Complete firstClear scope
Agree the subject, boundary and decision before filling the model.
A broad or mixed scope produces a misleading model.
Method guideProduct Discovery
Kano Model
A practical method guide: clarify prerequisites and materials, understand the complete process, and look up outputs, pitfalls, and stop criteria.
ComplexityMedium
Time1-2 Tage
Participants10-50
FormatWorkshop + async
MaturityEstablished
01
Prerequisite
What needs to be finished first
Complete firstAccess to relevant evidence
Bring source material and people who know the work; distinguish facts from assumptions.
Unverified interpretations become false certainty.
02
Preparation
What needs to be ready before start
Materials
Shared visual workspace, source evidence, and an agreed decision question.
People / roles
Researcher, representative respondents, product decision-maker, analyst.
Pre-read
Collect existing data, examples, constraints and relevant stakeholder perspectives.
Time needed
Several days or weeks for recruiting and responses; allow 60–90 min for classification.
Setup
For each individual feature ask two questions: response if it is present (functional) and response if it is absent (dysfunctional). Use the same five answers: like it; must be that way; neutral; can live with it; dislike it. Classify each pair with the evaluation table as Attractive, One-dimensional, Must-be, Indifferent, Reverse or Questionable; then report frequencies and segments.
03
Core question
The one question this method answers
How does each feature affect satisfaction when present or absent?
04
Flow
Phases with goal, actions, output and pitfall
Classifies product attributes by how their presence and absence affect customer satisfaction, using paired questions.
Response-pair matrix
Example responses per feature
Record both answers from the same respondent for each feature; then classify them using the Kano evaluation table.
| Feature and response pair | Feature | Functional | Dysfunctional | Category |
|---|---|---|---|---|
| Response pair 1Record one respondent’s answers for one feature | Reschedule online | Like it | Dislike | O · One-dimensional |
| Response pair 2Record one respondent’s answers for one feature | Choose reminder time | Like it | Neutral | A · Attractive |
1. Feature
- Response pair 1
- Reschedule online
- Response pair 2
- Choose reminder time
2. Functional
- Response pair 1
- Like it
- Response pair 2
- Like it
3. Dysfunctional
- Response pair 1
- Dislike
- Response pair 2
- Neutral
4. Category
- Response pair 1
- O · One-dimensional
- Response pair 2
- A · Attractive
The matrix records each respondent’s functional and dysfunctional answer together. The canonical A/O/M/I/R/Q evaluation table appears in the method example.
- 1
Features
Select individual attributes
Goal
Atomic attribute list
Inputs for this step
- Product options and relevant customer segments
Actions
- Break concepts into attributes respondents can evaluate independently and understand consistently.
Output
Atomic attribute list
Atomic attribute list
Quality check
Does each item contain one feature?
Pitfall
Feature bundles make answers ambiguous. Split bundles and test question comprehension.
Timing: Allow time according to scope and evidence; no universal duration.
- 2
Functional
Ask functional questions
Goal
Functional answer per respondent and feature
Inputs for this step
- Attribute wording and consistent answer scale
Actions
- For each attribute ask how respondents feel if it is present. Use the same five options: like it; must be that way; neutral; can live with it; dislike it.
Output
Functional answer per respondent and feature
Functional answer per respondent and feature
Quality check
Is the positive question neutral and clear?
Pitfall
The question exaggerates or obscures the benefit. Neutralize wording and make the scenario concrete.
Timing: Allow time according to scope and evidence; no universal duration.
- 3
Dysfunctional
Pair dysfunctional questions
Goal
Complete answer pairs
Inputs for this step
- Same attributes and unchanged response scale
Actions
- Ask the mirrored question for the feature’s absence; keep both answers paired for each respondent.
Output
Complete answer pairs
Complete answer pairs
Quality check
Does every functional answer have its paired question?
Pitfall
The second question asks importance instead of absence. Ask explicitly how they feel if the feature is not present.
Timing: Allow time according to scope and evidence; no universal duration.
- 4
Analysis
Apply evaluation table and inspect spread
Goal
Category distribution with uncertainty
Inputs for this step
- Answer pairs, Kano table and segment data
Actions
- Classify each pair as A/O/M/I/R/Q, aggregate frequencies and investigate Q, reverse, ties and segments.
Output
Category distribution with uncertainty
Category distribution with uncertainty
Quality check
Are distributions shown rather than only the winning class?
Pitfall
A small sample is presented as general preference. Report sample and segment; plan targeted research.
Timing: Allow time according to scope and evidence; no universal duration.
05
Artifact
What comes out at the end
Sketch: what the artifact looks like
Form
Classifies product attributes by how their presence and absence affect customer satisfaction, using paired questions. Record scope, evidence, assumptions, owner and next review in the versioned artifact.
Versioning / ownership
Record scope, date, participants, source version and owner. Note changed assumptions and the reason for each revision.
Tool alternatives
- Shared whiteboard or paper template
- Source links, records or measurement data
kano-working-template.md
Prepare the decision, source evidence and next review.
Kano Model: Worksheet
Question
To be confirmed
Desired outcome
To be confirmed
Scope
Run the method Time: See catalog planning range; no universal duration.
Complete this worksheet on paper or in your own document during the work.
Preparation for this scope
Method setup
- Materials: Shared visual workspace, source evidence, and an agreed decision question.
- Roles: Researcher, representative respondents, product decision-maker, analyst.
- Advance information: Collect existing data, examples, constraints and relevant stakeholder perspectives.
- Overall time needed: Several days or weeks for recruiting and responses; allow 60–90 min for classification.
- Setup: For each individual feature ask two questions: response if it is present (functional) and response if it is absent (dysfunctional). Use the same five answers: like it; must be that way; neutral; can live with it; dislike it. Classify each pair with the evaluation table as Attractive, One-dimensional, Must-be, Indifferent, Reverse or Questionable; then report frequencies and segments.
Prepare for the work steps
Features: Select individual attributes
- Product options and relevant customer segments
Functional: Ask functional questions
- Attribute wording and consistent answer scale
Dysfunctional: Pair dysfunctional questions
- Same attributes and unchanged response scale
Analysis: Apply evaluation table and inspect spread
- Answer pairs, Kano table and segment data
Response-pair matrix
| Feature and response pair | Feature | Functional | Dysfunctional | Category |
|---|---|---|---|---|
| Response pair 1 | ||||
| Response pair 2 |
- Response pair 1: Record one respondent’s answers for one feature
- Response pair 2: Record one respondent’s answers for one feature
Keep each respondent’s paired answers together. Do not replace this evaluation with a feature popularity score.
Attractive Quality and Must-Be Quality · Kano et al. (1984)
Features: Select individual attributes
Expected artifact: Atomic attribute list
Atomic attribute list
Entry:
...
- Does each item contain one feature?
Functional: Ask functional questions
Expected artifact: Functional answer per respondent and feature
Functional answer per respondent and feature
Entry:
...
- Is the positive question neutral and clear?
Dysfunctional: Pair dysfunctional questions
Expected artifact: Complete answer pairs
Complete answer pairs
Entry:
...
- Does every functional answer have its paired question?
Analysis: Apply evaluation table and inspect spread
Expected artifact: Category distribution with uncertainty
Category distribution with uncertainty
Entry:
...
- Are distributions shown rather than only the winning class?
Open questions and next steps
...
Method guide: https://methodatlas.meierhoff-systems.de/en/methods/kano/run-sheet
06
Example output
Concrete filled scenario, fictional example
Fictional example for orientation. Counts and timings describe this case and are not universal requirements.
kano-beispiel.md
Concrete filled scenario, fictional example
Kano evaluation table
Rows show the functional question (feature present); columns show the dysfunctional question (feature absent). Each respondent uses the same answer scale for both: like it, must be that way, neutral, can live with it, dislike it.
| Functional \ Dysfunctional | Like it | Must be | Neutral | Can live with | Dislike |
|---|---|---|---|---|---|
| Like it | Q | A | A | A | O |
| Must be | R | I | I | I | M |
| Neutral | R | I | I | I | M |
| Can live with | R | I | I | I | M |
| Dislike | R | R | R | R | Q |
Legend: A Attractive · O One-dimensional · M Must-be · I Indifferent · R Reverse · Q Questionable. Fictional result example: “reschedule online” could yield 5 O, 3 M, 2 A, 1 I and 1 Q across twelve fictional responses. This small example is not representative; inspect responses per person and segment.
07
Pitfalls
Recognize symptoms and steer against them
Quick overview, the full text is in the matching phase in the flow
- Select individual attributesFeature bundles make answers ambiguous.View in phase
- Ask functional questionsThe question exaggerates or obscures the benefit.View in phase
- Pair dysfunctional questionsThe second question asks importance instead of absence.View in phase
- Apply evaluation table and inspect spreadA small sample is presented as general preference.View in phase
Trap
Select individual attributes
Symptom
Feature bundles make answers ambiguous.
What to do
Split bundles and test question comprehension.
Trap
Ask functional questions
Symptom
The question exaggerates or obscures the benefit.
What to do
Neutralize wording and make the scenario concrete.
Trap
Pair dysfunctional questions
Symptom
The second question asks importance instead of absence.
What to do
Ask explicitly how they feel if the feature is not present.
Trap
Apply evaluation table and inspect spread
Symptom
A small sample is presented as general preference.
What to do
Report sample and segment; plan targeted research.
08
Stop criteria
When to pause, resolve prerequisites, or choose another approach
Stop if the decision question or scope is disputed; align it first.
Stop if key inputs are unavailable; list what evidence is needed.
Stop if the group treats assumptions as observed facts.
Finished the method guide?
Go to the profile for purpose, similar methods, and sources or continue to the next method in the catalog.