Marketing researchers usually draw conclusions about large groups of consumers by studying a small sample of the total consumer population. A sample is a segment of the population selected to represent the population as a whole. Ideally, the sample should be representative so that the researcher can make accurate estimates of the thoughts and behaviors of the larger population.

Designing the sample requires three decisions.

First, who is to be surveyed? The answer to this question is not always obvious. For example, to study the decision-making process for a family automobile purchase, should the researcher interview the husband, wife, other family members, dealership salespeople, or all of these? The researcher must determine what information is needed and who is most likely to have it.

Second, how many people should be surveyed? Large samples give more reliable results than small samples. It is not necessary to sample the entire target market or even a large portion to get reliable results, however. If well chosen, samples of less than 1 percent of a population can often give good reliability.

Third, how should the people in the sample be chosen? The Table below describes different kinds of samples. Using probability samples, each population member has a known chance of being included in the sample, and researchers can calculate confidence limits for sampling error. But when probability sampling costs too much or takes too much time, marketing researchers often take nonprobability samples, even though their sampling error cannot be measured. These varied ways of drawing samples have different costs and time limitations as well as different accuracy and statistical properties. Which method is best depends on the needs of the research project.

Types of Samples