Basic Marketing: A Global Managerial Approach

Perreault−McCarthy: Basic
Marketing: A
Global−Managerial
Approach, 14/e

8. Improving Decisions
   with Marketing
   Information

Text © The McGraw−Hill

Companies, 2002

Improving Decisions with Marketing Information 239

What does it really

mean?

Interpreting the Data—Step 4

After someone collects the data, it has to be analyzed to decide what it all means.

In quantitative research, this step usually involves statistics. Statistical packages—

easy-to-use computer programs that analyze data—have made this step easier. As

we noted earlier, some firms provide decision support systemsso managers can use a

statistical package to interpret data themselves. More often, however, technical spe-

cialists are involved at the interpretation step.

Cross-tabulation is one of the most frequently used approaches for analyzing and

interpreting marketing research data. It shows the relationship of answers to two

different questions. Exhibit 8-5 is an example. The cross-tab analysis showed that

customers who had moved in the last year were much more likely than nonmovers

to have adopted “Caller ID” on their phones at home.

There are many other approaches for statistical analysis—the best one depends

on the situation. The details of statistical analysis are beyond the scope of this book.

But a good manager should know enough to understand what a research project can

and can’t do.^19

It’s usually impossible for marketing managers to collect all the information they

want about everyone in a population—the total group they are interested in. Mar-

keting researchers typically study only a sample,a part of the relevant population.

How well a sample representsthe total population affects the results. Results from a

sample that is not representative may not give a true picture.

The manager of a retail store might want a phone survey to learn what con-

sumers think about the store’s hours. If interviewers make all of the calls during the

day, the sample will not be representative. Consumers who work outside the home

during the day won’t have an equal chance of being included. Those interviewed

might say the limited store hours are “satisfactory.” Yet it would be a mistake to

assume that allconsumers are satisfied.

You can see that getting a representative sample is very important. One method

of doing so is random sampling,where each member of the population has the same

chance of being included in the sample. Great care must be used to ensure that

sampling is really random, not just haphazard.

If a random sample is chosen from a population, it will tend to have the same

characteristics and be representative of the population. “Tend to” is important

because it is only a tendency—the sample is not exactly the same as the population.

Exhibit 8-5 Cross-Tabulation Breakdown of Responses to a Phone Company

Consumer Survey

Have You Moved in the Last Year?

Answers: No Yes Total

Do you have “Caller ID” on Yes 10.2% 23.4% 15.5%

your phone at home? No 89.8 76.6 84.5

To t a l 100.0% 100.0% 100.0%

Interpretation: 15.5 percent of people in the survey said that they had “Caller ID” on their phone at home. However, the

percentage was much higher (23.4%) among people who had moved in the last year, and lower (10.2%) among people

who had not moved.

Is your sample really

representative?

Random samples tend

to be representative