Marketing Research

I’ve written in the past that it’s best to use probability-based sampling techniques for your employee, market research or consumer survey samples whenever possible.  One of these techniques is called stratified sampling.  It is used when you expect that your population is heterogeneous (different) and that the survey results could vary greatly based upon certain subgroup characteristics.  If you are particularly interested in subgroup analysis within your survey sample, using a stratified sample can increase the accuracy of your results and reduce error estimates.  Here’s how it works:

Let’s say you are interested the television watching habits of American citizens, and you know (from anecdotal evidence or previous theory) that television watching varies widely by gender.  Since you know that males and females have disparate television watching habits, you want to select a sample whose results will accurately reflect the habits and responses for males and females independently.

What you do is first divide the population into mutually exclusive subgroups (or “strata”), and then take a random sample from each of the subgroups.  Using our gender example, you would divide the population into two groups (male and female), then take a random sample from your male and female subgroups, respectively.  You will be able to be more confident in what you say about your results than if you used a simple random sample from the overall population.