A McKinsey Quarterly article called Maintaining the customer experience caught my eye. It discusses scenarios where companies were trying to figure out the design point for a couple of customer experiences, one of which was the call waiting time for a call center. Here’s how the article sets up the problem:
Consider service levels, specifically average time-to-answer, which is one of the most common metrics used in call centers. Service levels-often based on regulation or historical precedent-are set by call-center managers and then used to calculate staffing requirements. But service levels are challenging to maintain and costly to improve: raising them by 10 percent requires much more than a 10 percent increase in staff
My take: This is an area where companies can make a lot of costly mistakes if they don’t understand what drives customer satisfaction. So I sent the following comment to the McKinsey Quarterly editors…
Conceptually, the Kano Model does a good job of helping dissect thinking in this area. In particular the model’s focus on three types of attributes: Must-be, One-dimensional, and Attractive.
Must-be attributes need to deliver a minimum threshold of value or the customer will be extremely dissatisfied. But the customer does not notice if that threshold is exceeded. Think about the brakes on a car; you expect them to work, but don’t notice much more than that.
One-dimensional attributes are those that continue to increase the value to customers. Think about price; the lower the better.
Attractive attributes are unexpected aspects of the experience that dramatically increase the value perceived by a customer. Since they don’t expect them, there aren’t any negative consequences if they are not there. Think about a call from the CEO of an airline after you’ve had a service problem; wow, that could make a significantly positive impression.
Using this model, we can better understand the mistake that companies often make about attributes like call waiting times. In most cases, I’d classify call waiting times as a must-be attribute. It’s a problem if the waits are too long, but there’s no lasting perceived value by customers if you shorten them under that threshold. So companies shouldn’t invest in dramatically shortening waiting times, but should figure out how to minimize the number (or impact) of people that experience a wait that goes beyond the threshold.
You may have noticed that offered up the option of either solving the problem (customer who have a wait time above the threshold) or lessening the impact. It may be very expensive to eliminate all customer waiting times that go beyond their must-be threshold. So companies may be better served to try another approach: like an apology from the call center rep or some more substantial service recovery option (maybe even some “attractive” options).
By understanding these differences, companies can focus their energy and investments in the right areas to drive up customer satisfaction. This is particularly important in these times when companies are cutting back; they need to make every investment count.
The bottom line: Figure out what’s must-have, attractive, and one-dimensional.