The 12 Days of Christmas - A look at pre-Christmas retail sales patterns

During a recent tenure at a national sporting goods retailer, I was bewildered by the increased Marketing spend in the final days leading up to Christmas after witnessing limited spend between Black Friday and then.  Based upon my experience (robust sample, I know, but hold on), buying decisions for the most part had been made significantly earlier than the week of Christmas, and last minute shopping would not be enough to save the season for this retail category.  This prompted me to examine our actual seasonal sales (Black Friday through Christmas) and understand how those sales were actually realized.  This resulted in a result so sompelling that our BI team published it for our business partners/customers.

The 12 Days of Christmas

As you all know, the sales season spanning from Black Friday to Christmas Eve (period referred to as Christmas season for remainder of this document) is the most important time of year for retailers.  While everyone understands the impact of Black Friday, it’s interesting to note that on average, 53% of the season’s sales happen in the last 12 days leading up to Christmas (51% if 2008 is removed). 

Week after week we look at daily comp sales, and have a pretty good idea what sales might be in the coming days and weeks. 

See typical 15 day period below:

However, in the days leading up to Christmas, this method of gauging performance is problematic showing large swings which may or may not reflect the existing sales trend.

See 15 day period including Christmas below:  Christmas (red circles)

 

So the question that we wanted to address is,

Given the volatility in year over year comparisons during this period, is there a way to stabilize our observations and develop a reliable prediction methodology for this period of time?

Upon analyzing 6 years of data, a surprisingly simple pattern began to unfold.  During the 12 days preceding Christmas, we identified 3 buckets of time (number of days) with similar sales proportions i.e. percentages of the seasons total sales volume.  Specifically, we found that on average ~17.5% of sales occurs in the 3 day period prior to Christmas, ~18.8% of sales occurs during the 4 day period preceding the 3 day period, and ~16.7% occur in the preceding 5 day period, hence the name, 3-4-5 Rule.  It’s a rule that helps us to better understand some of the ‘when’ and ‘how much’ questions that become critical to answer during holiday sales. 

See illustration below:

On Average, each bucket will account for 17.5% (+/- 1%) of the Holiday Season’s Total Sales.  Despite the study being based upon 6 years, the below illustration is using only 2 years:

·         3 days of sales leading up to Christmas (22^nd to 24^th)

·         4 days of sales preceding the 3-day bucket (18^th to 21^st)

·         5 days of sales preceding the 4-day bucket (13^th to 17^th)

So what does this all mean?  Well, it can help us to have a better picture of where our sales will end up as soon as December 12^th.  By then, we know that we have roughly 50% of seasonal sales revenue has been accounted for with expectations for 16% - 18% in the next 5 day window and 16% - 18% in the following 4 day window and 16% - 18% in the final 3 day window prior to Christmas.

This approach allowed us in BI to predict that Total Company Sales vs. LY for Period 11 would finish around -1.38% (actual Period results were -1.2%) despite seeing total company sales comp on December 20th at -12.9%.  IT also showed that the increased spend in the final days leading up to Christmas was not impacting our top line sales as history had shown that the realized pattern over history was similar regardless of spend in these final days.