Reports on BigCommerce data

Each report is one formula on live data. Type it in a cell; when a formula refers to A2, list the values in column A first (for example with =list.<table>(<column>)) and fill the formula down.

=data.orders.sum(net_total, counts_as_sale, TRUE)

Net sales. Order totals after refunds, for every order that counts as a sale (paid, being fulfilled, shipped, completed or refunded).

=data.orders.sum(net_total, month, A2, counts_as_sale, TRUE)

Net sales per month. List the months with =list.orders(month) in column A and the net sales beside each one.

=data.orders.avg(total, counts_as_sale, TRUE)

Average order. Average order total over the orders that count as sales.

=data.order_lines.sum(quantity, product, A2, counts_as_sale, TRUE)

Units sold per product. Quantity per product from the order lines. List the products with =list.order_lines(product).

=data.orders.sum(net_total, country, A2, counts_as_sale, TRUE)

Sales by country. Net sales per billing country in column A.

=data.orders.count(id, status, A2)

Orders per status. How many orders are awaiting payment, awaiting fulfillment, shipped, completed and so on. Put a status in A2.

=data.order_lines.sum(total, brand, A2, counts_as_sale, TRUE)

Sales per brand. Line totals per brand, from the order lines. List the brands with =list.order_lines(brand).

=data.orders.sum(net_total, channel_id, A2, counts_as_sale, TRUE)

Sales per storefront. Net sales per channel, for stores that sell on several storefronts. Put a channel ID in A2.

=data.products.count(id, stock, "<5")

Low stock. Products with fewer than five in stock.

=data.buyers_from_orders.count(e_mail, orders, ">1")

Repeat buyers. Buyers, guests included, with more than one order.

Build it on your own data

Orders, refunds, products, customers and coupons become live tables inside your BigCommerce control panel. Sales reports and dashboards stay current without exporting a CSV.