Automated Penalty Reward Analysis (Kano Factors)

Penalty Reward Analysis (also known as Kano Factors) is used to investigate the type of relationship between an outcome and features used in a Key Driver Analysis. The goal is to understand how an increase or decrease in the performance of a driver will impact the outcome, allowing us to optimize actions for improving the outcome.

quantilope's Penalty Reward Analysis is fully automated, allowing users to drag and drop the method into their survey instantly and watch results in real-time. 


Benefits of quantilope's automated Penalty Reward Analysis: 

  • Statistically sound results with the click of a button
  • Easy to understand visualizations with clear recommendations for action

Applications of quantilope's Penalty Reward Analysis

What characteristics are ‘must-haves’ for the use of a product?

'Automatic categorization' and 'money transfer' are must-haves for using the Banking App.

Are there features that customers do not expect but that would excite them?

Having an overview of 'all accounts at a glance' excites users, but the lack of this feature is not decisive for the intention to use the app.

Additional automated methods

Total Unduplicated Reach and Frequency (TURF)

Learn more

Maximum difference scaling (MaxDiff)

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Key Driver Analysis

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Request an Automated Penalty Reward Analysis Demo