Retailers and service-intensive firms closely monitor their capacity to balance a high level of customer service with maximizing revenue. Yet most methods of assessing the value of enhanced customer service (such as adding cashiers to make a line move more quickly or splitting waiting customers into several short lines) use customer surveys or similarly subjective methods to provide data about customers’ perceptions of service. Objective measures reflecting the true value of service are more difficult to collect. For example, how much does revenue increase or decrease in response to changes in staffing levels and how many customers are in line?
As part of a broader body of research examining the impact of many aspects of retailers’ customer service on revenue, Professor Marcelo Olivares worked with doctoral candidate Yina Lu, Andres Musalem of Duke, and Ariel Schilkrut of Scopix Solutions to create a method that allows retailers to place a dollar value on increases and decreases in wait times and staffing. The researchers used patented video identification technology to count customers waiting in line and to measure staffing levels at a large supermarket chain’s deli counter, taking a data sample every half hour for six months. They cross-referenced this data with point-of-sales records that track the history of customers’ purchases — the types and quantities of products bought over time — to estimate the impact of the deli queue on revenues.