What Is the Kano Model?

The KANO model is a useful tool for the classification and prioritization of user needs invented by Professor Noriaki Kano of the Tokyo Institute of Technology. Based on the analysis of the impact of user needs on user satisfaction, it reflects the non-compliance between product performance and user satisfaction. Linear relationship.

KANO model

Behavioral Scientist

The concept of satisfaction

Consumers' satisfaction is determined by their expectations of the products and services provided by the company, compared with the actual (perceived) effects, and the feelings of happiness or disappointment formed by users. That is, if the actual effect in actual consumption after purchase is in line with the anticipation, then you are satisfied; if you exceed the anticipation, you are satisfied; if you fail to meet the anticipation, then

Noriaki Kano divides the factors that affect satisfaction into five categories, including:

The five quality divisions of the Kano model provide directions for the improvement of Six Sigma.

The KANO model analysis method is a set of structured questionnaires and analysis methods developed by Kisho Kano based on the KANO model's segmentation principle of customer needs. The analysis method of the KANO model is to conduct surveys through standardized questionnaires, classify the attributes of various factors according to the survey results, solve the problem of positioning product attributes, and improve customer satisfaction.

research analysis

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The functions are analyzed from the perspective of the user.

Questionnaire

According to the collected functional analysis and design of the questionnaire, in the design of the questionnaire, the questionnaire should be as clear and understandable as possible, and the language should be as simple and specific as possible to avoid semantic ambiguity. At the same time, you can add short and obvious tips or instructions to the questionnaire. Convenient for users to answer smoothly.

problem	High satisfaction	High satisfaction	Zero satisfaction	Low satisfaction	Low satisfaction
If the product / service has a ** module, your rating is
If the product / service does not have a ** module, your rating is

The respondent only needs to tick the above questionnaire. This questionnaire is divided into two dimensions: satisfaction when provided, satisfaction when not provided, and satisfaction is divided into five, because people's satisfaction is often gradual, rather than abrupt. Modify it with the author, such as (like it, take it for granted / OK / OK, it doesn't matter, barely accept / live it, don't like it) more vivid description.

When sorting out the questionnaires, clean up individual cases of obvious and random answers, such as choosing "I like it" or "I like it all" for all questions.

Two-dimensional attribute attribution classification

		Not provided \ not available
		High satisfaction	High satisfaction	Zero satisfaction	Low satisfaction	Low satisfaction
provide \have	High satisfaction	Suspicious result	Excited	Excited	Excited	Expectation
	High satisfaction	Reverse	Non-differential	Non-differential	Non-differential	Essential
	Zero satisfaction	Reverse	Non-differential	Non-differential	Non-differential	Essential
	Low satisfaction	Reverse	Non-differential	Non-differential	Non-differential	Essential
	Low satisfaction	Reverse	Reverse	Reverse	Reverse	Suspicious result

The above table is just one of the most common methods. For example, the reverse type of demand should be inversely proportional to the degree of satisfaction. That is to say, if you provide, I am not satisfied. If you do not provide, I am satisfied. Only the bottom left corner is a clear reverse type requirement. The others are not clear and can expand the suspicious results. The following table is another method of data classification. At this time, it can vary from person to person, product to company, region to region, and satisfaction itself is difficult to measure.

		Not provided
		High satisfaction	High satisfaction	Zero satisfaction	Low satisfaction	Low satisfaction
provide	High satisfaction	Suspicious result	Suspicious result	Excited	Expectation	Expectation
	High satisfaction	Suspicious result	Suspicious result	Excited	Expectation	Expectation
	Zero satisfaction	Reverse	Reverse	Non-differential	Essential	Essential
	Low satisfaction	Reverse	Reverse	Reverse	Suspicious result	Suspicious result
	Low satisfaction	Reverse	Reverse	Reverse	Suspicious result	Suspicious result

Quantified form

Fill in all reasonable data in the form similar to the above.

It is not difficult to see from the table that each function may have scores on 6 dimensions (charm attribute, expectation attribute, required attribute, non-differentiation factor, reverse attribute, suspicious result), and add the proportions of the same dimension After that, the sum of the proportion of each attribute dimension can be obtained. The attribute dimension with the largest sum is the attribute attribute of the function.

It can be seen from the above table that the function of "information management-purchase behavior information" is a charm attribute. It means that without this function, the seller will not have strong negative emotions, but with this function, the seller will feel satisfaction and surprise.

Or calculate a better-worse coefficient to show the extent to which achieving this factor attribute will increase satisfaction or eliminate dissatisfaction. Better's value is usually positive, which means that if the product provides a function or service, user satisfaction will increase. The larger the positive value, the stronger the effect of user satisfaction, and the faster the satisfaction rises; the value of Worse is usually negative, which means that if the product does not provide a certain function or service, the user's satisfaction will decrease. The larger the negative value, the stronger the effect of reducing user satisfaction, and the faster the satisfaction decreases; therefore, according to the better-worse coefficient, projects with a higher absolute score of the coefficient should be implemented with priority.

A product wants to optimize 5 functions, but don't know which ones are needed by users. Through kano investigation and analysis, the better-worse coefficients of the five functions can be calculated respectively, and the following quartile maps are constructed.

The scatter plot is divided into four quadrants based on the values of the better-worse coefficients of the five functions.

The first quadrant indicates that the value of the better coefficient is high, and the absolute value of the Wors coefficient is also high. Factors that fall into this quadrant are called expectations (one-dimensional factors). Function 5 falls into this quadrant, which means that the product provides this function, and user satisfaction will increase. When this function is not provided, user satisfaction Will decrease

The second quadrant indicates the case where the value of the better coefficient is high and the absolute value of the Wors coefficient is low. The factors that fall into this quadrant are called charm factors. Function 1 falls into this quadrant, which means that this feature is not provided and user satisfaction will not decrease, but when this feature is provided, user satisfaction will be greatly improved. ;

The third quadrant indicates that the value of the better coefficient is low, and the absolute value of the Wors coefficient is also low. The factors that fall into this quadrant are called non-differential factors, and functions 2, 3, and 4 fall into this quadrant, that is, whether these functions are provided or not, user satisfaction will not change. These function points are users Unnoticed features;

The fourth quadrant indicates that the value of the better coefficient is low and the absolute value of the coefficient is high. The factors that fall into this quadrant are called mandatory factors, which means that when the product provides this function, user satisfaction will not increase, and when this function is not provided, user satisfaction will be greatly reduced; Function is the most basic function.

In practice, we must first go all out to meet the most basic needs of users, that is, the necessary factors expressed in the fourth quadrant, these requirements are things that users think we have an obligation to do. After realizing the most basic needs, we should try our best to meet the user's expectation needs, that is, the expectation factors represented by the first quadrant, which is the competitive factor of quality. Provide users with favorite additional services or product features that make their products and services superior to and different from competitors, and guide users to strengthen their good impression of this product. Finally, it strives to achieve the user's charismatic needs, that is, the charm factor expressed in the second quadrant, to improve user loyalty. Therefore, the better-worse coefficient value calculated according to the kano model indicates that the product needs to optimize function 5 first, and then satisfy function 1. The functions 2, 3, and 4 are no different requirements for the user, and there is no need to make great efforts to implement them.

Result output

In order to express these five types of requirements more clearly, they are placed in a coordinate chart, which shows the characteristics of each type of requirement. The abscissa is the degree of provision and the ordinate is the degree of satisfaction.