Restaurant Analytics: The 6 Numbers Every Operator Should Check Daily?
The six daily metrics — covers, average ticket, labor %, food cost %, voids, and repeat rate — that tell you in five minutes whether your restaurant made money today.
Restaurant analytics is the daily practice of reading a small set of operating numbers to know, before you go home, whether the shift made money and where it leaked.
Most operators drown in dashboards. You don't need 40 charts — you need six numbers checked every single day. Here they are, with the ranges that matter.
What are the 6 numbers I should check daily?
- Covers — how many guests you served. This is your demand signal. Track it against the same weekday last week, not yesterday.
- Average ticket (check average) — total sales divided by covers. A full-service spot might run $28–$45; quick-service $9–$16. A falling average usually means weak upselling or menu-mix drift.
- Labor % — labor cost divided by sales. Healthy is 25–35% for most formats. Above 35% on a slow night means you over-scheduled.
- Food cost % — cost of goods divided by sales. Target 28–35%; pizza and pasta concepts can hit 22–28%. A 3-point jump overnight points at portioning, theft, or a supplier price rise.
- Voids and comps — the dollar value of cancelled or comped items. A spike is the single best early-warning signal for till errors or staff shrinkage.
- Repeat rate — the share of today's guests who ordered from you before. On a commission-free direct channel you actually own this data, so you can measure it.
How much do these numbers move profit?
A worked example: a $12,000-sales day. Drop food cost from 34% to 31% and you keep an extra $360 that day — about $130,000 a year. Trim labor from 33% to 30% on the same sales and that's another $360. The numbers are small per shift and enormous per year, which is exactly why daily checking beats monthly accounting.
Why does owning the data matter?
If 28% of your orders flow through a third-party marketplace that charges 25–30% commission and hides the customer's contact details, your repeat rate is unknowable and your margin is gone. Direct Dine is commission-free and the order data stays yours, so covers, average ticket, and repeat rate are all measurable on your own channel — and that data is handled under GDPR and CCPA rules, with retention and erasure controls built in. This is not legal advice, but owning first-party data is what makes daily analytics possible at all.
When is daily analytics NOT worth it?
- Pre-opening or week one — you have no baseline yet; collect two to three weeks before drawing conclusions.
- Single-number panic — never react to one day in isolation. Food cost spikes on delivery-heavy days because packaging counts as cost of goods; that is normal.
- Tiny operations — a one-person coffee cart can read covers and cash and skip the rest.
The goal isn't more data. It's six numbers, every day, compared to the same weekday last week — the fastest honest read on whether you're running a business or a hobby.
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