What Is Customer Satisfaction?

How to build the best customer satisfaction surveys research

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Customer satisfaction is a continuous variable that can be represented as a continuum.

The ends of this continuum would be labeled "Not at all satisfied" and "Completely satisfied." Some value in between these extremes represents the level of satisfaction for a particular customer. Generally, market researchers consider the agreement between the point on the customer satisfaction scale and the actual opinion of the customer regarding their satisfaction to be inexact.​

However, it is feasible and even likely that the point on the scale approximates the customer's satisfaction. Since it is an approximate value, the market researcher will allow for a small degree of error. Because of this small approximation error, a market researcher would consider customer satisfaction to be a latent variable.

What Is the Difference Between Latent Variables and Manifest Variables?

Latent variables are those concepts in psychology, sociology, economics, and other social sciences that cannot be measured explicitly. For instance, market researchers are often interested in consumers' motivations or attitudes. But these concepts, like the concept of satisfaction, cannot be measured directly in the same way as, say, age, weight, or level of education. These demographic attributes are referred to as manifest variables and they can be measured explicitly; they are manifest in a tangible form.

Theoretically, scientists generally agree that for every latent variable being measured, several manifest variables should be associated with the latent variable. In this way, it is possible for the market researcher to explore the relationships between a latent variable which cannot be measured directly to several manifest variables which can be measured directly.

Developing Customer Satisfaction Survey Questions

Customer satisfaction can be measured well through the use of survey questionnaires. It is helpful to craft a number of questions that measure the degree of satisfaction or dissatisfaction experienced by a consumer on a scale. Though satisfaction is infinitely variable, for practical reasons, a satisfaction scale would need to be limited. The customer should be afforded sufficient flexibility in his or her response that the match between the customer experience and the response on the scale are comfortable.

Customer Satisfaction Scales - Scales used to indicate customer satisfaction are often 5-point, 7-point, or 10-point, such that zero always represents the highest degree of dissatisfaction. On a 5-point scale, a customer would be asked to select a response to a questionnaire item from the following set of alternatives: 1 Very unsatisfied, 2 Moderately unsatisfied, 3 Neutral, 4 Moderately satisfied, 5 Very satisfied.

For each component of the satisfaction survey that respondents are asked to consider, there should be three related questions. These questions are the manifest variables. The questions should be written so that it is easy to match the question language to the aspects of the survey components. For instance, if the market researcher is interested in measuring the component ease of doing business with a company, then the questions could address the speed of transaction, the usability of the website, and the live-chat customer service experience.

Satisfaction Survey Length - The survey questionnaire should range from about 15 to 35 items, each of which addresses some aspect of the components of customer service being measured. It is important that some of the questionnaire items are directed toward learning more about the customers themselves, not just their opinions, in order to support market segmentation analyses.

Analyzing Customer Satisfaction Data With SEM

Strong analyses of customer satisfaction will include mathematical and statistical methods of data analysis. An objective of the analysis is to estimate the relations between the manifest variables and the latent variables, and among the latent variables.

A commonly used method to conduct this type of analysis is a Structured Equation Model (SEM). The fit between the model and the data will be gauged against some criteria or a single criterion, such as the capacity to minimize deviation from the actual observed data will be minimized. The statistical method itself determines the weighting attributed to the relation between the latent variables, rather than a subjective opinion of the market researcher. The reliability of each of the manifest variables is calculated, the contents of the latent variables are derived, and the relations between the latent variables are calculated.

At this point, the market researcher is able to see whether the estimated model actually fits the data to an acceptable extent, typically by using the coefficient of determination which is designated as R2 and is a measure of the goodness of fit.