Classify features with the Kano model
Ask functional and dysfunctional questions, classify features as must-be, one-dimensional, attractive or indifferent, and use the Better and Worse coefficients.
Not all features affect satisfaction in the same way. Customers do not praise a hotel for having clean sheets, but they leave angry if the sheets are dirty. They do not expect a free upgrade, but they are delighted when they get one. The Kano model (Kano et al., 1984) captures these asymmetric effects and helps product teams decide what to build.
The five categories
- Must-be (M): basic expectations. Their absence causes strong dissatisfaction, but their presence goes unnoticed. Example: order tracking.
- One-dimensional (O): performance features. More is better, less is worse. Example: free delivery.
- Attractive (A): delighters. Their presence raises satisfaction, but customers do not miss them when absent. Example: an augmented reality try-on.
- Indifferent (I): customers do not care either way.
- Reverse (R): customers prefer not to have the feature.
The questionnaire
For each feature, ask two questions with the same five answers (I like it, I expect it, I am neutral, I can tolerate it, I dislike it):
- Functional: “If the app offers live chat with an adviser, how do you feel?”
- Dysfunctional: “If the app does not offer live chat with an adviser, how do you feel?”
The combination of the two answers maps onto a category through the Kano evaluation table. For example, “I like it” plus “I dislike it” is one-dimensional; “I expect it” or “I am neutral” plus “I dislike it” is must-be; “I like it” plus “I am neutral” is attractive. Contradictory combinations (liking both presence and absence) are classed as questionable (Q) and point to misunderstood questions.
Classify features with the Kano model
- The example has functional and dysfunctional answers for eight e-commerce features.
- Read the category of each feature and the Better and Worse coefficients.
- Look at the Better-Worse plot.
Reading the example
| Feature | Category | Better (CS+) | Worse (CS−) |
|---|---|---|---|
| Free delivery | One-dimensional (67.5% O) | .83 | −.81 |
| Loyalty points | One-dimensional (67.5% O) | .85 | −.79 |
| Order tracking | Must-be (63.7% M) | .25 | −.85 |
| Easy returns | Must-be (62.5% M) | .20 | −.79 |
| Live chat | Attractive (73.1% A) | .79 | −.03 |
| AR try-on | Attractive (68.8% A) | .75 | −.05 |
| Gift wrapping | Indifferent (85.6% I) | .10 | −.01 |
| Dark mode | Indifferent (82.5% I) | .14 | −.03 |
Better and Worse coefficients
The category with the most answers can hide a split audience. The customer satisfaction coefficients (Berger et al., 1993) summarise the whole distribution. Better = (A + O) / (A + O + M + I) is the share of customers whose satisfaction rises if the feature is present; Worse = −(O + M) / (A + O + M + I) is the share whose satisfaction falls if it is absent. Order tracking has a Worse of −.85: leaving it out would disappoint 85% of customers, but adding it raises satisfaction for only 25%. Live chat is the reverse: Better .79, Worse −.03.
From categories to a roadmap
- Fix must-be features first. Without order tracking and easy returns, nothing else matters.
- Compete on one-dimensional features. Free delivery and loyalty points are where better performance pays off proportionally.
- Add attractive features to differentiate. Live chat and AR try-on can delight at a time when competitors do not offer them.
- Skip indifferent features such as gift wrapping and dark mode, or offer them cheaply.
Kano dynamics
Categories change over time: today’s delighter becomes tomorrow’s expectation. Mobile apps, contactless payment and free returns all moved from attractive to must-be within a few years. Repeat Kano studies periodically, and segment the results: a feature can be attractive for one segment and indifferent for another.
Key takeaways
- Ask a functional and a dysfunctional question per feature.
- Must-be features prevent dissatisfaction; one-dimensional features scale with performance; attractive features delight.
- Use Better and Worse coefficients to see the full distribution behind each category.
- Prioritise: must-be, then one-dimensional, then attractive; skip indifferent features.
Check your understanding
Answer each question to see the explanation. Finishing the quiz marks this lesson as complete.