving month on month is doing something right even if it is not top of the table.
What not to do with it
Individual time-on-floor figures are tempting to use for performance management and usually a mistake. People optimise for the number rather than the customer, and accepting a request quickly to log a fast response helps nobody.
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