How does the Daasity Data Model differ from Shopify?

What are the key difference between the Daasity Data model and the Shopify Data Model?

Daasity Data Model

Daasity’s data model has been designed to deliver a customer based data set that can be used for powerful analysis. It’s important to understand how the data model treats certain elements as it will be different from how your data may appear in Shopify, which uses a financial accounting methodology. 

Order Status Logic

Daasity uses a concept of Valid Orders in all Order Explores and Dashboards. Certain orders should not be included in calculations as they are orders that ultimately don’t apply to the customer—even if they did at one time. 

The following Order Status are considered Invalid Orders and automatically have all units and amounts set to zero: 

• Cancelled Order 

• Fraud Order 
• Voided Order 
• Full Gift Card Purchase 
• $0 Order

Gift Cards

From an accounting perspective, Gift cards need to be considered a liability until they are used at which point the sales of items purchased using the gift card can be recognized as revenue.  In order to support Gift Cards, we utilize 4 different Order Statuses to describe the usage of Gift Cards: 

• Partial Gift Card Purchase – indicates that the order contained a Gift Card as an item but also contained other items in the purchase.  This is a VALID order however we only consider the non-gift card items in the sales metrics. 
• Full Gift Card Purchase – indicates that the order only contained a Gift Card.  This is an INVALID order. 
• Full Payment All Gift Card – indicates the purchase of non-gift cards items was made only using a Gift Card. 
• Full Payment Partial Gift Card – indicates that purchase of non-gift card items was made using a Gift Card and at least one additional payment method (i.e. more than one payment method was used to make the purchase)  

Frequently Asked Questions on Sales Metrics 

We hear questions from customers—especially from Finance and Accounting—around why numbers may not match other reports. It is all based on having a data model built around customers rather than accounting procedures. There is a place for both in every business.  

Q: Why do gross sales in Daasity/Looker not match Shopify? 

A: Daasity has changed our gross sales calculation to match with Shopify's definition.  If you see a difference between Daasity and Shopify, first check the following:

• Are you comparing across the same date ranges?  Note that the date range in Daasity is NOT inclusive of the end date that you specify while Shopify likely is inclusive of the end date you specify.
• Are you filtering out any orders in Daasity or Shopify?

If you still see a difference please contact support@daasity.com. 

Q: Why do Refunds not match Shopify? 

A: Daasity provides you with two separate sales explores that have two different methodologies.  The first is the Transactional Sales Explore.  For both Pro and Growth customers this explore will match exactly with the data that you see in the Shopify UI.

The second explore is the Order & Order Line Revenue Explore.  This explore uses a more customer-centric approach to order logic and many order and revenue metrics in this explore will not match with Shopify.  

For example, an order is placed on Jan 1 for $50; this order is recorded as being placed on Jan 1. On Jan 2, it is returned for a full refund. A new "transaction" is created on Jan 2 for the refund that cancels out the previous amount you thought you received in revenue. This revenue reversal will be counted—from a financial accounting view—to have occurred on Jan 2.  

In a customer data model, order activities are tied to the customer and orders are only counted if they are Valid Orders. When the order is returned, that is an alert to our data model that the order never should have happened in the first place. Therefore, the data model will set the values associated with that order to 0 and no longer count that order to have occurred on Jan 1.  

So in this example you will see the following in these two explores:

The Order & Order Line Revenue explore is designed this way to facilitate the most accurate Customer Lifetime Value calculation.  With a transactional based model you might end up with Lifetime Value curves that went down in specific periods instead of up.