The Kano Model provides a framework for assessing how various features of a product will satisfy customers. This information can be used in R&D efforts to determine which features should be prioritized for development or improvement. At its most simplified, the Kano Model classifies each feature into the following four categories.

Categories

• Attractive — also referred to as exciters or delighters, these are unexpected features that increase the attractiveness of the overall product. Their absence does not hurt perception because they are not expected, but their presence will have an impact.
• Performance — these features are directly related to overall satisfaction, and how well they perform matters. The better this feature functions, the more satisfaction with the overall product. Likewise, poor performance or absence reduces satisfaction.
• Must-have — similar to performance features, these are expected by consumers. There will be dissatisfaction and disappointment if this feature is not present. However, these features are considered basic table stakes and do not increase excitement.
• Indifferent — these features are neither attractive nor unattractive. Their presence or absence has no impact on whether a consumer is satisfied or dissatisfied.

To determine which category each feature belongs to, two questions are asked:

1. How would you feel if the product INCLUDED this feature?
2. How would you feel if the product DID NOT INCLUDE this feature?

Responses are captured on a 5-point satisfaction scale. The discrete method for analyzing the results uses a counts analysis to determine each feature's category.

The Continuous Method

The continuous method categorizes each feature while also providing a visualization that reveals the relative differences among all tested features. To accomplish this, the 5-point scales are recoded to weight satisfaction more strongly than dissatisfaction and align their direction such that a more positive score indicates more desire for inclusion.

Scoring

These scores are then averaged for each question and plotted on a chart to identify its classification. The upper right quadrant is where most features will fall and is the portion displayed in your report. If a feature falls in one of the other three quadrants, its category will be identified but will not be visible on the chart.

• Questionable features are those where responses were conflicting, suggesting either a mutual dislike for including and excluding, or a mutual like of including and excluding. For these items, review how the question was worded — it may have been confusing to respondents. Using satisfaction anchors rather than "I like it" / "I expect it" may reduce the number of questionable features because they better capture the ordinal nature of the scale.
• Reversed features are those where there is a preference for not including the feature. If the questions were worded properly upon review, this could provide useful insight into features that users may find problematic.