KANO MODEL ANALYSIS

Build what delights, not what disappoints

Categorize features by their real impact on customer satisfaction, Must-Be, Performance, Attractive, Indifferent or Reverse, using the classic two-question Kano survey. Then focus effort where it moves satisfaction most.

Satisfaction score
42%
Avg customer happiness
Avg implementation
53%
Development progress
Quick wins
1
Attractive, under-built
Must fix
0
Must-Be below expected
3 features categorized
FeatureIf present (functional)If absent (dysfunctional)CategoryImpl.SatisfactionPriority
Attractive
%
%
Exp 70% · -55%
86.2
Performance
%
%
Exp 50% · on track
0.0
Must-Be
%
%
Exp 35% · +25%
0.0
Category distribution
Must-Be1 · 33%
Performance1 · 33%
Attractive1 · 33%
Indifferent0 · 0%
Reverse0 · 0%
Strategic insights
1 quick win availableAttractive features that could delight users with relatively little build effort. Prioritize these for outsized satisfaction gains.
Where to focusGet Must-Be features right first, compete on Performance features, and use Attractive features to differentiate. Don't over-invest in Indifferent features, and watch for Reverse features that some users actively dislike.

What the Kano model measures

The Kano model maps the relationship between how well a feature is implemented and how satisfied customers are as a result. Its insight is that this relationship is not linear and differs by feature type. Some features only cause dissatisfaction when missing and are taken for granted when present. Others scale satisfaction in proportion to how good they are. And a few delight customers out of all proportion to the effort involved. Treating all features the same is how teams pour resources into work that never moves the needle.

The five Kano categories

Must-Be features are basic expectations; their absence causes anger but their presence earns no praise, like a hotel room having a working lock. Performance features satisfy in proportion to how well they are done, the more the better, like battery life. Attractive features delight when present but are not missed when absent, the source of competitive differentiation. Indifferent features move satisfaction either way very little and are candidates for cutting. Reverse features actively reduce satisfaction for some users, meaning more is worse. Knowing a feature's type tells you how much to invest and what to expect in return.

How the two-question survey works

Each feature is evaluated with a pair of questions. The functional question asks how the customer feels if the feature is present; the dysfunctional question asks how they feel if it is absent. Each is answered on a five-point scale from like to dislike. The pair of answers is then read against the standard Kano evaluation table, which maps every combination to a category. This tool runs that mapping automatically, so changing either answer instantly re-categorizes the feature, letting you see how perception shifts the strategy.

Turning categories into priorities

Categorization is the start, not the end. The priority score in this tool weights the gap between expected and actual satisfaction, how much of the feature is already built, and the category itself, so it surfaces the under-implemented Attractive features that represent quick wins and the weak Must-Be features that represent risk. The principle is simple: secure the basics, compete on performance, and spend your remaining innovation budget on a small number of delighters rather than spreading it thin.

From insight to a working roadmap

A Kano analysis is only valuable if it changes what gets built and when. That means the categorization lives where the product team can see it, satisfaction data flows in from real customers rather than guesses, and the output connects to your prioritization and delivery process. Puetto configures the tools, builds the automations, and runs the day-to-day ops that keep customer insight connected to the roadmap, faster than a hire and more accountable than an agency.

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