What it is
Kano is a framework for understanding how the presence or absence of a feature influences satisfaction in different ways.
Overview notes
Why it helps
Kano is useful when the business needs a language for feature tiers not just a rank-ordered list.
Decision guide
When to use it
- When feature prioritization is the main question
- When the team needs a more intuitive framework than a utility model
When not to use it
- When trade-offs across multiple attributes need to be modeled formally
Inputs required
- Paired functional and dysfunctional responses
Typical outputs
- Must-have performance attractive indifferent classifications
Simple example
Classify app features to distinguish basic expectations from features that genuinely create delight.
Strengths
- Easy for stakeholders to understand
Limitations
- Less precise than formal trade-off models
Common mistakes
- Treating classifications as fixed across contexts and segments
How I use it in practice
I use Kano when the team needs a fast and intuitive way to organize product features before deeper prioritization work.
What is outputted
- Feature category summaries
How to interpret the output
- Focus on how feature absence versus presence changes reactions
How to communicate to clients
- Explain that Kano is a framework not a market simulator
Displayr / Q implementation notes
- Keep paired-question coding consistent
Mini demo
Kano classification placeholder
A small future demo could classify a feature after choosing functional and dysfunctional responses.
This method is marked as a good candidate for a future teaching demo, but v1 keeps the site lightweight for GitHub Pages.