Something struck me while I was reading a recent Kano study on transportation services1. One of the questions in the study was:
How would you feel if clear information were provided about the transportation services?
How would you feel if the information about the transportation services were unclear?
At first, I wondered why this question was in the study. Surely, nobody would not want information to be unclear? Why would they include such an obvious feature?
It’s not about the feature, it’s about its category
I’m sure everyone at the transport company would agree that clarity of information is a necessary attribute of their service.
But then the next question is: when is it clear enough? Is it even ever clear enough? Should the company invest in mobile apps, an open API, integrations with Google Maps, more ubiquitous signage?
Will customers be satisfied as long as their expectations are met? Or will their satisfaction keep increasing the more the transport company invests in providing clear information?
So it’s not about asking whether a certain attribute is desirable or not. It’s about how that attribute determines customer satisfaction.
That’s why “clarity of information” was in the Kano study.
If clarity of information turns out to be a must-be attribute of the transport service, customers will be happy when their expectations are met, but they won’t get happier above that level of clarity. Good enough will be good enough.
But if clarity of information turns out the be a one-dimensional attribute of the service, customer satisfaction will increase together with the degree of clarity. The more, the better.
Knowing a service attribute’s Kano category helps you make the right decisions. This knowledge helps the transport company decide how much effort to allocate to providing clear information.
If good enough is good enough for the customer, investments above a certain level would not contribute to higher customer satisfaction. Effort would be better spent elsewhere.
On the other hand, if information clarity is a case of “the more, the better”, the transport company will have to continuously invest in increasing clarity of information. Matching expectations would not be enough.
Don’t dismiss the obvious
When you’re thinking of excluding a feature from your Kano study, don’t look at how obvious the feature is.
Instead, think about how obvious its category is. More often than not, you won’t be able to tell, and you’ll want to ask your customers to be sure.
Chen, Mu-Chen, Chia-Lin Hsu, and Chun-Han Huang. "Applying the Kano model to investigate the quality of transportation services at mega events." Journal of Retailing and Consumer Services 60 (2021): 102442.