Does this skill conduct the actual user surveys?

No, it assists in designing the functional/dysfunctional questionnaires and analyzes the resulting data provided by the user.

Can I use this for small sample sizes?

Yes, but the skill will flag the results as 'MEDIUM' confidence for 5-8 respondents, noting that 20+ respondents are required for statistical significance.

What is a CS Coefficient?

CS (Customer Satisfaction) coefficients consist of 'Better' and 'Worse' scores that quantify the extent to which a feature increases satisfaction or prevents dissatisfaction.

UX Kano Model Prioritizer

Name: UX Kano Model Prioritizer
Author: geekatron

bygeekatron

•

Herramientas de Diseño

Classifies and prioritizes product features using the Kano methodology to identify essential requirements and customer delighters.

The UX Kano Model skill provides AI-augmented feature classification to help product teams understand which capabilities satisfy, delight, or frustrate users. Based on the Kano et al. (1984) methodology, it categorizes features into Must-be, Performance, Attractive, Indifferent, and Reverse types using functional/dysfunctional questionnaire pairs. It goes beyond simple listing by calculating Customer Satisfaction (CS) coefficients for priority matrix visualization and providing survey design templates. This skill is essential for moving from subjective backlog debates to evidence-based roadmap decisions, calibrated by respondent sample size for statistical confidence.

Características Principales

01Feature lifecycle analysis to track migration from 'Delighter' to 'Table Stakes'

02Calculation of Customer Satisfaction (CS) coefficients (Better/Worse) for priority mapping

03Confidence calibration based on sample size (directional vs. statistical classification)

04Generation of functional/dysfunctional survey design templates for team administration

05Automated classification into Kano categories (Must-be, Performance, Attractive, etc.)

0616 GitHub stars

Casos de Uso

01Resolving stakeholder disagreements on feature value with a structured, evidence-based framework

02Prioritizing a product backlog by identifying which features provide the most satisfaction impact

03Analyzing user research data to identify unique 'delighters' that differentiate a product from competitors

Características Principales

01Feature lifecycle analysis to track migration from 'Delighter' to 'Table Stakes'

02Calculation of Customer Satisfaction (CS) coefficients (Better/Worse) for priority mapping

03Confidence calibration based on sample size (directional vs. statistical classification)

04Generation of functional/dysfunctional survey design templates for team administration

05Automated classification into Kano categories (Must-be, Performance, Attractive, etc.)

0616 GitHub stars

Casos de Uso

01Resolving stakeholder disagreements on feature value with a structured, evidence-based framework

02Prioritizing a product backlog by identifying which features provide the most satisfaction impact

03Analyzing user research data to identify unique 'delighters' that differentiate a product from competitors