Kano Analysis

A method introduced by Noriaki Kano in 1984 for grouping product features by their impact on customer satisfaction: exciters/delighters, performance features (satisfiers), basic expectations that cause dissatisfaction if missing (dissatisfiers), and indifferent attributes that do not affect satisfaction.

Key Points

  • Classifies features into four groups: Exciters/Delighters, Satisfiers (performance), Dissatisfiers (must-be), and Indifferent.
  • Guides prioritization by focusing on what most increases customer satisfaction for the effort invested.
  • Customer satisfaction is non-linear: adding basics rarely increases satisfaction, while delighters can create outsized positive reactions.
  • Categories shift over time as markets mature; validate via customer research (e.g., Kano questionnaires with functional/dysfunctional pairs).

Example

In backlog refinement for a mobile app, the team runs a Kano survey. Biometric login is classified as a Delighter, faster load times as a Satisfier, GDPR compliance as a Dissatisfier (must-be), and custom color themes as Indifferent. The product owner prioritizes must-be and performance items first, then schedules the delighter for an upcoming release.

PMP Example Question

A product owner wants to prioritize features based on how each one influences customer satisfaction, recognizing that some basics prevent dissatisfaction, some improve satisfaction proportionally, and a few create unexpected delight. Which technique should the team use?

  1. MoSCoW prioritization
  2. Kano Analysis
  3. RICE scoring
  4. Pareto analysis

Correct Answer: B — Kano Analysis

Explanation: Kano Analysis classifies features as delighters, satisfiers, dissatisfiers, or indifferent to understand and prioritize by their effect on customer satisfaction.

AI for Project Managers — Build Plans Faster, Lead Better

Turn messy inputs into structured project plans in minutes. If you are a project manager tired of spending hours on documentation, this course shows you how to use AI to work faster while staying fully in control.

This is not a generic AI course. You will learn how to use AI as a practical co-pilot to build real project artifacts—charters, WBS, schedules, risk registers, and executive reports—using structured, reliable prompt frameworks.

You will also learn how to keep your project aligned across scope, schedule, cost, and risk, and how to interpret performance data like Earned Value Management to support better decisions and communication.

Everything is designed for immediate use. You get ready-to-use prompt templates and workflows you can apply right away in your projects. Watch the video to see how it works and start building your first AI-supported project plan.



Launch your career!

HK School of Management provides world-class training in Project Management with AI and Agile Methodologies. Just for the price of a lunch you can transform your career, and reach new heights. With 30 days money-back guarantee, there is no risk.

Learn More