Skip to main content

Reports - POS Order Details Report

Written by Andy Hornbeak

The POS Order Details report goes one level below the order — one row per item sold, with the product, the quantity, the price, and the income account it posts to. It is how you find out what is actually selling, rather than just how much you took.

This article assumes you already know the basics of the Sharper reporting module — the Name, Token, Subtotal, column picker, and filter fields. For a full walkthrough of the reporting form itself, see the Sharper Reporting Reference Guide. This article only covers what's specific to Order Details.


Why This Report Matters

Order totals tell you how the store performed; item detail tells you why. That distinction is what drives stocking, pricing, and menu decisions. Use it to:

  • Rank products by units sold or revenue, to see what carries the store

  • Find slow sellers before you reorder them

  • Total point of sale revenue by income account for accounting

  • Compare category performance — food against drink, chandlery against fuel


One Row Per Item, Not Per Order

Every order appears once for each item on it, with the order-level details repeated across those rows.

Because the order repeats, counting rows counts items rather than orders. The line-level Subtotal, Discount, Tax and Total columns are per item and add up correctly, so use those. And as with the Orders report, voided orders are included — filter on Order Status or your totals will be overstated.


Building an Order Details Report

  1. Go to Reports → Point of Sale → Order Details in the left sidebar.

  2. If a shipped report is close to what you need, use the ⋯ menu → Copy first — shipped reports can only be edited by the Sharper team.

  3. Otherwise click + New and give it a Name, such as "Product Sales Ranking."

  4. Add the columns below from the Available panel.

  5. Set Subtotal to Total or Quantity depending on whether you are ranking by revenue or by units.

  6. Turn on Summarize Report for a product summary rather than every individual line.

  7. Click Save, then Get Report to set a date range and run it.


Available Columns

Field

What It Shows

Product Name, Product SKU

What was sold — the reason to use this report over POS Orders

Product Category Name

The category the item belongs to. Group on this to compare parts of the range against each other.

Quantity

Units sold — subtotal this to rank by volume rather than value

Subtotal, Discount, Tax, Total

The line's values

Income Account

Where the item's revenue posts. Group on this to reconcile point of sale takings against the general ledger.

Order

The order the item belongs to — group or sort on it to see a whole basket together

Order Date, Order Time, Order Hour

When the sale happened. Order Hour is ready to group on for time-of-day analysis.

Order Status

Whether the order completed or was voided — include it on anything you total

Register Name

Which register sold it

Voided By, Void Reason

Void detail, where the order was cancelled

User Display Name

Who rang the sale — useful for reviewing discounting by person

Customer Name, Cust Type

The customer, where the sale was attached to an account

Note: Modifiers are not itemized here. An item sold with extras shows its own line and the price effect of those extras, but the extras themselves are not listed — for that, use the POS Order Modifiers report.


Useful Filters

  • Best sellers by revenue: group by Product Name, subtotal on Total, completed orders only, sorted descending.

  • Best sellers by volume: the same, subtotalled on Quantity instead — the two rankings are often quite different.

  • Category performance: group by Product Category Name with Total subtotalled.

  • Point of sale revenue by account: group by Income Account, to tie back to the ledger.

  • Discounted items: Field Discount, operator >, value 0, with User Display Name selected.

  • One product's history: Field Product Name, set to the product, over a season.

Running the two best-seller rankings side by side is the most useful comparison here — a product that ranks high on volume but low on revenue is often one worth repricing.

Did this answer your question?