The Advantages and Disadvantages of the Profile Approach to Analyzing Life Style Data

ABSTRACT - This paper discusses the relative merits and demerits of using the profile technique to analyze life style data. The pros and cons discussed are those which are particularly relevant to profiling and not data analysis in general.


Stephen C. Cosmas (1976) ,"The Advantages and Disadvantages of the Profile Approach to Analyzing Life Style Data", in NA - Advances in Consumer Research Volume 03, eds. Beverlee B. Anderson, Cincinnati, OH : Association for Consumer Research, Pages: 501-503.

Advances in Consumer Research Volume 3, 1976      Pages 501-503


Stephen C. Cosmas, Needham, Harper and Steers Advertising, Inc.


This paper discusses the relative merits and demerits of using the profile technique to analyze life style data. The pros and cons discussed are those which are particularly relevant to profiling and not data analysis in general.

Today, I am going to talk to you about profiling, a way of analyzing consumers' life styles. Specifically, I want to discuss the advantages and disadvantages of the profiling technique. But, before I begin the discussion, it might be helpful to make some general comments about what profiles are and how they are constructed.

In a critical review article on "psychographics", Wells? (1975) made a comment to the effect that almost all of marketing is communication and that marketers are most effective when they know their audiences. Now, one technique for knowing an audience, and probably one of the most widely used for this purpose, is the life style profile.

The life style profile is a technique for analyzing life styles. To construct a profile, a target audience of interest must first be defined. The target audience can be the heavy users of a product or service, such as fast food restaurants (Tigert, Lathrope and Bleeq, 1971); readers of a particular magazine (Michaels, 1973); members of a specific age group (Wells and Cosmas, 1975); consumers who shop outside their own communities (Reynolds and Darden, 1972) -- in fact, any group of interest. Next, the target audience responses to the activity, interest and opinion questions are compared with the responses of the remainder of the population. Items which show significant differences are used to construct a profile of that target audience. Table 1 is one such example. This was a profile developed by Plummer (1971) of male bank charge card users.



Here, the profile of male bank credit card users was produced by comparing that target group with the remainder of the population and taking those items that showed significant differences.

The profile shows, according to Plummer that, more than non-users, the heavy users of commercial bank credit cards agreed with items like:

"I would rather live in or near a big city than in or near a small town."

"I often have a cocktail before dinner."

"We often serve wine at dinner."

"I enjoy going to concerts."

"I like to think I'm a bit of a swinger."

"I expect to be a top executive in ten years."

"I do more things socially than most of my friends."

"I am or have been president of a club or society."

And disagree with items like:

"I stay home most evenings."

"There are day people and there are night people, I am a day person."

"My days seem to follow a definite routine such as eating meals at a regular time."

When added to the traditional demographics, this profile provides an interestingly detailed portrait of the male bank charge card user. The picture that emerges is one which seems:

"to typify the popular stereotypes of the successful man of the rise ....

The picture of the suburban businessman arriving home from the office and having a cocktail, settling down to a nice meal, and then going off to various activities ....

He is a busy, young businessman on the rise who knows where he is going ....

(Plummer, 1971)

In the above example, the independent variables (the life style questions) were related to the dependent variable (bank charge card use) through the simple technique of cross-tabulation. This represents one way of developing profiles. Other ways that have been used include correlational analysis, discriminant analysis, canonical correlation and combinations of the above (Tigert, 1966; Pessemier and Ginter, 1973; Darden and Reynolds, 1972).

However, rather than dwell on methods for constructing profiles, let me proceed to discuss the relative merits and demerits of using profiles, however constructed, to measure the life styles of target audiences.

One of the advantages of using profiles to measure consumer life styles is that once constructed, they are relatively easy to communicate to the users of the information.

Communication is relatively easy because life style profiles are interesting in and of themselves. They seem to describe how members of the target group live and interact with their environment. They describe peoples' activities, interests and opinions on a variety of everyday matters which are in the realm of experience of most individuals. This easy communication is an important advantage because if the user does not understand the profile, he is likely not to use it (Ellis, 1975).

A second advantage of profiles is that they focus on only one target -- the group that has been previously designated as the one of primary importance. This makes it possible to focus in on a single target rather than to fragment attention among several targets, as is the case with segmentation. Profiling, however, is not characterized by only advantages. There are several disadvantages to using profiles.

One disadvantage to using profiles is that they often lead both the researcher and the user to concentrate on differences and thus ignore absolute levels of response. For example, the item "I attend church regularly," might produce the following hypothetical results:


From the response, one might conclude that non-filtered smokers are relatively uninterested in religion when compared to other smokers. As a comparison the conclusion is valid; but the temptation is to go even further here and conclude that non-filtered smokers do not go to church. In terms of absolute levels, that conclusion is obviously incorrect.

Looking back at the profile of male bank charge card users, it can be seen that when the absolute values of some items are re-examined, different conclusions may be reached. For example, the idea of the young businessman coming home from the office and having a cocktail might lead to the conclusion of a regular pattern of consumption of cocktails by the bank charge card users. But looking at the item "I often have a cocktail before dinner" it can be seen that only 36% agreed with the statement. This is not to single out this particular study for criticism, or even to say that the data were misinterpreted, but rather to point out that when profiles are used in the analysis of life style data, absolute levels can often be lost and their importance misplaced.

Probably the biggest disadvantage of profiles is that they may force the combination of several different groups into one. For example, among heavy users of soft drinks, there might exist several quite different groups of consumers with different life styles. If these groups are combined into one "heavy user" group, the differences between the groups are lost. Furthermore, if two different groups of heavy users differ from the non-users on the same dimension, but in opposite directions, merging the different heavy user groups into one overall heavy user group may lose the distinction entirely.

In summary, there are several advantages to using the profile approach to analyzing life style data. One, profiles are easy to communicate. And two, the profiles focus in on one target and therefore tend to present a more detailed picture of a target audience of interest. On the other hand, there are several disadvantages to using profiles. Researchers and users can be mislead by concentrating on differences and ignoring the absolute value of the data. And, profiles may force the combination of several different life style groups and thus, sometimes cause the loss of important distinctions. One way of correcting this latter problem is through segmentation analysis, which will be discussed by Sunil Mehrotra.


William R. Darden, and Fred D. Reynolds, "Canonical Correlation and Redundancy Analysis of Consumer Innovativeness and Life Style Characteristics,'' unpublished working paper, University of Georgia, 1972.

Richard Ellis, "Harnessing Pegasus: The Management of Multivariate Analysis," unpublished paper presented at the 58th International Marketing Conference of the American Marketing Association, Chicago, 1975.

Peter W. Michaels, "Life Style and Magazine Exposure," Combined Proceedings: Marketing Education and the Real World and Dynamic Marketing in a Changing World. Boris W. Becker and Helmut Becket, eds., Chicago, American Marketing Association, 1973, 324-331.

Edgar A. Pessemier, and James L. Ginter, "Profiles of Market Segments and Product Competitive Structures," Paper No. 409, Krannert Graduate School of Industrial Administration, Purdue University, May, 1973.

Joseph T. Plummet, "Life Style Patterns and Commercial Bank Credit Card Usage," Journal of Marketing, 35 (April, 1971), 35-41.

Fred D. Reynolds, and William R. Darden, "Intermarket Patronage: A Psychographic Study of Consumer Outshoppers," Journal of Marketing, 36 (October, 1972), 50-54.

Douglas J. Tigert, "Psychometric Correlates of Opinion Leadership and Innovation," unpublished working paper, University of Chicago, 1969.

Richard Lathrope, and Michael Bleeq, "The Fast Food Franchise: Psychographic and Demographic Segmentation Analysis," Journal of Retailing, 47 (Spring, 1971), 81-90.

William D. Wells, "Psychographics: A Critical Review," Journal of Marketing Research, 12 (May, 1975), 196-213.

William D. Wells, and Stephen C. Cosmas, "Life Styles," paper presented at the Conference of Knowledge of Consumer Behavior, Rann Program, National Science Foundation, April, 1975.



Stephen C. Cosmas, Needham, Harper and Steers Advertising, Inc.


NA - Advances in Consumer Research Volume 03 | 1976

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