A Pragmatic Approach For Retail Fashion Monitoring

Lawrence J. Ring, University of Virginia
ABSTRACT - The need to monitor market changes, competitive activities, and individual company performance is a challenge to all retailers. And, in the fashion retailing business, it is especially important because of frequently changing consumer tastes and interests and the attendant shifts in merchandise styles and merchandising methods. This paper outlines a method for fashion market monitoring which tracks both consumer interests and store patronage and can be used to better understand store performance.
[ to cite ]:
Lawrence J. Ring (1978) ,"A Pragmatic Approach For Retail Fashion Monitoring", in NA - Advances in Consumer Research Volume 05, eds. Kent Hunt, Ann Abor, MI : Association for Consumer Research, Pages: 668-674.

Advances in Consumer Research Volume 5, 1978      Pages 668-674


Lawrence J. Ring, University of Virginia


The need to monitor market changes, competitive activities, and individual company performance is a challenge to all retailers. And, in the fashion retailing business, it is especially important because of frequently changing consumer tastes and interests and the attendant shifts in merchandise styles and merchandising methods. This paper outlines a method for fashion market monitoring which tracks both consumer interests and store patronage and can be used to better understand store performance.


Within the past decade, the fashion arena has become a popular topic of contemporary consumer research. Over the same period, the proliferation of new styles and fashions has pushed the industry to new sales heights here and abroad. Recent figures indicate that U.S. and Canadian consumers purchase well over 25 billion dollars worth of clothing and accessories annually from a diverse array of retail outlets.

In this mass market, recent studies (King, Tigert, and Ring, 1975, and Sproles and King, 1973) reveal that a large proportion of the population is interested in fashion participation and continuously monitors current fashion trends. In addition, mass fashions are simultaneously available to the fashion consumer in nearly all price ranges.

Mass communications and the rapid production of fashions have increased the rate of fashion diffusion throughout the population. We are now witnessing the accumulation of sizable and frequently updated wardrobes by almost all segments of the population.

Along with this development of mass manufacturing strategies, the proliferation of mass media information and influence, and the increased levels of disposable income has come a general explosion of new retailing and merchandising concepts which have strong implications for the individual firm's merchandising strategy and attendant "retail image."

In any particular fashion retail marketplace, the consumer is faced with a choice among a varied group of fashion outlets each developing and maintaining its own "fashion" profile. The ability of each of those competing retailers, and particularly among those large chains competing for the mass market, to meet consumer needs and at the same time monitor competitive changes in the marketplace is dependent upon the individual firm's ability to efficiently gather and synthesize information about the changing marketplace.

This paper describes a methodology for providing a complete diagnosis of the structure of an individual fashion market including patterns of buying behavior and determinants of patronage for major competing chains.


Historically contemporary fashion research has focused on the fashion innovator and the fashion opinion leader as prime sales targets and key links to the volume fashion market. A variety [A representative list of fashion segmentation studies would include King (1963), Grindereng (1967), Pasnak and Ayers (1969), King and Summers (1970), Reynolds and Darden (1973), Sproles and King (1973), Baumgarten (1975), Tigert, Ring, and King (1975), and Painter and Grianzin (1976).] of methodological studies designed to define, isolate, and profile these segments have dominated fashion research since the basic concept was first introduced by King (1963).

In general, fashion segmentation has been based on the division of consumers into relatively homogeneous segments based on demographic, psychological, and sociological measures, media exposure characteristics, and specific measures of fashion involvement and consciousness.

Contemporary fashion theory research has tended to focus on the fashion process and its interacting behavioral system. Researchers have been increasingly interested in the dynamics of fashion adoption and diffusion. The specific situations of fashion innovativeness, fashion opinion leadership, and the broad concept of the fashion change agent provide an expanding base of literature in the fashion arena.

In fashion apparel thought, the fashion change agent has been seen as more than simply an innovator or opinion leader as traditionally defined. Sproles and King (1973) have argued that while innovativeness and opinion leadership in fashion are theoretically distinct concepts, that the differentiation may not be either pragmatically necessary nor even a requirement for segmentation purposes. The time compression of contemporary fashion diffusion confounds the strict identification of innovators and opinion leaders and major or mass market adoption is accelerated instead by a broadly identified change agent segment of the population (Sproles and King, 1973).

From the retailer's point of view in the mass market, the problem is to determine the levels of fashion involvement of the population and ascertain the size and needs of each "level of fashion involvement" segment.


Over the last fifteen years, the author and others have conducted a number of research investigations of fashion involvement in the United States and Canada. The accumulated data base now contains measurements of fashion interest at different points in time in different geographic regions and among both male and female populations. As a result, a comparative data base spanning fifteen years has now been established.

In the case of one measure, data has been collected from over twenty independent populations using essentially identical methods of sample selection and exactly identical and, therefore, comparable measurements of fashion interest, That measure is general fashion interest (also sometimes referred to as fashion awareness). In each of the investigations mentioned above, the following question was asked of all respondents:

"Which ONE of these statements best describes your reactions to changing fashions in men's (women's) clothes? Even though there may be no statement listed which exactly describes how you feel, make the best choice you can from the answers listed."

I read the fashion news regularly and try to keep my wardrobe up to date with the fashion trends ____1

I keep up to date on all the fashion changes, although I don't always attempt to dress according to these changes __ 2

I check to see what is currently fashionable only when I need to buy some new clothes ___ 3

I don't pay much attention to fashion trends unless a major change takes place ___4

I am not at all interested in fashion trends ___5

Comparative results using this measure have been reported elsewhere and provide a baseline for future comparison and tracking of fashion interest (see King, Tigert, and Ring, 1975, and Ring, 1977). Therefore, this particular question provides an excellent measure of fashion interest across any particular population.


The relationship between consumer attitudes and retail sales has long been a popular topic for examination by retail researchers -- and particularly with regard to department stores (Berry, 1969, Lazer and Wyckham, 1969, and Weale, 1971, for example.)

A number of techniques have been utilized by marketers in researching retail image. The semantic differential (Arons, 1961, Anderson and Scott, 1970, and Kelly and Stephenson, 1967) and the open-ended questionnaire (Berry, 1969), have been two of the more popular techniques employed.

As discussed by Arnold and Tigert (1973), however, each of these techniques has significant problems. The major issue is their characteristic length and complexity. The semantic differential, for example, requires the respondent to rate each retailer on each attribute under study. The open-ended questionnaire, on the other hand, generally requires personal interviewing and content analysis of the responses.

Tigert (1976)has demonstrated that the measurement of store characteristics by the use of the "associative technique" is both reliable and valid, as well as discriminating. He contends, in fact, that the associative technique measures the world in a way which reflects the manner in which consumers go through the choice process.

Operationally, the associative technique involves asking each respondent which store (among a set of stores representative of a particular market) best answers each of a set of individual questions related to the stores. This technique has been employed in the analysis which follows.


Retail image researchers have, over the years, identified a large number of dimensions upon which consumers judge a store's performance and which therefore may conceivably contribute to the constitution of a store's personality or image. For example, Lazer and Wyckham (1969), listed four major image dimensions, while Martineau (1958) suggested six traits, Stephenson (1969) described eight dimensions, Wyckham (1967) 30 dimensions, May (1971) 42 dimensions, Berry (1969) 44 dimensions and Shapiro (1970) 94 dimensions in a study of retail products among Boston consumers.

While these studies have focused on a variety of store types and product classes, many have dealt in some way with fashions. Based on these results, and on other fashion research over a period of several years, several "attitudes" or "image dimensions" have been found to consistently characterize retail fashion chains and as well to be useful for management decision-making. These dimensions in the question format of the "associative technique" and in the case of men's fashions are:

1. Which store is the easiest one to get to from your home?

2. Which store has the lowest prices?

3. Which store has the highest prices?

4. Which store has the most knowledgeable/helpful salesclerks?

5. Which store has the highest quality men's fashions?

6. Which store has the lowest quality men's fashions?

7. Which store gives you the best value for the money in men's fashions?

8. Which store gives you the worst value for the money in men's fashions?

9. Which store has the largest overall merchandise assortment/selection in men's fashions?

10. Which store is best for conservative, everyday men's wear?

11. Which store is best for current, up-to-date men's wear?

12. Which store is the best for the very latest, most fashionable men's wear?

13. At which store do you find the most exciting merchandise display of men's fashions?

14. Which store has the best fashion advertising?

In addition, two measures of share of shoppers should be employed in this approach, again using the "associative technique." They are:

1. Which store was visited the last time an article of men's wear was purchased?

2. Which store is shopped most often for men's wear?


The results which are reported later in this paper represent an example of the implementation of the approach described here over several years in Toronto, Ontario, Canada for the expressed purpose of monitoring the retail fashion marketplace there. This research was conceptualized as a joint academic/industry project and has been operated and supported on that basis now for four consecutive years beginning in 1974. The example which is discussed below is based on data collected about the men's fashion market in Toronto and is representative of other similar efforts elsewhere and in the women's fashion market as well.

Data Collection

The data for the Toronto Project has been collected each year (1974-1977) by mailed self-administered questionnaire from the Toronto Census Metropolitan Area (CMA). The samples have been obtained by telephone placement of questionnaires to adult male household heads. The samples were recruited to be in balance with city demographic profiles. Questionnaire administration has taken place in the spring of each year. A total of 615 usable questionnaires were mailed to each respondent complete with standard self-administration instructions. Each participant received a small gift for completing the questionnaire.

Store Selection

In attempting to understand the structure of the Toronto men's wear retail mass marketplace, it was first necessary to define a relevant set of retailers to present to respondents for their judgments. Since the analysis was to be concerned with the mass market, and was to be based on consumer judgment, it was important to include those chains which had sufficient market coverage and general recognition for respondents to judge them.

Ten stores and an "all other" category were listed as response alternatives in the survey, including the city's three major department stores. Each of the chains included in the analysis was operating at least six retail outlets in Toronto in 1975. In addition, it was estimated that each of the chains was obtaining gross men's wear sales in Toronto of at least $5 million per year.

Fashion Interest Results

Table 1 presents the 1974-1977 fashion interest results for the ongoing Toronto project. These results can be interpreted in several ways. For example, those respondents who perceived themselves to be in the first category (see question series), might be identified as innovators since they indicate that they keep their wardrobes up to date with fashion trends. However, perhaps a more important concern than the first category alone is the aggregated total of the first two categories. Pragmatically, those respondents who have responded in either the first or second level fashion interest categories might be classified as active in fashion interest, at least in terms of consistently monitoring, if not purchasing, new fashions.

By combining the first and second levels of fashion interest as indicated above, it is clear that approximately one quarter of the respondents over the four years can be classified as active in fashion interest and capable of influencing the mass population at least verbally, if not visually, with regard to changing fashion trends. This is true because those men responding in both the top two fashion interest levels keep informed of fashion changes and thereby could potentially be communicators of information. And, those individuals in fashion interest level one are also potentially visual influentials by virtue of the fact that they keep their wardrobes up to date and are therefore wearing the latest fashions for all to see.

Looking at the data another way, it appears that the majority of adult male Toronto consumers are not particularly interested in new men's fashions. And, in comparison to female and college student fashion interest statistics and even American adult male statistics (see Ring, 1977), Toronto has fewer change agents (categories one and two).

More importantly, from a market monitoring perspective, it appears some significant shifts have occurred in the level of fashion interest over the four year data base. For example, the drop in percentage reporting as fashion change agents from 1974 to 1975 represented a significant change in fashion interest level, as did the five percent increase from 1976 to 1977. [The observed difference of 7 percent is greater than 2.4 standard errors from zero, while the 5 percent difference from 1976 to 1977 is 1.96 standard errors from zero. Both significant at the .95 level.] This kind of information might be particularly important to the firm which is merchandising primarily toward the top end of the fashion market as is demonstrated in the next section of this paper.



Fashion Interest by Store

The basic thesis in this analysis is that consumers differ in the fashion shopping behavior based on their self perceived fashion interest or involvement. To explore this question, the fashion interest measure need only be cross-classified with a measure of share of shoppers such as "store shopped most often."

The following example illustrates some rather dramatic differences between the self-perceived fashion interest level of the shoppers of a leading Toronto department store and a leading fashion specialty chain. In Table 2, it is clear that the fashion specialty chain shoppers perceive themselves as much more interested in men's fashions than do the department store shoppers. Taking 1975 as an example, fully 40 percent (levels 1 and 2) of the fashion specialty chain shoppers were regularly monitoring (if not purchasing) new men's fashions. In contrast, only 17 percent of the department store shoppers made a similar response.

These differences are important at any given point in time and also as they may change over time to the management of each chain. Satisfying the needs of the highly fashion interested clientele of the fashion specialty chain surely points to a different merchandising strategy than does satisfying the needs of the department store shopper. These results lead to an analysis of store patronage dimensions.



[The difference between department store consumer fashion interest and fashion specialty chain fashion interest were significant at the .001 level based on X2 analysis.  *READ: among those who shop most often at the department store, 0.8 percent said that they regularly read the fashion news and tried to keep their wardrobes up-to-date with the fashion trends.]

The analysis of store patronage can proceed at two levels. Initially, the concern is with the share of shoppers mentioning each chain on each of the patronage dimensions. Secondly, however, it is important analyze the attitudes of each chain's shoppers on a chain-by-chain basis.

Table 3 continues the example of the department store and the fashion specialty chain for the year 1975. In this table the share of shoppers (of the overall sample) which mentioned each of the two stores as being best (or worst, highest, lowest, etc.) on each of the patronage dimensions have been presented. These results document the "image" of each chain as seen by the overall sample at a particular point in time (spring, 1975.)



Market coverage in Table 3 has been measured by asking respondents which store is the "easiest to get to from their home?" Based on the percentage of respondents who identify a particular store as the easiest on to get to from home, a "trading area" can be defined for each store (chain). The discussion will refer to the trading area with the term, "market coverage." For example, the Department Store had a 18 percent market coverage because 18 percent of the respondents said that the Department Store was the easiest to get to from home. The Specialty Chain had only a 2 percent market coverage.

A more important concern than market coverage alone is the relationship between market coverage and share of shoppers (as measured by the "last shopped" and "shop most often" questions.) Twenty-nine percent of the sample last shopped of the department store compared to 5 percent which last shopped at the fashion specialty chain. Similar figures are obtained on the shop most often measure, indicating that a much larger percentage of the market shops at the department store than at the specialty chain.

However, the ratios between "market coverage" and the two share measures provide a slightly different perspective. The ratio analysis eliminates the differential market coverage across chains and expresses each chain's customer set as a ratio of coverage.


Both of the chains in the above example have better than "one to one" ratios of the two share measures to market coverage. Interpretatively, these findings indicate that these two chains were performing better than could be expected based on their market coverage alone. Chains with ratios of less the "one to one" would be drawing fewer shoppers than the percent who said the chains were closest to home--meaning some shoppers were driving past those chains to get to other, less accessible stores for some reason.

The ratio analysis can also be performed on the price, quality and value for the money measures since two data points were collected for each of those dimensions. A better than "one to one" ratio on each of these dimensions would indicate a positive price, quality, and value image from the overall sample. In this example, the department store is positive on all three dimensions, while the fashion specialty chain is positive on quality and "negative (or less than one to one) on price and value.

Looking at some of the other dimensions, the department store appears to have a larger percentage than the specialty chain in many, but not all, of the cases. This may, in part, be attributable to the fact that many more respondents shop at the department store, and all other things being equal probably tends to rate the store shopped most often highest or best on each of the important dimensions. Consequently, to some extent the share of mentions on any given question often tends to mirror the share of shoppers for a given chain. Thus, if the results are examined only in terms of absolute percentages, a store with a large share of shoppers might be thought to be very strong on a particular dimension, while a store with a small share might be considered to be weak. This mistake can be avoided if the raw percentages are examined in comparison to the overall share of shoppers for the chain. For example, in terms of absolute percentages, both of the example chains appear to be equally strong on the best salesclerk question (question 10.) The department store obtains 19 percent of the mentions and the specialty chain obtains 20 percent. However, if these figures are compared to overall share of shoppers, it is clear that the department store is not performing particularly well on this dimension, while the specialty chain is extremely strong here. Only 6 percent of the sample shopped at the specialty chain but three times that many said the chain had the most knowledgeable, helpful salesclerks. In contrast, 35 percent of the sample shopped at the department store, but only 19 percent said that store had the most knowledgeable, helpful salesclerks.

Another method of understanding the strengths and weaknesses of each chain is to analyze how the shoppers of each individual chain rate that chain. This can be easily accomplished through the use of cross-classification analysis.

Cross Classification

Table 4 contrasts the shoppers of the two chains across 11 determinants of patronage. This analysis is based on the cross-classification of shoppers "most often shopping" each chain with each of the retail patronage dimensions. Given the fashion interest findings discussed earlier, the fashion specialty chain should be expected to be perceived as more fashion-oriented than the department store. In this example, that is the case.

Clearly, the shoppers of the department store have a different "image" of their "most often shopped" chain than do the fashion specialty chain shoppers of their "most often shopped" chain.

Although more sophisticated analysis techniques can be utilized (for example, see Ring, 1976), simply assigning the attributes to whichever chain obtained the higher percentage yields interesting results. What emerges is a statement of the strengths and weaknesses of the two chains as perceived by their own shoppers.

For example, consumers would appear to be shopping at the department store because of its good location, lower prices and higher value for the money, better merchandise assortment/selection, better (more) advertising, and a stronger orientation to conservative, everyday men's wear. The fashion specialty chain shoppers, on the other hand, are paying for higher quality, more salesclerk "stroking", an exciting merchandise display, and a current-to-very latest, most fashionable apparel mix.

These findings are consistent with the consumer self-perceptions of their own fashion interest as discussed previously. The department store was viewed as low on the fashion spectrum and its shoppers perceived themselves as only marginally fashion involved. The fashion specialty chain shoppers perceived themselves as much more highly interested in fashion and their chain as highly fashion oriented in terms of product offering.





Monitoring Over Time

Thus far the discussion of store patronage and the fashion profiles of each store's shoppers has been discussed only as it related to one point in time, the spring of 1975. While this analysis in and of itself is obviously useful, it becomes even more relevant when it is done on a regular basis over a long period of time. The time series analysis permits management to observe its effectiveness at attempting to penetrate new market segments or to change its image from year to year. For example, one major Toronto department store had watched its market share and its image on many important dimensions such as display, assortment, and merchandise fashionability erode as competitors expanded their operations into new stores with more fashionable merchandise while the department store "let itself go" in anticipation of the eventual opening of a major downtown showcase flagship store and shopping mall. The data in Table 5 reflect this store's performance on selected dimensions over the four year period during which the Toronto project has operated.

Between the collection of data in 1976 and in 1977, this department store opened its new flagship store downtown. The upward shifts on the selected dimensions included in the table reflect the impact of the new store on the marketplace, and indicate the chain's image has improved over the year on each of these measures.

Similar analyses have been completed for each chain on each of the patronage dimensions and on the fashion interest question for each of the four years. In addition, a number of other relevant dimensions have been measured as well, included demographics, fashion AIO measures, price and volume pointing measures, additional fashion involvement questions, media and information sources measures, and fashion item (suit, sports jacket, etc.) measures. In total, these results provide the basis for a complete diagnosis of the Toronto fashion market including patterns of buying behavior and determinants of patronage for major competing chains.


Earlier studies have documented major differences among consumers in terms of their fashion involvement and fashion consciousness. Other research has uncovered major differences in consumer perceptions of competing retailers and in the profiles of the customers of competing retailers

In the competitive fashion retailing milieu, these differences are of major decision-making importance. The established retailer inevitably has a store image which has attracted his existing clientele. That image may have been planned as a strategic maneuver, or it may have been generated fortuitously. Therefore, the retailer, in selecting his product line offerings, as well as in designing his entire fashion retail presentation, can buy product offerings which coincide with his present strategy and image, or select offerings or make image decisions purposively designed to attract other segments that he may not now service.

This paper describes a methodology for retail fashion market monitoring which applies fashion segmentation research techniques and retail image methods to the men's fashion context.

This methodology provides new input for the retailer in terms of identifying and profiling fashion market segment, in selecting his product lines, his merchandising approach, and in designing and targeting his entire retail presentation to specific fashion market segments.

Market monitoring permits the diagnosis of the market structure and the understanding of patterns of buying behavior over time and enables the retailer to precisely pinpoint his strengths and weaknesses as they currently exist and as they change over time.


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