sc_previous_year_comparison

In this article

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

Summary

The sc_previous_year_comparison view uses the NRF calendar to compare marketing performance metrics across different periods. Pertinent metrics from a previous year, quarter, month, etc., are calculated and associated with the current year, quarter, month, etc.

• View Grain: Order-level transactions.
• Primary (Composite) Key(s):
  • scid
• Foreign Key(s): 
  • order_id
  • cuid
  • campaign_id 
  • order_date 
  • attribution_date

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_previous_year_comparison. This list should not be assumed to be comprehensive.

• I want to understand how my previous (year, month, period, quarter, week, day) compares to the current (time window) regarding campaign, customer, order, or product metrics. 
• I want to ensure that my period-over-period comparisons honor the NRF calendar, not the standard Gregorian calendar. 

When not to use the view

The NRF calendar is built so that comparisons between periods can be standardized. It employs a 4-5-4 configuration for a given quarter (meaning the first month in a quarter has 4 weeks, the second has 5 weeks, and the third has 4 weeks). This view uses the NRF calendar as its basis, so comparing data from this view against the standard Gregorian calendar will likely mislead analysts. 

Years in the NRF calendar generally consist of 52 weeks. There are some years with 53 weeks instead (i.e., 2012, 2017, 2023). These years must still be considered in analysis, but will not have a corresponding prior or future period. Thus, a gap in reporting may need to be accounted for. 

Considering that the same customer might have placed an order in the previous year, the view should be used for something other than granular customer- or order-level comparison. Because logic in this view tries to associate data from previous periods with the current, previous period orders and customers will be associated with the current date. This view is built for aggregate analysis, not transactional analysis.

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