Measuring the Effect of Queues on Customer Purchases

Find the best tradeoff between customer service capacity and pricing by calculating the extent to which long lines affect sales and revenue.
August 23, 2011
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The Idea

Find the best tradeoff between customer service capacity and pricing by calculating the extent to which long lines affect sales and revenue.

The Research

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.

Practical Applications

Customer service managers, operations managers

You can use this research to estimate how service levels are likely to affect customers’ willingness to wait in line before abandoning a purchase and the how much they are willing to pay for products given how long their wait in line is. To compensate for lost revenue from perceived long waiting times, retailers would have to increase prices. The researchers’ field test found that increasing the number of customers waiting in line from 5 to 10 was equal to a 3 percent price increase, whereas increasing the line from 10 to 15 was equivalent to a 10 percent price increase, suggesting that beyond a certain threshold of line-length, the impact on the customer is much larger.

You can also use this research as a tool for customer segmentation. The researchers’ results show that customers who are least sensitive to pricing — those who purchase the most premium items — are also the most sensitive to wait time. Hence, long queues are particularly harmful for the most profitable customer segments.

Marketing managers, retail facility designers

You can use this research to anticipate how your retail operation’s line affects customers’ purchase incidence — whether or not customers end up completing a purchase once they get in line — and their choice to substitute alternate products and services. Results indicate that purchase incidence is mostly affected by the number of customers in line, not by staffing levels or the speed at which the line moves. You can also use this research to aid decisions about presenting promotions, planning the physical layout of checkout stations, and managing the experience of customers waiting in line to minimize the perception that they will experience a long wait.