As mentioned in the previous installment in this series (Telephone Sampling), this article was originally written as part of an internal training manual. While a few of the statistics cited within have changed somewhat since the original writing, the content of the article still applies. We'll print this article in several installments:
Because we've kept this article in its original form, some readers may find it to be a bit technical. As a user of research, it is not important to have a thoroughunderstanding of each of the sampling issues discussed in this article. However, as a user of research, it is very important to realize that these issues exist. Good research, after all, is not simply a matter of writing good questions.
A. Background
Mall intercept surveys are widely used and (theoretically) able to reach a large segment of the population. In any given two-week period, about 2/3 of U.S. households shop one or more times at a mall. According to a CASRO membership survey, about 25% of all marketing research and 64% of personal interviews are conducted at malls.
B. Pluses And Minuses
The good things about mall samples are:
The bad things are:
C. Effect Of Mall Samples On Results
For copy, concept, and product tests, data suggest that mall samples understate scores.
D. "Ideal" Mall Sampling Plan
According to an article by Seymour Sudman, 1 to achieve a very good sample via the mall intercept method. However, this is what you have to do.
E. Practical Plan
Sudman's plan, unfortunately, is so difficult to put in practice that it would rarely, if ever, be used. In particular, the concept of posting interviewers at randomly selected mall entrances would be effective only for on-the-spot interviews. If respondents have to go to an office, the refusal rate caused by having to walk the length of the mall would eliminate whatever benefit there might be to the random sampling plan.
The following is a plan for "good but not pristine" mall samples:
F. Quota Screening
We've seen that mall shoppers are a demographically biased group. You can partly overcome this bias by using a quota sample if you know what the characteristics of the sample should be. But what if you don't know? Suppose, for example, you're screening for people who took both French and Spanish in high school and once worked flipping burgers. You haven't the slightest idea what they're like, let alone what the incidence is.
That's where quota screening comes in.