Kano Model

The Kano Model was created by Kano Noriaki in 1984 to understand how users perceive the value of certain product capabilities. In this article I just want to provide a quick overview to the methodology. For a detailed reference and different ways to evaluate the results, I recommend The complete guide to the Kano model.

The Kano method helps to answer:

• How do we measure satisfaction?
• How do we understand how our features are perceived by users?
• What features will deliver a wow effect?

With this method it is easy to group features in four categories based on satisfaction and functionality and visualize it as two dimensional graph.

In this article I will not use the original survey analysis but introduce the continuous analysis by William DuMouchel.

The four Kano categories

Indifferent

Indifferent features are those that users don’t care about. They don’t increase satisfaction when present, and they don’t decrease satisfaction when absent.

Must-be

Must-be or basic expectation features are features that are expected by default. If they are missing, users feel frustrated or even betrayed. If those features are there, users will not compliment you, they simple assume that those features should be there. Identifying must-be features is crucial as this helps to understand the minimum feature set you must invest in.

We expect from a phone that we can easily make a phone call. If the interface of a smart phone makes it hard to make simple calls or the device gets frozen, they will simply return the product.

Performance

Performance are the more the better features. Satisfaction rises as performance improves and drops as performance weakens.

How long the battery of your phone lasts under heavy use or how fast the phone charges has a direct impact on satisfaction. The same is true for Wi-FI range and speed, audio quality, etc.

Attractive

Attractive features (delighters or exiters) are features users don’t expect. So, users will not get upset if those features are not there but when they are there, satisfaction jumps exponentially. They create the wow, I did not know the product can do that or hey, that’s nice feeling.

On the wow side, imagine a user in 2007 switching from an old mobile phone to the iPhone 1.0. On the hey, that’s nice side imagine our phone becoming an correct translator on a trip abroad.

Today, a smart phone will not wow us anymore as attractive features become performance or must-be features over time. Kano categories are valid for a certain point in time when the analysis is done.

Kano questionnaire

You can either explain or demonstrate features or run a survey.

• You ask how they would feel if the feature was present (positive or functional question)
• and then ask, how they would feel if the feature would be absent (negative or dysfunctional question).

The participant must provide the Kano rating for each question:

• I like it
• I expect it
• I am neutral (I don’t care)
• I can tolerate it (I can live with it)
• I dislike it

Include a test example at the beginning to explain the ratings.

Prefer experience or showing the features over describing the features. Let us assume, you want to find out the satisfaction of a certain file upload. The closer it will be to the real experience, the better users will be able to provide feedback.

DuMouchel continuous analysis

William DuMouchel has extended the original discrete categorizational analysis. This approach takes the participants responses as continuous values.

DuMouchel assigns a score to each functional and dysfunctional answer and considers reverse results and questionable data. Reverse response indicate that the users want exactly the opposite of what has been proposed. Questionable data refers to invalid or contradictory answers.

Step 1: Map each response to the correct values

Step 2: calculate the averages

Step 2: Map the feature to the graph