Front of house, by server. Who sold what, and how.
The page
Pick a date and a venue. It is live — the numbers move during service. The print button gives you a paper copy.
The table
Server — as your POS knows them.
Gross sales — before discounts.
Net sales — after.
Discounts — what they gave away.
Items sold — how many.
Checks — how many bills.
Avg check — net divided by checks.
Sorted by gross by default. A Total row sits on top.
Not every row is a person
Your POS has accounts that are not servers: a bar terminal, a takeout station, a house account. They appear here because they rang in sales.
AM Bar with 14 checks is a terminal, not someone called Am. Know which of your rows are people before you read anything into them.
Reading it
Avg check is the number that says something. Two servers with similar gross can have very different average checks — one turned twenty small tables, the other held six large ones. Neither is wrong. They are different jobs.
Discounts is the number to watch. A server whose discount column is consistently above the others is either working the door on comps, or they are not. Open Check Analyse, filter to Discounted, and look at their checks.
One server
Click a row.
The cards — gross, net, average check, items sold, checks, discounts, for that server on that day.
Time of day — their sales, hour by hour. The axis runs 5am to 3am: that is the business day, drawn. A spike at noon and nothing after 3pm is a lunch shift, and the chart says so without anyone writing it down.
Top items sold — what they moved, quantity, gross, net.
Switch Server jumps to someone else without going back.
What top items tells you
Whether someone sells what you want sold.
A server whose top items are the high-margin dishes is doing something the others are not. That is worth knowing, and it is worth asking them how.
Next
AI Forecast — tomorrow, before it happens.