Retail analytics

Every store and channel, compared on one screen.

Bring store, online and inventory data into one model, compare stores side by side with small multiples, and give each district manager their own stores through row-level security.

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Row-level security and field masking apply to every dashboard, report, export and AI answer. See the controls

Weeks: last 8Default view

Sales vs last year, by store

This year

Harbor St+6.2%

Market Sq+3.8%

Riverside−2.1%

Old Town+1.4%

Station Rd+4.9%

Mill Lane−0.6%

Stock cover

Weeks

Product	Cover
Rain jacket	1.4
Trail shoe	1.9
Day pack	3.2
Wool sock	6.8

Illustration with sample data. Store performance as the North district’s manager sees it: row-level security returns only that district’s stores. Conditional formatting marks low stock cover.

The questions retail teams ask.

Each answer describes what the product does today, and links to the page in the documentation that explains how it works.

How does each store compare with the rest?
Bind the store field to the small multiples well and one chart becomes a panel per store, so a district reads as one grid instead of a stack of dashboards.
Small multiples
Can each district manager see only their stores?
A row-level security policy limits the rows each person sees. It applies to every chart, export and drill-down, and to the reports a manager subscribes to.
Row-level security
How did this week compare with the same week last year?
DateShift moves a measure to the same period last year, last quarter or last month, and the measure works in every chart built on the model.
SquareX time intelligence
Which lines are about to run out?
Conditional formatting colors stock cover below the threshold you set, and an alert rule on a KPI card tells the buyer when it crosses the line.
Conditional formatting

How the work runs.

Alerts when a number crosses its line, and the reports and reviews that arrive on a schedule.

Every day
Stock that needs attention
An alert rule on stock cover notifies the buyer by email or in the app when it falls below its limit.
Alert rules
Every week
Each store's own report
One scheduled report reaches every store manager, filtered to their store.
Data-driven delivery
Every season
The trading review
Write the season's trading review as a story, with live charts and a section assigned to each district.
Stories

Your data, where it lives.

Query point-of-sale and inventory data live in the database or warehouse it lands in, or upload it as files. Pipelines can pull in Shopify and Stripe data, and a WooCommerce connector is in preview.