Customer Satisfaction Metrics
Customer satisfaction is often measured by customer survey data via the five-point scale:
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Very satisfied
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Satisfied
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Neutral
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Dissatisfied
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Very dissatisfied.
Satisfaction with the overall quality of the product and its specific dimensions is usually obtained through various methods of customer surveys. For example, the specific parameters of customer satisfaction in software monitored by IBM include the CUPRIMDSO categories (capability, functionality, usability, performance, reliability, installability, maintainability, documentation/information, service, and overall); for Hewlett-Packard they are FURPS (functionality, usability, reliability, performance, and service).
Based on the five-point-scale data, several metrics with slight variations can be constructed and used, depending on the purpose of analysis. For example:
(1) Percent of completely satisfied customers
(2) Percent of satisfied customers (satisfied and completely satisfied)
(3) Percent of dissatisfied customers (dissatisfied and completely dissatisfied)
(4) Percent of nonsatisfied (neutral, dissatisfied, and completely dissatisfied)
Usually the second metric, percent satisfaction, is used. In practices that focus on reducing the percentage of nonsatisfaction, much like reducing product defects, metric (4) is used.
In addition to forming percentages for various satisfaction or dissatisfaction categories, the weighted index approach can be used. For instance, some companies use the net satisfaction index (NSI) to facilitate comparisons across product. The NSI has the following weighting factors:
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Completely satisfied = 100%
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Satisfied = 75%
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Neutral = 50%
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Dissatisfied = 25%
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Completely dissatisfied = 0%
NSI ranges from 0% (all customers are completely dissatisfied) to 100% (all customers are completely satisfied). If all customers are satisfied (but not completely satisfied), NSI will have a value of 75%. This weighting approach, however, may be masking the satisfaction profile of one’s customer set. For example, if half of the customers are completely satisfied and half are neutral, NSI’s value is also 75%, which is equivalent to the scenario that all customers are satisfied. If satisfaction is a good indicator of product loyalty, then half completely satisfied and half neutral is certainly less positive than all satisfied. Furthermore, we are not sure of the rationale behind giving a 25% weight to those who are dissatisfied. Therefore, this example of NSI is not a good metric; it is inferior to the simple approach of calculating percentage of specific categories. If the entire satisfaction profile is desired, one can simply show the percent distribution of all categories via a histogram. A weighted index is for data summary when multiple indicators are too cumbersome to be shown. For example, if customers’ purchase decisions can be expressed as a function of their satisfaction with specific dimensions of a product, then a purchase decision index could be useful. In contrast, if simple indicators can do the job, then the weighted index approach should be avoided.