How To Use The Retail Calendar

The Calendar view in Daasity offers you a powerful way to look at period-over-period performance

Key Topics

• Why Use a Retail Calendar
• How to Use the Pivots in Looker
  
  • Pivot by Today
  • Pivot by Yesterday
  • Pivot by Retail Week
  • Pivot by Month
  • Pivot by Retail Month
  • Pivot by Quarter
  • Pivot by Year
  • Pivot by Retail Year
• Compare Custom Date Ranges

Why Use a Retail Calendar?

Depending on your sales channel, sales may not be even across every day of the week due to varying dates between different months and years. Historically, this has made it difficult to compare year over year sales until the 1940s, when the use of a retail calendar became common.

The retail calendar allows you to compare sales across different time periods to help measure performance in a more dynamic fashion, and potentially predict sales based on historical trends. Retail calendars are constructed with four quarters with 91 days in each, in either a 4-5-4 or a 4-4-4 format (i.e. a month with 4 weeks followed by a month with 5 weeks and finally a month with 4 weeks). This ensures that every month has the same number of weekends as the same month in the prior year, so that sales for the same comparable time period have the same number of weekdays and weekends. Additionally, the National Retail Federation (NRF) uses a 4-5-4 calendar and adjusts the start of the calendar year to ensure that major holidays are reflected in the same time period for proper comparisons.

The Daasity retail calendar (shown as the "Calendar" view in most explores) follows the NRF calendar dates shown in the link above.  Along with the NRF calendar structure, this view contains a number of pivot dimensions that allow you to compare data from different timeframes.

 

How to Use the Pivots in Looker?

0 - Pivot by Today

The Pivot by Today dimension allows merchants to see performance for Today compared to Yesterday and (or) Today Last Year. First, filter on the Pivot by Today dimension and select "is not null" in the filter field.  This will remove the dates that are not today, yesterday, and the same day last year.

Second, pivot the Pivot by Today dimension. 

Finally, pick the measures you want to view in your comparison. In the screenshot below we picked Total Gross Sales as an example. Note that the data under Today Last Year is based upon our retail dates comparison, which means it doesn’t simply go back 1 year from Today , but looks for the day last year that has the same retail week number and day of week as of Today.  Generally this will match up the same days of the week and will match up holidays from this year with holidays from last year.  In other words, our example below isn't comparing 3/24/2022 with 3/24/2021, it is comparing it with 3/25/2021 as this is the same retail week number and day of week as 3/24/2022.

 

1 - Pivot by Yesterday

If merchants want to see the performance of Yesterday (This Year) compared to the same day last week (labeled as This Yesterday Last Week) and (or) the same day last year (labeled as This Yesterday Last Year (Last Year)), this filter would be the best choice for them. The steps are the same as the Pivot by Today filter:

1. Filter on Pivot by Yesterday dimension is not null, so as to remove the dates that are not in the comparison.
2. Pivot the Pivot by Yesterday dimension.
3. Pick the metrics you want to compare on, in the screenshot below, we pick Total Gross Sales as an example.

Again, generally this will match up the same days of the week and will match up holidays from this year with holidays from last year.  In other words, our example below isn't comparing 3/23/2022 with 3/23/2021, it is comparing it with 3/24/2021 as this is the same retail week number and day of week as 3/23/2022.

2 - Pivot by Retail Week

Used to compare the current retail week with last week and the same week last year.  Use the same steps from above to use this dimension (filter for Is Not NULL, pivot this dimension, then add the measures you want).  The data will show you current week results WTD (i.e., through yesterday unless you are using the Shopify Hourly Explore which will be through today), vs last week through the same number of days and same week last year through the same number of days.  So if today is Thursday, results from the Order & Order Line Revenue explore will show this week through Wednesday, last week through last Wednesday, and the same week last year through that Wednesday.

Note that "Retail Week" starts on a Sunday and ends on a Saturday in the NRF and Daasity calendar.  

3 - Pivot by Month

This filter uses the same methodology as the filters above, but shows data for the current month vs last month and vs the same month last year.  Again, results are shown through the last complete day of this month vs the same number of days last month and the same month last year.

Note that This Month Last Year is based upon a calendar dates comparison NOT a retail month, which means it looks back 1 year from This Month.

4 - Pivot by Retail Month

This filter uses the same methodology as the filters above, but shows data for the current month vs last month and vs the same month last year.  Again, results are shown through the last complete day of this month vs the same number of days last month and the same month last year.

Note that This Month Last Year is based upon a retail dates comparison, which means it looks for the month with the same retail month number and day of month as This Month.  A retail month often does not begin on the 1st day of the month so this comparison will often use very different days than the Pivot by Month comparison.

5 - Pivot by Quarter

This filter uses the same methodology as the filters above, but shows data for the current quarter vs last quarter and vs the same quarter last year.  Again, results are shown through the last complete day of this quarter vs the same number of days last quarter and the same quarter last year.

Note that This Quarter Last Year is based upon calendar dates, NOT retail dates which means it looks back 1 year from This Quarter.

6 - Pivot by Year

This filter uses the same methodology as the filters above, but shows data for the current year vs last year.  Again, results are shown through the last complete day of this year vs the same number of days last year.

Note that Last Year is based upon calendar dates comparison, which means it looks back 1 year from This Year.

7 - Pivot by Retail Year

This filter uses the same methodology as the filters above, but shows data for the current year vs last year.  Again, results are shown through the last complete day of this year vs the same number of days last year.

Note that in this dimension, This Year is based upon a retail dates comparison, which means it looks for the year with the same retail year number and day of year as This Year.  A retail year often does not begin on the 1st day of January so this comparison will often use very different days than the Pivot by Year comparison.

 

COMPARE CUSTOM DATE RANGES

Below the Calendar view is a Calender - Compare to Previous view that allows you to compare data across custom time periods.

 

To use this feature:

1. Specify a period for comparison in the 'This Period' filter
2. Add 'Comparison Periods' dimension into the table
3. Filter 'Comparison Periods' to return relevant results
4. At minimum, filter for 'is not null'
5. Possible values for this dimension are 'This Period', 'Previous Period', and 'Previous Year'. So filter for whichever comparison you're trying to provide
6. Add a measure for comparison
7. Hit RUN

The “Comparison Periods” dimension has custom sorting logic so that when you sort them Descending, the order will be:

1. This Period
2. Previous Period
3. Previous Year

As an example, if This Period filter is set to 3/8/2022 - 3/15/2022 (exclusive), Comparison Periods will be:

1. This Period: 3/8/2022 - 3/14/2022
2. Previous Period: 3/1/2022 - 3/7/2022
3. Previous Year: 3/8/2021 - 3/14/2021