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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  1. Applying your Kano study results
  2. Prioritizing features

Prioritising by the value of a feature's presence and the cost of its absence

A visual way of showing priorities

Last updated 9 months ago

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Categories help you understand how to strategize about your product, but in terms of prioritising it's still just a list of features with a category attached to it. Sometimes you'll want to make things more visual and telling, especially when features are in the same category.

One way of doing so is by using Mike Timko's . As a reminder, value of presence = A+OA+O+M+IA+O \over A+O+M+IA+O+M+IA+O​ and cost of absence = - O+MA+O+M+IO + M \over A + O + M + IA+O+M+IO+M​

Let's use an example where all features are in the Attract category:

Feature
M
O
A
I

A

2

24

53

21

B

27

20

46

7

C

18

28

38

16

Calculating the value and cost turns this table into:

Feature
Value of presence
Cost of absence

A

0.55

-0.26

B

0.73

-0.47

C

0.56

-0.46

And this can then be easily visualised in a graph:

Prioritise by cost or value?

If you look at the previous graph, it's pretty clear why feature B is ranked highest: the value of its presence is highest, and the cost of its absence is highest too (albeit with a tiny difference of 0.01 with the feature C). The same applies to feature C: the value of its presence is just a bit higher than feature A's, and the cost of its absence is higher too.

You will however run into analyses where the ranking is not that clear cut. Consider this result:

Feature
M
O
A
I
Value of presence
Cost of absence

A

23

24

32

21

0.55

-0.47

B

5

7

71

17

0.78

-0.12

C

52

28

18

2

0.46

-0.80

Should you prioritise feature B, because its value when present is highest of all three features? Or should you prioritise feature C, because the cost of its absence is higher than that of the other features?

The answer is C. As one researcher (Chen, 2021) puts it:

to ensure customer satisfaction, it is vital to do away with customer dissatisfaction.

The final ranking is therefore:

Use this rule of thumb when sorting features based on their value of presence and cost of absence:

  • Feature with the highest cost of absence first;

  • When tied: feature with the highest value of presence.

Reverse features are not part of this calculation. You should to develop a positive counterpart.

Consider the negativity effect; the "notion that even when of equal intensity, things of a more negative nature have a greater effect on one's psychological state" (). In other words, not having something weighs heavier than having something. Customers feel worse when they miss something than when that something is available.

re-examine Reverse features
Wikipedia
Cost-Value or Better-Worse analysis