sc_items

In this article

• Summary
• Supported Use Cases
• When not to use the view

Summary

The sc_items view serves as the repository for information on order line items. In this view, you will find granular information about the items in a given order, including the sku, item price, quantity purchased, and item-level discounts. 

 View Grain: Order Item-level details. Each record should have a unique combination of an order and product identifier. 

• Primary (Composite) Key(s):
  • item_uid
• Foreign Key(s):
  • scid
  • sku

 The scid field can be used as a joining condition with other views in SoundCommerce if those views contain the scid field. Generally speaking, the order_id field may also be used as a joining condition. However, be cautious with using just order_id as different channels may reuse order_id values. The scid takes channel and source into consideration.

Supported Use Cases

The following use cases are examples and only provide a subset of all potential use cases that can be addressed with data found in sc_items and other views. This list should not be assumed to be comprehensive. 

• I am interested in identifying items purchased in a specified time frame by one-time customers.
• I want to understand which items were purchased by customers who have more than 12 months between subsequent orders. 
• I want to identify which items tend to be purchased on discount vs. those purchased at full price. 

When not to use the view

This view contains order item-level data. The order item level is one of the lowest grains supported by SoundCommerce. Therefore, most joins with other, less granular, views in SoundCommerce will force duplication of record-level metric values. A consequence of this is inflated aggregate values.

The sc_items view does not contain specifics about the following:

• Campaign-related metrics (i.e., clicks, impressions, conversions)
• Fulfillment-related metrics (i.e., shipment partner, tracking number, fulfillment breakdown of constituent items)
• Product-related metrics (i.e., warehouse inventory for a given product)
• Customer-related metrics (i.e., customer historical sales, customer CLV)
• Customer PII-related values (i.e., first and last names, emails, phone numbers, addresses)

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