The Kano Model block helps you identify which product features truly matter to users — and which are just “nice to have.” The Kano method classifies features based on how their presence or absence affects user satisfaction.
What is the Kano Model block used for?
What is the Kano Model block used for?
The Kano Model helps you understand which features users consider essential, which ones improve satisfaction, and which ones you can safely deprioritize. It highlights what is critical for launch, what can differentiate your product, and what you can cut without harming the experience.
Each respondent is asked two questions per feature:
Functional question: How would you feel if you did have this feature?
Dysfunctional question: How would you feel if you did NOT have this feature?
How features are classified
Based on all responses, each feature falls into one of the Kano categories:
01 Must-be features — Basic expectations. Users take them for granted, and their absence causes strong dissatisfaction.
02 One-dimensional features — The better these features are implemented, the more satisfied users feel. More = better.
03 Attractive features — Delightful “wow” features. Users don’t expect them, but having them significantly boosts satisfaction.
04 Indifferent features — These have little to no impact on user satisfaction.
05 Reverse features — Features users actively dislike. The more you add, the worse the experience.
How to create a Kano Model task?
How to create a Kano Model task?
01 Add instructions
Give respondents context about the product and why you’re evaluating features. For example:
“We’re building a task-management app and want to understand which features are most important to you.”
02 Add features to evaluate
For each feature, you can define:
Feature name (e.g., “Dark Mode”)
Optional description — a short explanation if the name may be unclear
Optional media — image, GIF, or video to illustrate the feature
You can add up to 15 features and enable randomization to avoid order bias.
What is in the Kano Model report?
What is in the Kano Model report?
Your report includes two sections: Feature Priority and Response Distribution.
01 Feature Priority
A table summarizing the evaluation of each feature:
Category — the dominant Kano category (Must-be, One-dimensional, Attractive, Indifferent, Reverse)
Better (%) — Satisfaction coefficient, showing how much satisfaction increases if the feature exists
Formula: (Attractive + One-dimensional) / (Attractive + One-dimensional + Must-be + Indifferent)
Worse (%) — Dissatisfaction coefficient, showing how much satisfaction drops if the feature is missing
Formula: −1 × (One-dimensional + Must-be) / (One-dimensional + Must-be + Attractive + Indifferent)
Priority — an automatically generated recommendation based on both coefficients. Examples:
“High priority — 72% of users would be dissatisfied without this feature.”
“Medium priority — could deliver a positive wow-effect to 68% of users.”
“Low priority — users are largely indifferent to this feature.”
02 Response Distribution
A visual breakdown of how users categorized each feature (Must-be, One-dimensional, Attractive, Indifferent, Reverse).
Methodology: how Kano analysis works
Methodology: how Kano analysis works
The Kano method uses a classification table that maps the pair of answers (functional + dysfunctional) to a category:
Like | Expect | Neutral | Tolerate | Dislike | |
Like | Q | A | A | A | O |
Expect | R | I | I | I | M |
Neutral | R | I | I | I | M |
Tolerate | R | I | I | I | M |
Dislike | R | R | R | R | Q |
Legend:
A = Attractive
M = Must-be
O = One-dimensional
I = Indifferent
R = Reverse
Q = Questionable
Example:
If a respondent answers “I’d really like this” for the functional question and “I could live without it” for the dysfunctional one, the feature is classified as Attractive.
For each feature, we determine the dominant category and compute the Better/Worse coefficients.
Questionable answers are excluded from coefficient calculations and shown separately.
Tips & tricks
Tips & tricks
01 Optimal number of features
We recommend testing 5–7 features at a time. Evaluating more than 10 may cause fatigue and reduce answer quality. If you have many features, split them into several Kano blocks.
02 Keep descriptions clear
Use simple, straightforward language. If the feature name could be unclear, add a short description.
03 Segment your audience
Different user groups may perceive the same feature differently. For example, beginners may consider something a Must-be, while advanced users find it Indifferent.
04 Repeat the study periodically
User expectations evolve. What was Attractive a year ago may become Must-be today (e.g., Dark Mode). A refresh every 6–12 months is a good practice.
05 Combine with other blocks
After Kano, you can ask follow-up questions using the Question block, such as:
“What other features would you like to see in the product?”
This often uncovers ideas users haven’t mentioned yet.