How do you avoid common pitfalls and biases when using the Kano model?

2 Choose the right method

There are different methods for collecting data for the Kano model, such as surveys, interviews, focus groups, or experiments. Each method has its advantages and disadvantages, depending on your objectives, resources, and context. For example, surveys are efficient and scalable, but they may not capture the nuances and emotions of customers. Interviews are more in-depth and qualitative, but they may be influenced by interviewer bias or social desirability. You need to choose the method that best suits your purpose and ensures validity and reliability.

3 Avoid leading or confusing questions

One of the most common pitfalls of using the Kano model is asking leading or confusing questions that may skew the results. Leading questions are those that suggest a desired answer or imply a judgment, such as "How much do you love this feature?" or "Don't you think this feature is essential?" Confusing questions are those that are vague, ambiguous, or too complex, such as "How do you feel about this feature?" or "What are the benefits of this feature?" You need to ask clear, neutral, and specific questions that elicit honest and accurate responses.

4 Validate and update your findings

Another common pitfall of using the Kano model is assuming that your findings are static and universal. Customer preferences and expectations may change over time, depending on the market conditions, competitive offerings, or technological innovations. What was once a delighter may become a basic feature, or vice versa. You need to validate and update your findings regularly, by conducting follow-up research, testing your assumptions, and tracking customer feedback.

5 Use the Kano model as a guide, not a rule

The final tip on how to avoid common pitfalls and biases when using the Kano model is to use it as a guide, not a rule. The Kano model is a helpful framework for understanding customer preferences and prioritizing product features, but it is not a substitute for critical thinking, creativity, or experimentation. You need to consider other factors, such as your vision, strategy, resources, and constraints, when making product decisions. You also need to test and iterate your features, and measure their impact on customer satisfaction and loyalty.