Kano Model Analysis Tool
Enter your Kano survey answers for each feature. The tool classifies them with the standard table and shows the majority category and the better and worse coefficients.
RICE = Reach x Impact x Confidence / Effort. Switching method keeps your ideas and the other method's numbers.
Ranked by RICE score (0)
No ideas yet. Add one on the left, or start from the example.
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Four steps to a Kano analysis.
- 1
List the features
Add the features you want to test.
- 2
Ask two questions
How would you feel if it was there? How would you feel if it wasn't?
- 3
Enter the answers
Add counts, or paste one respondent per line.
- 4
Read the result
Each feature gets a category and its coefficients.
FAQ
What is the Kano model?
A way to sort features by how they affect satisfaction. Must-be features are expected, so nobody thanks you for them but everyone notices when they're missing. Performance features give more satisfaction the better they are. Attractive features delight people who didn't expect them. Indifferent features change nothing either way.
What is the Kano questionnaire?
For each feature you ask two questions: "How would you feel if the product had this?" and "How would you feel if it didn't?" The answers are the same five each time: I like it that way, I expect it that way, I'm neutral, I can live with it, I dislike it that way. Each pair of answers maps to one category in the Kano evaluation table.
How are the better and worse coefficients worked out?
Better is (Attractive + Performance) divided by (Attractive + Performance + Must-be + Indifferent). It shows how much adding the feature could lift satisfaction. Worse is the same count with Performance and Must-be on top, shown as a negative. It shows how much leaving it out could hurt. Reverse and Questionable answers are left out of both.
What if the answers are split between categories?
The category shown is the one with the most answers. On a tie the tool picks Must-be first, then Performance, Attractive and Indifferent, and marks it as a tie. A lot of Questionable answers usually means people misread the question, so check the wording. How many people you need depends on how mixed your users are, so treat a small sample as a hint, not proof.
Can I use it for several respondents?
Yes. Add each answer pair with a count, or paste one respondent per line, such as "like, dislike". Your list is kept in this browser and shared with the RICE, ICE and MoSCoW modes. Log in to save it, or download a CSV.
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