Kano model
Also called Kano analysis, Kano survey, Kano questionnaire
A way to sort product features by how people feel when a feature is there and when it is not: must-have, performance, attractive or indifferent.
Each feature is asked about twice, once as present and once as absent, on the same five answers: I like it, I expect it, I am neutral, I can live with it, I dislike it. The pair, not either answer alone, places the feature. Disliking its absence while merely expecting its presence marks a must-have; liking its presence while not minding its absence marks an attractive feature; liking one and disliking the other marks a performance feature, where more is simply better.
Read the whole distribution, not only the largest category. A feature split between must-have and indifferent is telling you that two groups of users want different things. The satisfaction and dissatisfaction coefficients summarize the pull in each direction, from 0 to +1 and from 0 to −1, and leave reverse and questionable pairs out of their denominator.
Categories drift. Today's attractive feature is tomorrow's expectation once competitors ship it, so a Kano study describes one audience at one time.
Worked example
40 pairs for offline mode: 18 must-have, 10 performance, 6 attractive, 6 indifferent. Satisfaction is (6 + 10) ÷ 40 = 0.40; dissatisfaction is −(18 + 10) ÷ 40 = −0.70: losing it would hurt more than having it pleases.
Where it goes wrong
Vague feature descriptions. People answer about what they imagine, and two respondents imagining different things produce a split that looks like a finding.