Optimizing staff productivity through footfall analytics

Sharp focus on staff productivity and service level intensity has a vital role in improving service quality and enhancing conversion for retailers who want to boast store efficiency. Footfall data, also known as people counting data, has now made it easier than ever for the retailers to assess the strengths and weaknesses of their stores when it comes to staff performance. . This includes knowing the peak and off-peak times to avoid over/under staffing and lowering the burden on staff to always keep their morale high.  

Some of the key performance indicators used to assess staff productivity are: VPSH (visitor per staff hour), TPSH (transaction per staff hour) and RPSH (revenue per staff hour).  

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VPSH (Visitor per staff hour)

VPSH allows retailers to optimize the service intensity in stores as they gauge the number of visitors served by each staff member on an hourly basis. This metric helps in adjusting staff requirement according to peak hours such that if the number is high, a need for more staff is determined and if the number is low, additional staff can be reassigned.  

Footfall analytics solutions present in the SaaS market such as Shopper Value further add insights to footfall analysis through store-wise trends and comparisons for an overall network health analysis of retail chains.  

Find out how Khaadi optimizes store performance through footfall data.

TPSH (Transaction per staff hour)

Transactions per staff hour is another important KPI to gauge the level of transactions being closed by the sales staff on an hourly basis. This, coupled with traffic, transactions, and sales gives retailers a sharp insight into profitability generated staff productivity.  

RPSH (Revenue per staff hour)

RPSH can be used to analyze the revenue generated through sales per staff hour. This is not just a strong indicator of the staff’s ability to sell high value products but also helps identify opportunities to cross-sell and up-sell.  

People counting and footfall data have now become pertinent when it comes to gauging and improving staff productivity in retail stores.

Analysis of the key performance indicators on staff productivity allows retailers to ensure all store visitors are attended to by their staff in the best conceivable way. Through the right data, retailers can make sure that their stores have the right strategies in place to manage the influx of visitors and minimize lost sales and revenue