There were times when companies designed products without even considering how their customers felt about them. Their idea was that product performance was the single driver of customer satisfaction.
That idea is still around. But you, as a designer, instinctively know that there is more to customer satisfaction than mere product performance. There is a more subjective aspect to it. Something that lives in the mind of the customer.
If you want to integrate the subjective factor of customer satisfaction in your product decision-making, the Kano model is for you.
The Kano model is a theory and method to determine how customers perceive product or service features. It helps you prioritize features by their impact on customer satisfaction.
The model is mature, popular and easy to apply. It takes as much time and effort as you are willing to put into it. Even with little effort, its results are already valuable.
You can do a Kano study for any type of product or service. It’s been used on projects ranging from the redesign of a complete airline service to deciding what features to include in an Android app.
The theory and the method
The Kano model was developed in the 1980s by Dr. Noriaki Kano, a Japanese professor and business consultant.
His theory is that there are two factors that determine how customers perceive product features. One the one hand, there is the feature’s performance: how well it works. Performance is more or less objective.
But there is also a subjective factor. That factor determines whether and how a feature’s performance influences customer satisfaction.
Kano developed a method to combine these two dimensions that determine perceived quality into a set of 5 categories:
Must-be features: when customers expect a feature just like they expect the sun coming up each morning, that feature is categorized as a Must-Be feature. The performance of the feature has little impact on customer satisfaction (customers are merely “not dissatisfied”), except if the feature is underperforming or absent (then they are dissatisfied). Think of the brakes of a car, for instance.
One-dimensional (or Perform): known as “the-more-the-better”-features. Customer satisfaction and dissatisfaction are in direct relation to the feature’s performance. Car mileage is a good example: the farther you can drive with a full tank of fuel, the more satisfied you’ll be (and vice-versa).
Attractive. Also known as Delighters. Satisfaction with features of this category is dependent on their presence and not on their performance. Absence creates no dissatisfaction, presence leads to satisfied customers.
Indifferent: when customers do not care about a feature, it’s categorized as an Indifferent. Presence as well as absence have no impact on satisfaction or dissatisfaction, and neither does performance.
Reverse features are features whose presence and better performance invokes dissatisfaction, while their absence and lesser performance generates satisfaction. In short, when customers hate a feature, its category is Reverse.
Consider a service like Dropbox and some of its features:
Must-be Automatic syncing of files across devices Customer attitude: Not dissatisfied if present, dissatisfied if absent One-Dimensional Part of storage is free Customer attitude: Performance contributes to satisfaction, lack of performance to dissatisfaction. Attract Automatic creation of photo albums Customer attitude: Satisfied if present, but not dissatisfied if absent Indifferent Files can be sorted by filename length Customer attitude: Neither performance nor presence have impact on satisfaction Reverse Files are automatically deleted after 30 days Customer attitude: The less, the better
The category of a feature determines what you should be doing with it.
It’s for example no use improving the performance of a Must-Be feature. It will not increase the customer’s satisfaction. But a one-dimensional feature needs all the effort you can allocate to it: the better its performance, the more satisfied your customers will be. These are typically the features products compete on.
So when you know a certain feature is a Must-Be feature and your competitor doesn’t, guess who’ll be spending too much time and effort into something that does not contribute to customer satisfaction?
For the features used in the Dropbox example above, the categories are predictable.
Or are they? You may think Dropbox users are not interested in sorting files by the length of their filenames. But they might like that feature for a reason you never thought of. Never assume!
“What gets us into trouble is not what we don’t know. It’s what we know for sure that just ain’t so.”
― Mark Twain
There’s only one way of eliminating assumptions: asking your customers. The beauty of the Kano method is that it is not only a theory, but also a very practical way of collecting customer input to categorize features.
Surveying customers to categorize product attributes
To know how customers perceive the quality of product features, Noriaki Kano developed a specific survey format and evaluation method.
For each feature, customers answer how they feel about that feature’s presence (or performance) and how they feel about its absence (or underperformance). For each question, their answer must be one of:
I like it
I take that for granted1
I don’t care
I can live with it
I dislike it
Let’s say you’re building a voice-controlled TV. In order to save costs, you are considering leaving out the remote control. But of course, you wonder how customers will react to that. This is how you ask them using the Kano survey format and how one customer may have answered:
The TV comes with a remote control o I like it * I take that for granted o I don’t care o I can tolerate it o I dislike it The TV does not come with a remote control o I like it o I take that for granted o I don’t care o I can tolerate it * I dislike it
The customer’s answer is then evaluated with a lookup table:
Like Expect Neutral Accept Dislike
Like Q A A A O
Expect R I I I
Neutral R I I I M Accept R I I I M Dislike R R R R Q
The surveyee in the example expects the remote control’s presence (row 2) and dislikes its absence (column 5). According to the evaluation table, this makes the feature a Must-Be feature.
(The Q-category stands for “Questionable”, indicating the response makes no logical sense. You cannot like that the TV comes with and without a remote at the same time, for instance).
Of course, you shouldn’t take one customer’s response as the basis for your decisions. Determining the category is done by tallying all responses.
A survey with 80 customers could result in the feature being a Must-Be feature as the majority of answers categorize it as such:
Feature M P A I Q | Result Remote control 54 12 8 4 2 | Must-Be
Now you know you should not throw out the remote control. Customers will think of your new TV model as incomplete if it doesn’t have a remote.
The Kano model is an easy enough method to get started with, but there’s a lot hidden under its surface.
You are probably already wondering how to interpret less clear-cut results than the one in the example given. And are you allowed to change the survey format or the answer labels? How should your questions be worded? What’s the best way of doing a survey?
I’ll be sharing more of my experiences and research here. I’m also writing a full guide to the Kano model that explains things in more detail. I’ve put some parts of that guide online for you to read, share and add your comments and questions to.
People who have read about the Kano model earlier may find this one a bit surprising. I’ll explain the wording in a later post.