Customer wait time is one of the most reliable leading indicators of customer satisfaction in retail because, well, customers don’t like to wait. And if they do have to wait, they express the opposite of satisfaction.
As banks reduce their branch staff levels, customer wait times are likely to increase, which is a negative influence on customer satisfaction unless the problem is addressed. The problem for bankers is that overstaffing their branches increases operational expense. How do you get the balance right?
Essentially, the challenge for retail banks is twofold. First, how do you staff the branch throughout the day, week and month to provide a consistent wait time experience for customers that is within the bank’s target service level? Second, how do you know if your goal is being achieved? How should you measure and monitor customer wait time?
It’s not just actual wait time that matters in customer satisfaction. The other two factors affecting customer satisfaction with wait time are perceived wait time and expected wait time. Studies have shown that perceived wait time – the amount of time a customer thinks they have waited – goes up rapidly after the expected wait time is surpassed. The difference between expected and perceived wait time is an important factor in understanding customer satisfaction.
Another complication: some customers are more concerned about wait time than others. For example, people living in a retirement community are typically less concerned about wait time than people living in a metropolitan area. So, for metropolitan branch customers who are time-sensitive, perceived wait time is a better indicator of customer satisfaction than the actual wait time. In general, however, actual wait time has the largest impact on customer satisfaction.
Balancing Trade-offs
In Kiran’s Branch Transformation Survey conducted between March and June of 2015, retail bankers were asked what they thought was the maximum time customers would wait for service and still consider it a positive experience. For service interactions, 82% of respondents said five minutes or less. For sales interactions, 62% said five minutes or less, with 92% indicating 10 minutes or less.
Retail bankers might assume that if customers walking into a branch are satisfied with a five-minute wait time, they would be delighted with a three-minute wait time. However, does the cost of overstaffing to achieve this service level necessarily justify the benefit?
Each bank’s retail delivery strategy drives their target service level. Setting and managing service levels becomes the act of balancing trade-offs between customer satisfaction and operational costs. Retail banks can optimize wait time using a three-step approach and advanced analytics:
- Set a target service level with a wait time metric. For example, a target service level of 90/5 means 90% of customers will not wait more than five minutes.
- From strategic to tactical to operational, the next steps involve predicting customer arrivals and work content, aligning branch resources with work content to achieve the target service level and optimizing staff scheduling.
- Finally, to manage service levels on an on-going basis, monitor on-the-ground service levels based on actual staffing and the variability of customer demand. This is where Wait Time Analytics (WTA) can help.
WTA uses advanced analytics and queuing methodology to accurately determine whether on-the-ground service levels for each branch in the entire network exceeded the target service level, met the target, or did not achieve the target on an intra-day basis. WTA utilizes tracked transaction data from the electronic teller and platform systems, actual number of frontline staff servicing customers and time standards.
Alternative methods for estimating and monitoring wait times have significant shortcomings over an analytics-based approach. Customer surveys and mystery shopper studies are not strong predictors of customer wait times for the whole network because they use small samples. Video image processing and lobby management systems can provide an accurate measure of customer wait time, but at a very high cost.
Best practices for managing customer wait experience include effective lobby leadership. For customers waiting in the lobby, managing their perceived wait time is the most important thing. With effective lobby leadership, a customers expected wait time can be properly set so that the perceived wait time is within the limits of a customer’s willingness to wait and still be satisfied.
For customers waiting for service or sales interactions, managing the actual wait time is the most important action. Hiring, training, and retaining the right people are keys to success with reducing variability in service and sales activity times, which in turn minimizes actual customer wait times.
Finally, proper branch staff training is important. Customer migration to digital channels can be accelerated by training branch staff to intercept, redirect, and assist customers to effectively use self-service and agent-assisted technologies in the branches.
Optimizing customer wait times across the entire branch network and monitoring them with wait time analytics can create a competitive advantage. Banks that can consistently hit their service level targets are more likely to improve customer satisfaction and customer loyalty.
Mr. DeLapa is CEO with San Diego, Calif.-based Kiran Analytics. He can be reached at [email protected].
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