See what sells.
Know what comes next.
A working example of how store and online information could become clearer buying decisions, fewer reconciliation questions, and a useful daily briefing.
Explore sizes, colors, markdowns, returns, stock movements and settlement records. All sample inputs are generated for this concept, not taken from Famous Brands accounts.
No store, ecommerce or payment systems connectedThe retail picture, with a path to every number.
Compare weeks, departments and channels. Sales, product margin and cash settlement answer different questions.
Net sales by department
Store versus online
What needs a closer look?
Weekly comparison
Days 01–28 are synthetic periods, not actual calendar dates. All margin and return metrics are defined in their detailed views.
What sold—and what came back?
Follow styles into individual sizes and colors. Sales records aggregate one SKU, day and channel; they are not individual customer receipts.
Style performance
Refunds use the sample selling price, after markdown. Returned units are linked to the same aggregated sales record. A live returns workflow needs original receipts, refund dates and reason codes.
Buy and replenish at the SKU level.
Inspect stock movements and test next-period demand. Inventory uses the whole 28-day period and shared sample stock pool; the selected department applies.
How the plan is calculated
Closing stock = opening + receipts + resellable returns − gross units sold. Non-resellable returns do not re-enter stock. Demand = latest 7-day net units ÷ 7 × (1 + selected growth). Target = ceiling(demand × planning days × (1 + buffer)). Replenish = max(0, target − closing stock). Suggested cost = replenish × sample unit cost. Days cover = closing stock ÷ historical daily net units. No supplier lead time, open purchase orders or seasonality is modeled.
Separate selling price from product margin.
Markdowns and returns reduce revenue; sample product costs explain the contribution remaining before fees and operating expenses.
Same selected net-unit volume and costs. No demand lift assumed.
Net sales = list-price gross − discounts − refunds. Product cost = (sold units − resellable returned units) × unit cost, retaining cost for damaged/non-resellable returns. Gross product margin = net sales − product cost. Labor, rent, shipping, taxes and payment fees are excluded; this is not operating profit.
Explain the deposit, not just the sales total.
Date and channel filters apply to batches; department is excluded because deposits settle the whole channel.
Reconciliation assumptions
Sample store sales use 84% card / 16% cash; online sales use 100% card. Modeled fees = 2.6% of card captured + $0.10 per estimated card transaction. These are fictional assumptions, not Famous Brands’ rates or a proposal. Expected deposit = card − fees − sample held reserve. One batch has a $79 recorded shortfall; two deposits are pending. Known variance excludes pending deposits. Chargebacks, tax, tips, cross-day refunds and fee adjustments are not modeled.
Ask a useful retail question. See the evidence.
This is a deterministic analysis preview using this demo’s records, not a live language model. Responses identify their scope and explain the calculation.
Erin’s retail management briefing.
A traceable summary for the selected sales scope, with separately labeled payment and inventory scopes.
Start with one useful workflow
Clover, Shopify or other integrations depend on the actual setup, available exports/APIs, permissions and agreed scope. No live connectivity, savings or platform migration is promised.
Talk through the demo with Chris →