Fast-casual POS, menu mix, and store P&L
Industry
Fast-casual restaurants (build-your-bowl, wrap, and salad)
Restaurants
12 company locations across 4 U.S. metro markets
Menu
120 items across bowls, wraps, salads, sides, drinks, and desserts
Volume
about 1.4M POS tickets and 2.1M menu lines over the two years
Throughput
about 164 tickets per store per day
Average check
about $15.80 net on a closed ticket (about $16.45 gross)
System scale
about $23.1M in gross system sales across the two-year window
Annual net
about $10.9M a year once discounts, comps, voids, and refunds come off (about $21.7M across the window)
Same-store sales
up about 5 percent in year two, all of it check rather than traffic
AUV
about $0.90M average unit volume per restaurant per year
Dataset scope
13 Professional-tier tables
Sabeona Restaurant Group is a fictional regional fast-casual restaurant chain created for synthetic BI demos and training; it represents no real restaurant brand, location, menu, staff member, guest, or delivery marketplace. The kit presents a believable build-your-bowl operator at the scale of a tight, busy regional group: a dozen high-volume restaurants averaging about 164 tickets a day across four metros. BI builders move from monthly store sales into menu engineering, food and labor cost, store four-wall P&L, loyalty membership, and on-premise versus delivery economics. It is built for restaurant operations, finance, and marketing teams rather than as a point-of-sale system of record.
These are the operating questions this kit is optimized to answer first.
Track net sales, food and labor cost, and four-wall margin by month and across the twelve stores, four markets, and formats.
Split comp growth into traffic and check across the ten restaurants open both years, and see why Chicago comps triple Dallas.
Rank items by sales and plate food cost to find margin heroes and cost pressure.
See how lunch and dinner, dine-in and delivery, drive the sales base and the check.
Follow enrollment, tier mix, recency status, and ticket share across cohorts of real member activity.
Trace a delivery order from subtotal through commission and promo to net remitted to the store.