Counts accept fractions: 1/2, 2 1/2, or 2.5 all work. Leave an item blank or tap Skip to leave it out of this count — it keeps its last known on-hand and is never assumed to be zero. Enter 0 only if it’s truly out. Scanning a UPC jumps to that item; unknown UPCs can be assigned on the spot.
Separate guides for vendors or item groups on different schedules — e.g. Food (Mon/Wed/Fri) and Liquor (Mon only). Each guide has its own count days, and trends are calculated per guide.
Order suggestions predict usage from recent counts, then adjust for seasonality and events. All settings here apply to every store.
Trend-based targets are increased by this percentage to cover normal swings.
The forecast averages the last 3 matching counts, weighting the most recent heaviest. Percentages should add up to 100.
Upload a year of weekly sales as a seasonal proxy. CSV columns: week (1–53), sales. Weeks that sell above your yearly average scale orders up; below, down. Replaced automatically per-item as count history builds.
One-off boosts for known events (festivals, private parties). Orders in the date range are multiplied by this factor, stacking with seasonal adjustments.
Where items are stored in this store. Items can have more than one. Click to remove.
Everything resolves to a base unit: CT (each), OZ-wt (weight), OZ-fl (volume). New units can reference any existing unit: LB = 16 × OZ-wt, then Case-25LB = 25 × LB.
Import units from CSV — columns: name, factor, ref_unit (rows are processed in order, so a unit can reference one defined above it):
Add a brand:
Add a store:
Reset just this store's items, counts, guides & locations — or wipe everything for every store.
Invite people by email — they'll get a link to set their own password. Assign each person a role and the store(s) they manage; admins automatically see all stores.
Invite a new user:
Items, history, logs, units, brands, stores, guides, team, settings. Importing overwrites all shared data.