The complete guide to the Kano model
  • The complete guide to the Kano model
  • Why I wrote this guide
  • A short note on terms used
  • The value of the Kano model
  • The Kano model in a nutshell
  • Step-by-step guide to a Kano study
    • First rule of a Kano study
    • Gathering features
    • Designing your Kano survey
      • The art of formulating good questions
      • More on questions
      • Wording the answers
      • Test your survey
    • Administering your Kano survey
      • In person or online?
      • Selecting survey participants
      • Survey layout
    • Analysing the results of your Kano study
      • Classic Kano survey analysis
      • Continuous analysis
      • Validity and reliability
  • Applying your Kano study results
    • Prioritizing features
      • Prioritising by Kano category
      • Prioritising within categories
      • Prioritising by the value of a feature's presence and the cost of its absence
    • The product development lif
      • Understanding Kano categories to make the right decisions
      • Removing features
      • Identifying areas of improvement
      • The under-utilisation of the Reverse category
      • Disrupting conventions
    • Uncovering customer segments
    • Tracking the life cycle of customer attitudes and product features
      • The life cycle of successful product features
      • Other patterns
      • Customer satisfaction over time
    • Product communication
    • Organisational benefits
      • Objective decision making
      • Product process
      • Resource allocation
    • When not to use the Kano method
  • History of the Kano model
    • Genesis of the Kano model
    • Extensions to the Kano model
    • alternative-kano-methods
    • kano-model-critique
  • Appendices
    • appendix-i-answer-labels
    • appendix-ii-bibliography
  • Deleted
    • Preface
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  • Using the lookup table
  • Tallying the results

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  1. Step-by-step guide to a Kano study
  2. Analysing the results of your Kano study

Classic Kano survey analysis

Last updated 7 months ago

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The original way Noriaki Kano devised to analyse a survey was to use a lookup table to classify each pair of responses per feature and then tally the results:

Using the lookup table

In the classic analysis, you look up the category of the combination of a respondent's functional and dysfunctional answers.

Functional ↓

Dysfunctional →

Like

Expect

Neutral

Accept

Dislike

Like

Q

A

A

A

O

Expect

R

I

I

I

N

Neutral

R

I

I

I

N

Accept

R

I

I

I

N

Dislike

R

R

R

R

Q

Tallying the results

When you have determined the category of each response, tally them up. For each feature, count the number of times they have been attributed the Natural, One-Dimensional, Attractive, Indifferent, Reverse and Questionable categories.

For a survey with 25 respondents, the results could be:

N

O

A

I

R

Q

Feature #1

9

10

1

2

3

0

Feature #2

9

5

4

2

4

1

...

The classic way to determine the final category of the feature is to simply look at what category has the majority. For feature 1, that’d be One-Dimensional. For the second feature, that would be that it’s a Natural.

When you're ready with your analysis, you can begin .

interpreting the results
Source: Kano et al. (1984), translated