I delivered a presentation to the Tampa Bay Agile Meetup Group regarding the Voice of the Customer along with two models and two elicitation techniques. The model and elicitation technique that seemed to spark the most interest was the Kano Model and Kano Survey.
The Kano Model was developed by Dr. Kano in Japan in 1984. Kano’s assertion was that not all features affected the customer’s satisfaction equally and that customer loyalty correlates to the customer’s emotional response to the features. Whether a customer buys your product, or not, depends on their emotional response to it. Different features invoke different responses and it is all based on the perception of the customer. Value attracts customers, quality builds loyalty and innovation is necessary to differentiate your product and compete in the marketplace.
The model depicts “level of execution” on the X-axis (poor – well) and depicts the “customer satisfaction level” on the Y-axis (very dissatisfied – very satisfied). There are 3 main classifications and 2 additional for a total of 5 in the model. I will first review the 3 main classifications of “Must Be”, “One Dimensional” and “Attractive” (these are the original labels that Kano assigned, but people have substituted others).
Must Be: The first classification is “Must Be” (also referred to as the “Must Have”, “Basic”, “Essential”). This is the type of feature that if not present will make the customer very dissatisfied, but at the same time the fact that the feature is there does not overly satisfy the customer. An example, might be “soap” in a hotel room. If a customer does not have any soap in their hotel room they will be very displeased. These product features are usually so obvious that if you are interviewing a customer they may not even mention them. The more or better the feature the less displeased the customer will be, but there will be a point where improving on the feature will not make the customer any more satisfied. In our “soap” example, it would be dissatisfying for a customer if they ran out of soap. So, if you had one or two extra bars of soap then this would keep the customer from becoming dissatisfied, but having 50 bars of soap in the room would not push their satisfaction level any higher than if you had those couple of extra soap bars. “Must Be” features do not result in product differentiation and are expected by the customer.
One-Dimensional: The second classification is “One-Dimensional” (also referred to as “Performance”). This feature is measured by the customer and the better the measurement is received by the customer then the better the satisfaction and fulfillment level of the feature. This type of feature is on the mind of the customer when purchasing and if you are ahead of your competitors then you will gain customers. This feature is usually the easiest to attain/elicit and the customer will most always pay more if you are better than your competitors in this area. An example of these types of features would be the battery life, disk space and processing power of a laptop computer. Exceeding your competitors for these features will proportionally grow customer satisfaction.
Attractive: The third classification is “Attractive” (also referred to as “Exciter”, “Delighter”, “Innovative”, “WOW!”). These features are unexpected by the customer and contribute to the uniqueness of your product. These features are innovative and contribute to very high customer satisfaction levels. They “WOW!” the customer. These features are difficult to attain/elicit, but have great impact. Attractive features may diminish over time and eventually even become “Must Be”. An Attractive feature for my son when he got his new mobile phone was “swipe texting”. At one time flat screens on a TV were Attractive features, but they are long since expected (“Must Be”) now.
The two additional classifications are “Indifferent” and “Reverse”.
Indifferent: The classification of “Indifferent” relates to features which do not sway the customer’s satisfaction much in either direction whether the feature was executed poorly or well.
Reverse: The classification of “Reverse” relates to features that dissatisfy the customer if they are present. An example may be an annoying pop-up message.
In summary, utilize the Kano model to classify your features customer satisfaction levels and deliver a product that meets the basic “Must Be”, maximizes the “One-Dimensional” and includes as many “Attractive” features as possible at a cost the market will bear. Also, take a look at the Kano Survey below which will explain how to conduct the survey and assess your feature’s customer satisfaction types.
The Kano Survey goes hand and hand with the Kano Model and is the technique used to ascertain the customer satisfaction classification of a feature. The survey is fairly simple and consists of pairs of questions that are asked to the customer.
For each feature we ask a pair of questions. One is positive and one is negative.
Positive: If you could … how would you feel?
Negative: If you could not … how would you feel?
The customer answers each question with one of five answers. They “1-Like”, “2-Expect”, “are 3-Neutral”, “can 4-Live With” or “5-Dislike” it. For each pair of questions, we take the value of their answers and match them on the survey matrix. If the customer answered “1-Like” to the feature’s positive question and they answered “5-Dislike” to the feature’s negative question then we would follow the positive column of “1-Like” down until it met the negative column of “5-Dislike” and find that the color at this intersection is blue. According to the key, blue represents a “One-Dimensional” customer satisfaction type (see Kano Model post for what this means).
If you were a producer of toothpaste a feature of your product might be “easily dispense your toothpaste”. To attain the customer satisfaction type we would survey customers and aggregate the findings for the following pair of questions.
Positive: If you could “easily dispense your toothpaste” how would you feel?
Negative: If you could not “easily dispense your toothpaste” how would you feel?
In conducting the survey your number of responses need to be at a certain level for the survey to meet your needs. For those mathematically inclined the calculation to determine the minimum survey responses needed is listed below.
Sample Size = (Z-score)² – StdDev*(1-StdDev) / (margin of error)²
Adjusted Sample Size = (SS) / (1 + ((SS – 1) / population))
Population = total number of people represented in your selected universe
Margin of error = willingness for error (ex: +- 5%)
StdDev = standard deviation; how much variance do you expect in responses; (if no preference then use .5)
Z-score – corresponds to confidence level (90%=1.645, 95%=1.96, 99%=2.326)
Example Sample Size:
SS=((1.96)² x .5(.5)) / (.05)²
SS=(3.8416 x .25) / .0025
SS=.9604 / .0025
So, 385 respondents are needed
If you know your population you can then adjust accordingly:
SSadjusted = (SS) / [1 + ((SS – 1) / population)]
Have fun utilizing this technique to gain the Voice of the Customer!