Using Primary Scales in Marketing Research

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  • 0:04 What is a Primary Scale?
  • 1:31 Scale Types
  • 3:31 Collecting Data for a Scale
  • 4:33 Lesson Summary
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Lesson Transcript
Instructor: Scott Tuning

Scott has been a faculty member in higher education for over 10 years. He holds an MBA in Management, an MA in counseling, and an M.Div. in Academic Biblical Studies.

Market research findings are only significant and accurate if data is collected and reported using an appropriate scale. This lesson explores various types of primary scales and gives examples of their use.

What is a Primary Scale?

Imagine a high school senior preparing to apply to college. Like many, he may have applied to a few dream schools. A few letters have arrived in the mail, and from the size of them, it's not good news. In describing the reason for the student's rejection, there is a common theme: most applicants accepted to the Ivy League Schools ranked in the top 10% of their high school class. Besides being a category the applicant is not a part of, what does this top 10% figure actually mean?

This type of criteria provides a great launch pad for understanding primary scales, because the significance of being in the top percent of a class is extremely dependent on the type of scale being used. Although the example scenario was centered on admission to college, market researchers often have a similar experience when reporting out the results of a study. Saying something like, ''10% of consumers prefer brand A over brand B'' only has meaning if the comparison is taking place on the proper primary scale.

A primary scale is the measuring stick by which study subjects are evaluated in relation to one another. In the college admission example, the primary scale is comparing the applicant's ranking to the size of their graduating class. When preparing to report out the results of market research, there are several types of scales that can be selected. Selecting the correct measurement structure is critical, because inappropriate selections will preclude or disrupt the accurate statistical analysis of the findings.

Scale Types

The nominal scale is the most basic (and perhaps least useful) of the options for scale. The key characteristic of a nominal scale is that it does not order, rank, or compare its subjects. In other words, nominal scales simply label variables.

Overview of an Nominal Scale
Nominal Scale Graphic

Ordinal scales resemble nominal scales with one key difference: ordinal scales do make comparisons or rankings between the group's members. The most basic ranking structure can be applied to a market research question that reads something like, ''Please rank the following 5 brands of cola from best to worst tasting. ''

Overview of an Ordinal Scale
Ordinal Scale Graphic

Neither a nominal scale nor an ordinal scale is suitable for mathematically solid statistical analysis. There are no tangible values associated with a nominal scale, and although an ordinal scale does conduct a ranking, there is no specific ''zero''. Since the scale lacks a tangible baseline, ordinal scales also cannot be used in a mathematical analysis.

On the other hand, an interval scale can participate in a statistical analysis because it generates data that's less arbitrary than either nominal or ordinal scales. In an interval scale, the distance (interval) between two data points is known, consistent, and measurable. This means the distance between the points 1 and 2 is comparatively equal to the distance between the points 4 and 5. However, multiplying and dividing intervals is not possible. A score of 4 is not twice as much as a score of 2. This is due to the lack of a true zero on the scale.

Overview of an Interval Scale

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