> For the complete documentation index, see [llms.txt](https://help.daasity.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.daasity.com/support/faq/when-to-use-order-line-revenue-or-transactional-sales-report.md). # When to use Order Line Revenue or Transactional Sales Report? The two Most-Used Explores Order Line Revenue (OLR) and Transactional Sales Report (TSR) have slight differences. It is important to know which one to use and why. There are many ways to evaluate and look at data. Daasity has always taken **a customer-first approach** to our data model. The majority of Merchants rely upon and are used to Shopify, which has a **modified financial first approach** to how they report sales. In order for you to have the flexibility to view your reporting from either angle, we've made available two separate explores: the **Transactional Sales Report** explore and the **Order & Order Line Revenue** explore ## Transactional Sales Report The [Transactional Sales Report ](/core-concepts/data-models/data-explores/digital-analytics-unified/transactional-sales-report-explore.md)has additional information joined to it, which allows analysis similar to the [Order Line Revenue Explore](/core-concepts/data-models/data-explores/digital-analytics-unified/ecommerce-orders-and-revenue-by-order-date-explore.md). It also will contain all of your Sales Sources, NOT just Shopify. However, whether refunds appear in TSR depends on the integration - see the refunds section below. There are some differences in how Shopify's logic is applied to various elements in an Order, including Shipping Fees, Taxes and Discounts. {% hint style="danger" %} If you see a difference in your OLR and Transactional Sales Report Numbers After still accounting for the differences below - Email - and grant Daasity access to your Partner Portal and We can dig deeper into specific Orders {% endhint %} {% hint style="success" %} The largest delta that is typically noticed is the treatment of Refunded values. {% endhint %} For integrations that provide refund transactions to TSR, the refund is recorded as a separate transaction on the date the refund occurred. This represents the accounting/transactional view of the data. TSR currently carries refund transactions for Shopify, BigCommerce, Target Plus, TikTok Shop, and Walmart Marketplace. This is determined by the integration the data comes from, not the sales channel. For example, a wholesale store that runs on Shopify carries refund transactions in TSR. Amazon and all other integrations are purchase-only in TSR: their refunds do not appear as separate refund transactions. Where refund data is available for these integrations, it appears in the Order Line Revenue Explore, netted back to the original order date. {% hint style="success" %} Use the Transactional Sales Report Explore when you need refunds reported on the date they occurred, for the integrations listed above. {% endhint %} {% hint style="warning" %} If an Order is Edited in Shopify (Manually changed in Shopify, for example by a Customer Service Rep) Shopify will treat this as a New Order and The Transactional Sales Report add another Order Code (Order Line) for this Order. There is NO way to tie these orders back to Daasity. The Order Line Revenue Explore will Make these changes within the Original Order - and Keep the Order as One Line (Order Code). {% endhint %} **Gross Margin in TSR** Gross Margin in the Transactional Sales Report is calculated at the transaction level, designed to mirror Shopify's financial reporting. **Shipping and fulfillment costs** are *not* included in TSR Gross Margin; TSR focuses on pure product-level cost of goods and transactional revenue. Because TSR records sales and refunds on the transaction date, it should be used for **financial reporting or reconciliations** that need to match your sales platform or accounting statements. For integrations that are purchase-only in TSR, such as Amazon, refunds will not be included in these figures. ## Order Line Revenue Explore {% hint style="success" %} Net Sales will NOT match Shopify when using the Order Line Revenue Explore. {% endhint %} The Order Line Revenue explore is based on a **customer-first data model** which ties the Refund back to the order in which the item was purchased. Where refund data is available, the refund is netted back to the original order date rather than reported as a separate transaction on the refund date. This is a typical methodology for Customer level reporting, cohort reports and Lifetime value reporting. **This also allows the item to be mapped back to exactly which items were originally purchased.** {% hint style="success" %} **An order contains 1 row in the database.** The order has various attributes such as Sales, Items, Taxes and Refunds, all connected to that original order. {% endhint %} #### **Gross Margin in OLR** Gross Margin in Order Line Revenue is calculated at the order level, connecting each refund back to the original purchase. OLR includes shipping and fulfillment (3PL/outbound) costs in COGS to provide a full cost view per order. This Explore should be used for customer-level or contribution margin analysis, where the goal is to understand true profitability per order or cohort. #### SKU Cost Precedence (Applies to Both TSR and OLR) Both Transactional Sales Report and Order Line Revenue use the same SKU cost precedence logic. There is no difference in how SKU costs get into TSR and OLR - they both start with UOS (Unified Order Schema). Costs are sourced in the following order: 1. **Shopify** - Initial default source 2. **BSD** - Overrides Shopify when available 3. **Skubana** (or its successor platform) **Note:** We often customize this with NetSuite or other ERP integrations. We typically recommend sourcing costs from your ERP system if you have one, as it provides the most accurate and up-to-date cost data for your business operations. ## Which Explore Should You Use? | | **Transactional Sales Explore** | **Order Line Revenue Explore** | | -------------------------------------------------------------- | ------------------------------- | ------------------------------ | | Reporting on Sales to match Shopify | X | | | Sales that include refunds over a time period, such as monthly | X\* | | | Customer Reporting | | X | | Individual item-level reporting | | X | | Financial gross margin reporting (excludes fulfillment) | X | | | Contribution margin analysis (includes fulfillment) | | X | \*TSR refund reporting is currently available for Shopify, BigCommerce, Target Plus, TikTok Shop, and Walmart Marketplace. Amazon and all other integrations are purchase-only in TSR; where their refund data is available, use Order Line Revenue, which nets refunds back to the original order date. {% hint style="success" %} **The Order Line Revenue Explore has one row *****per SKU***** in an order. The Transactional Sales Report has one line *****per transaction*****.** {% endhint %} In the Transactional Sales Report, a refunded product appears as a separate transaction for the integrations listed above. This makes it more difficult to tease out what actually happened with an order. **It is best to use Order Line Revenue if you are researching one order.** **Note:** Differences in gross margin between the two Explores are by design. TSR is intended to align with Shopify's financial reporting (transaction-level), while OLR is designed for customer-level profitability analysis. The key difference is that OLR includes shipping and fulfillment costs in COGS, while TSR does not. Both Explores use the same SKU cost precedence logic. If you observe GM discrepancies outside these modeled differences, please contact Daasity Support. ## Daasity Valid Order {% hint style="success" %} Shopify considers a Valid Order to be anything that is NOT deleted or a Test Order. The Order Line Revenue Explore matches this definition. {% endhint %} You can use a [“Daasity valid order flag](/support/faq/what-is-a-daasity-valid-order.md)” that Removes any Orders that are cancelled, voided, fraud, and free orders. If you look at unfiltered sales data in Order Line Revenue, that data will include cancelled, fraud, voided, and free orders. You can Use the Daasity Valid Order Flag to remove these.