There's been a lot of research looking at the psychology of waiting. You can learn more about how to manage your customers' perceptions of waiting in our article about that. Here we'll discuss some of the research on providing wait times, and why you should strive to do so.
I was in a restaurant this past weekend where the host said that they do not quote wait times. They wouldn't even tell us how long their waitlist was. I was blown away!
The wait ended up being only 20 minutes, but we were very close to leaving because we had no idea how long it would be.
When your list is 100 people long and the wait might approach 2 hours, I have a lot of sympathy for the people managing the queue. Coming up with a quoted wait time in real time without the help of a queue management system is almost impossible. But when you've got about 4 names on the list? You should try!
Here's why.
Providing Wait Time Estimates Reduces the Average Wait
This seems counter-intuitive. Simply providing a wait time estimate can reduce the average wait? How?!
Well, a study looking at banking call centers found that providing wait time estimates led to lower average wait times for all customers.
Every time someone decided to give up their spot in line, it shortened the wait time for everyone else. When estimated wait times were long, this prompted some customers to abandon the line. But when wait times were short, like during non-peak hours, customers were less likely to abandon the line (as compared to when no wait time estimates were provided and customers had no idea how long the wait was, even if it was short).
This reduced the overall average wait time while keeping the total number of customers served constant. Just by providing these estimates – both when the wait is long and when it's short – companies can improve the waiting experience for everyone.
Your Quoted Waits Should Be Pessimistic
This shouldn't come as a surprise to any restaurant host that quoted a 30-minute wait and then was confronted by angry guests after 35 minutes. Expectations matter.
However, there's another reason it may be beneficial to provide a pessimistic wait time estimate: this can weed out less-patient customers who are likely to abandon their spot in line eventually anyway.
If capacity limitations mean that you won't be able to serve all customers, then more pessimistic estimates upfront will quickly eliminate the customers with less tolerance for waiting, speeding up the queue and improving the experience for everyone. Plus, these less-patient customers are likely to return at a time when you're less busy.
Again, in the same bank call center study, researchers examined the impact of quoting a wait time on both of the above. They found that actual waits that were shorter than expected had only a small positive impact on the customer experience. Waits that were longer than expected had a significantly negative impact on customer experience, however.
This suggests that service operations should generally avoid providing optimistic wait-time estimates. Although an optimistic estimate may reduce upfront abandonment rates, that boost isn't worth the negative experience customers will have when they end up waiting longer than expected. If the estimate is just slightly pessimistic, it's unlikely to increase the abandonment rate, and the pleasant surprise when their wait is faster than expected will have a significant positive impact on the overall customer experience.
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You Should Provide Frequent (or Real-Time) Updates
It's definitely better to provide a marginally pessimistic estimated wait time than no wait time at all, but it's even better if you provide frequent updates.
In a physical line, it's very obvious when you're making progress because you keep moving closer to the front. In a virtual queue, however, this isn't the case.
From a study with a major ridesharing provider, researchers were able to quantify just how much better it is to provide wait time updates.
In their study, they analyzed customers who received a more pessimistic initial wait time estimate and (by definition) received more frequent updates for a given wait length. They found that these customers experienced faster perceived progress and so canceled their rides at a lower rate.
As long as the initial estimate is not too pessimistic, the positive impact of more frequent updates offsets any increase in immediate abandonment that occurs as a result of the longer initial estimate.
Just as in the call-center study, this suggests that slightly pessimistic wait-time estimates are better than optimistic ones — although if wait-time estimates are too pessimistic, the net abandonment rate may rise.
Customers That Wait Longer Than Expected Take Longer Than Average
In an unexpected finding of another study with call center data, customers who waited longer than the expected wait time ended up also spending longer on the call once they were connected. This may be because customers who were forced to wait longer than expected spent more time complaining, or felt the need to ask for additional services in order to justify the extra time spent waiting.
If people take longer to be served after waiting longer than they expected, it's yet another reason to ensure your wait time estimates are on the pessimistic side.
If you provide more pessimistic estimates, your customers will take less time being served, which increases your operation's overall total throughput.
Of course, all of this hinges on your ability to make accurate wait-time estimates. Improving your ability to estimate actual wait times is therefore a worthwhile investment, and one a queue management system can help with.