In the retail world, the peak traffic hours are the ones with more store visits. Those hours in a week would always occur at the same time as peak selling hours. In reality, however, even high-performing retailers will have difference between the two group of hours. These differences make sense because at the end the sales and conversion rate depend largely on the amount of sellers we have in store and their skills when the visitants go in.
It is certain that some sales will be lost if we have no the correct number of sellers and with the adequate skills when the largest number of store visits are received.
“Peak Exceptions” are calculated when you compare which hours in a week were peak sales hours, but not peak traffic hours, and vice versa.
Within the top 20 open hours, a high-performing retailer will have an average of 1.5 Peak Exceptions per store per week, whereas a retailer who executes less effectively may have as many as 4.5 Peak Exceptions per store per week. The higher this number is more reflect the loss of opportunities.
Specialty retailers typically achieve 50% or more of their weekly sales in the 20 top sales open hours per week. That’s half of your sales in a quarter of your hours.
The 20 peak traffic hours and peak sales hours also present store teams with the largest single opportunity to change their results. This means that retailers have a big opportunity to improve their results if they manage correctly these peak hours.
Having predictive visibility to when these peak hours will occur for each store is an essential component of effective scheduling strategies in order to increase the sales.
The three focus items that store managers should be looking to achieve here are:
In order to archive these items the following capabilities are crucial:
Fortunately the state-of-the-art in data analytics has made great progress in recent years, and now, for each one of these required capabilities there are advanced analytics that can help tremendously. Reviewing each one:
Retailers who are not collecting the value can bring their data and these analytical techniques are missing a great opportunity to improve their results.
The customer experience is the deciding factor that will separate the winners from the losers. Consistently producing an environment that creates a positive customer experience starts with combining smart staff scheduling and precise sales and traffic predictions.
Putting both the right number of employees and your best performing employees on the selling floor during peak periods will have the biggest impact on your results.