Back in October, we released our list of the Top 10 Busiest Shopping Days of 2016. Now, it’s time to revisit the list and our holiday retail observations to see how well our predictions held up.
Top 10 as predicted:
As you can see, we correctly predicted all 10 days but flipped the order of the Friday and Monday bookending Christmas (12/23 and 12/26) and reversed the order on the first Saturday of December (12/3) and the last Thursday before Christmas (12/22). Together, these 10 days accounted for nearly 44% of the total season’s brick-and-mortar traffic, which is very similar to the percentage from the top 10 traffic days in 2015.
As you can see from the graph below, Black Friday surpassed all other shopping days! In fact, though many other organizations predicted that Super Saturday, 12/17, would steal the show, Super Saturday’s in-store traffic was only about half as busy as Black Friday (Super Saturday came in at #4). Some may blame this on the unusually cold weather we experienced nationally that week, but as we described in an earlier post on the impact of weather on Super Saturday, we can only reasonably attribute a 7% drop in traffic to the poor weather.
There is only one significant reason that Super Saturday did not rank #1 in store traffic: tradition. After observing in-store traffic for as many years as we have, it’s become clear that shoppers prefer to visit stores on Black Friday more than they do on any other day. Black Friday shopping is a tradition that hasn’t changed and is unlikely to lose its luster in the near future, regardless of others’ enthusiasm for last-minute shopping predictions.
As we suggested in several of our holiday blog posts, there is a definite pattern in holiday shopping traffic, which the below graphic indicates. Since the 2017 season aligns fairly closely with 2012 and includes a fourth Saturday in December, we can already predict that it will be one of the top days for next season, but will still easily fall short of Black Friday 2017. (Bookmark this post and review it again next year!)
While overall seasonal traffic trends were down 6-7% year-over-year, the good news is that sales-per-shopper trends were up 2-3.5%. Sales-per-shopper is the product of conversion multiplied by average transaction size (ATS) and represents how well a store performs, regardless of customer traffic trends. We consider this to be a measurement of a store team’s service effectiveness in taking care of their customers. Since conversion rates were relatively flat YOY, the increase in sales-per-shopper comes primarily from ATS. This ATS upswing throughout 2015 could be due to a couple of factors, for example:
- With traffic down, shoppers are proving to be more prepared and more selective when they are ready to purchase – and they are willing to accept either a higher average price per item, or the addition of extra merchandise upon check out
- Retailers are providing a great in-store experience and exceptional products that counter the impact of reduced visits
When you dive a little deeper and contrast the top 10 days of 2016 with the overall season, a couple of other trends stick out:
- Year-over-year traffic was down slightly, yet more on days that fell outside of the top 10
- Year-over-year sales-per-shopper levels were also up on days that fell outside of the top 10
It’s natural to assume that, since the top 10 days accounted for 44% of the traffic, higher traffic drove the sales-per-shopper differential. However, when you consider how stores allot labor hours, it’s more likely to have been a result of staffing opportunities on the top days.
This can be broken down as follows:
- STAR is the difference of shopper traffic divided by labor hours and measures the effective service level the store is providing to shoppers — the lower the ratio, the higher the service level.
- Shopper-to-Associate Ratio (STAR) was favorable to last year in both the top 10 days and for the overall season.
- But the STAR was actually lower outside of the top 10 days, which may account for both lower service levels and lower store selling effectiveness as measured by Sales-per-Shopper.
Planning both merchandise availability and staffing levels around the highest traffic shopping days will pay off with continual improvements in sales-per-shopper, regardless of year-over-year store vs. web traffic trends.