Identifying and Analyzing Consumer Shopping Strategies

ABSTRACT - Typically, shopper typologies have been based on unidimensional motivations or on store attribute preferences. This research examines the utility of multidimensional shopping strategies as a basis for identifying shopper types. Six strategies for grocery shopping are delineated.


Joseph P. Guiltinan and Kent B. Monroe (1980) ,"Identifying and Analyzing Consumer Shopping Strategies", in NA - Advances in Consumer Research Volume 07, eds. Jerry C. Olson, Ann Abor, MI : Association for Consumer Research, Pages: 745-748.

Advances in Consumer Research Volume 7, 1980     Pages 745-748


Joseph P. Guiltinan, University of Kentucky

Kent B. Monroe, Virginia Polytechnic Institute and State University


Typically, shopper typologies have been based on unidimensional motivations or on store attribute preferences. This research examines the utility of multidimensional shopping strategies as a basis for identifying shopper types. Six strategies for grocery shopping are delineated.


The purpose of this study was to identify a typology of consumer grocery shopping strategies. Although the notion of shopper "types" is not new, prior typologies have been based either on unidimensional motivations, on store attribute preferences, or on shopping orientations. Our notion of shopping strategies is similar to the concept of brand choice strategies suggested by Wright (1975) and by Blattberg, (1976). Shopping strategies represent sets of activities that reflect the motives and decision processes governing shopping behavior. That is, shopping strategies represent the amount of external and internal search, the objectives of the search activity, and the planning activities prior to a shopping trip. This research focuses on grocery shopping behaviors. While grocery items are generally construed to be convenience goods, it is postulated that much shopping activity takes place when the shopping trip is used as the unit of analysis rather than the purchase of a particular item. Accordingly, this research was designed to identify: the basic grocery shopping strategies employed by consumers; and demographic, socio-economic, and ideal store attribute descriptors of such shopping strategies.


Most retail patronage behavior research has focused either on identifying correlates of various measures of store loyalty or on the use of store image and benefit analyses to predict store choice. Primarily, pre-purchase behavior has been equated with information search and research has focused on number of stores shopped, number of shopping trips, brands considered, product characteristics considered, number or types of information sought, or information sources used. Other activities such as planning and budgeting have rarely been included in such studies. While limited in that it understates the complexity of shopping behavior, much of this existing research evidence does suggest a number of testable hypotheses.

Shopping Orientations and Motives

A natural outgrowth of interest in shopping motives is the attempt to classify shoppers according to motives. Both Stone (1954) and Kenny-Levick (1969) developed shopping typologies according to motives. Darden and Reynolds (1971) replicating Stone's research also classified shoppers into economic, personalizing, apathetic, and ethical types. Appel (1970) discovered innovative shoppers and conventional shoppers. Similarly, Tauber (1972) has suggested that people derive personal satisfactions from shopping and that these satisfactions compel some people to search for information or to visit several stores. Moschis (1976) discovered that different types of shoppers use different sources of information, trust sources of information differently, and have different preferences for information. That is, different types of shoppers have different shopping strategies and people with different life styles have different information needs. Similarly, Bucklin (1971) suggested that patronage habits and search orientation may be based on perceived household roles.

Perceived Benefits

Other researchers have suggested a relationship between the extent of search and the perceived benefits of search. Bucklin (1966) hypothesized that the consumer will engage in information when: the cost of shopping is low; the buyer knows little about the product and the stores that sell it; and the value of the product is high. Katona and Mueller (1955) indicate that extended decision processes tend to occur when the buyer perceives shopping as enjoyable rather than burdensome. Farley (1964) and Nicosia (1966) suggested buyers balance perceived costs of search against perceived benefits of information. Image and benefit research claims that shoppers will consider shopping only in those stores where the store image is congruent with benefits or ideal attributes sought by the shopper (Doyle and Fenwick 1974; Calantone and Sawyer 1978; Stephenson 1969). But Carman (1969) has suggested that shoppers with the same desired benefits may pursue different shopping strategies to achieve these benefits. Monroe and Guiltinan (1975) suggest the propensity to engage in purchase planning, information search, and budgeting may be function of general opinions about the benefits of shopping.

Shopping Strategies

Several researchers have included the concept of strategy in their investigations into information search and shopping behavior. Both Carman (1969) and Moschis (1976) related information search to shopping strategy. Shopping strategies represent sets of activities that reflect the motives and decision processes governing shopping behavior. These strategies tend to develop over time and reflect general procedures which buyers may adopt such as store loyalty (Carman 1969), brand strategy (Newman 1977; Bennett and Mandell 1969), and dealing or bargain strategies (Carman, 1969).

Summary of the Evidence

Despite the myriad findings, research methods, and approaches, it seems clear that shoppers do not behave similarly for similar types of goods. Some shoppers engage in search before and during shopping; others search for low-price alternatives, but do not necessarily shop more frequently, always prepare a shopping list, or check ads before shopping; and others seem to be motivated by convenience and do not "shop around". Therefore, additional research is needed on the multidimensionality of shopping behavior.


Data were collected from a mail survey panel conducted in three time periods; before, during, and after the introduction of a third major supermarket into a previously duopolistic market, over a 20-week period. Respondents were selected using every tenth name from the street lists of the towns in the market area. The first wave of the survey was conducted four weeks prior to the opening of the new store and approximately 550 (38%) responded. During the first 10 days of the store opening, the 550 respondents were mailed a second questionnaire. Forty-five percent or 250 replied during the second wave. Thirteen weeks later a third questionnaire was mailed and 169 households (67%) responded. The analysis reported in this paper is based on these 169 households who responded to all three questionnaires. These panel households represent approximately 12% of the original sample, and 31% of the first set of respondents.

The data collected included: a 38-item activity, interest, and opinion (AIO) seven-point agree-disagree questionnaire (Wave 1); ratings of the relative importance of 23 grocery store attributes, using seven-point scales for each item (Wave 1); general socio-economic data and grocery budget data (Wave 1); media and coupon usage data (Wave 3); perceived travel time and in-store shopping time (Wave 3); patronage data related to primary store shopped (Waves 1,2,3): and propensity and reasons for trying the new store (Wave 2).

The AIO variables were adopted from prior store patronage studies (Bucklin 1971; Darden and Ashton 1974; Reynolds, Darden, and Martin, 1974; Stephenson 1969) and from the psychographic inventory of Wells and Tigert (1971). The AIO's reflected a variety of search activities, including pre-purchase planning, search objectives, and opinions regarding the various benefits of shopping. Thus, they reflect the elements suggested in the literature from which multidimensional strategies might be derived. Respondents were asked to respond to each statement in terms of grocery shopping activities only. Ideal store attribute data. socio-economic data, and shopping behavior data were gathered to provide expanded descriptions of each group and to determine whether significant shopping behavior differences existed.


Since earlier research had identified shopping typologies, and had discovered that individual shoppers pursue different shopping strategies, the first task was to classify respondents into shopping groups. Group profiles were then developed for the purpose of isolating shopping strategies unique to each shopper group.

To develop a useful, nonredundant set of shopping strategies, a series of data reduction steps was taken with respect to the AIO items. First, 12 items with highly skewed distributions were eliminated from further analysis, then a factor analysis was performed on the remaining AIO's. Using a minimum eigenvalue of 1.0 and a screen test, a six-factor solution was derived. Based on an analysis of the items with highest commonalties, the six factors appeared to represent: recreational and social; in-store information; brand name; venturesome/innovator; bargain hunting; and planning and budgeting.

Since the objective was to define types of shopping strategies, 17 items were not considered further at this point in the analysis singe they represented household role and benefits of shopping variables. All remaining shopping strategy items were then correlated and a set of seven items was chosen to reduce the problem of redundancies in intercorrelated variables. The seven items retained did include the shopping strategy items which loaded high on each of the six factors. These items were:

1.  I like to shop in different stores just to see what is new.

2.  I budget a certain amount to spend on groceries each week.

3.  I shop a lot for store specials.

4.  I make my purchase selection according to my favorite brand name, regardless of price.

5.  I shop at the store(s) where my friends buy their groceries.

6.  Before grocery shopping I prepare a shopping list.

7.  I look for nutritional labeling information that is included on some grocery packages.



Respondents were cluster analyzed on the basis of similarity of evaluations on the seven strategy variables. Cluster analyses with two through ten groups were examined for the entire sample and for two split-half samples. A six-group solution was chosen in each split-half because going to a seven group solution did not materially reduce the ratio of within-groups sum of squares to total group sum of squares. Further, consistency of the two split-half groups was determined by correlating the mean scores on each of the seven items for each matched pair of groups from the two split halves (Calantone and Sawyer 1978). The average correlation coefficient was statistically significant (r = .828, p. < .003).

The first step in developing group profiles was to describe the groups in terms of the shopping strategies characteristic of each cluster. A one-way analysis of variance indicated that the degree of agreement varied significantly across the six groups. Ideal store attributes and the remaining AIO items were then analyzed across groups by a series of one-way ANOVA tests. Fifteen of twenty-three ideal store attributes varied significantly across groups at the .05 level or better. Seventeen of the remaining AIO variables were significant at the .05 level or better. Finally, demographic variations across groups were analyzed, Table 1 provides a summary of the shopping strategies characteristic of each group and of the demographic variations. Table 2 provides a summary of the ideal attribute, AIO, and demographic profiles of each group.



As indicated above, multi-dimensional shopping strategies appeared and were associated with a variety of attribute preferences, opinions about shopping, and demographic factors. The significance of employing a multi-dimensional approach can be shown by comparing several pairs of groups. For instance, the in-store economy group tends to confine information search to the actual shopping trip, whereas economy planners indicate a greater use of external-to-store information.

Similarly, while groups 3 and 5 might be viewed as "involved shoppers," group 3 appears to be more concerned with "value," venturesomeness, and social motives. By contrast, group 5 shoppers are more quality conscious and household-role oriented. Finally, groups 2 and 6 are similar in terms of a lack of planning and budgeting and in terms of brand name reliance. However, the convenience orientation of group six primarily reflects "in-store" and "accessibility'' factors. Members of this group are not necessarily disinterested in shopping, as they do shop for specials and are willing to try new stores. These contrasts suggest that simplistic, unidimensional shopping typologies may obscure the more complex strategies which consumers employ.

A number of the findings reported here are consistent with earlier research. For example, Appel's (1970) innovative shopper is similar to both the in-store economy and the economy planner shopper groups identified in this research. Similarly, Darden and Reynolds (1971), Kenny-Levick (1969), Stone (1954) and Williams (1978) identified an economic shopper group. However, a primary distinction discovered in this research is that economic shoppers can be separated further depending on types of information search and pre-shop planning. Unlike the in-store economy shopper, the economy-planner shopper uses both media sources as well as in-store information. This finding reinforces Moschis' (1976) result that shoppers do differ in terms of preferences and use of external information.

Darden and Reynolds (1971) and Stone (1954) both described an apathetic shopper that combined indifference or dislike for shopping with desires for convenience. However, Kenny-Levick (1969), Williams (1978), and this study have recognized distinguishing characteristics between the apathetic and convenience shoppers. The convenience shopper appears to be more pressed for time while the apathetic shopper dislikes shopping. Moreover, the convenience shopper is less likely to be store loyal. The personalizing shopper of Darden and Reynolds (1971), Stone (1954), and Kenny Levick (1969) have some similar characteristics of the homemaker group in this study. The homemaker group here does exhibit some positive feelings toward the social aspects of shopping. Doyle and Fenwick (1974) and Williams (1978) identified an older shopper group that is similar to the involved, traditional shopper of this study. In each instance, the shopping groups are not necessarily economy-minded, but show concern for variety, quality, as well as price.

The identified shopping strategies also have some similarities to previously reported strategies. The apathetic and homemaker shopping groups do use both brand loyalty and store loyalty strategies as suggested by Blattberg (1976). However, the economy planner group does not follow the strategy of being both store loyal and brand loyal, in that they cannot be typified as brand loyal. Blattberg (1976) also suggests that deal-prone shoppers are likely to visit several stores. In the retail market examined here, the economy planners use coupons and look for specials, but they do not like to change stores. On the other hand, the in-store economy group does visit several stores. The economy planners are similar to the careful shopper identified earlier by Carman (1969).


The variety of types of satisfaction entailed in the shopping process indicate that similar benefits may be achieved through alternative search patterns. Further, the fact that the shopping groups varied more dramatically on opinions and activity measures than on ideal store attribute preferences would suggest that perceived utilities of shopping may be more useful indicators of search propensity than desired store benefit structures.

Of primary significance, however, is the implication that attempts to understand consumer search processes can be more successful when multiple search strategies are considered and where these strategies are associated with a multi-dimensional array of beliefs, activities, interests, demographics, and behaviors.


Appel, David L. (1970), "Market Segmentation--A Response to Retail Innovation," Journal of Marketing, 34, 64-66.

Bennett, Peter D. and Mandell, Robert M. (1969), "Pre-purchase Information Seeking Behavior of New Car Purchasers--The Learning Hypothesis," Journal of Marketing Research, 6, 430-433.

Blattberg, Robert; Peacock, Peter, and Sen, Subrata K. (1976), "Purchasing Strategies Across Product Categories,'' Journal of Consumer Research, 3, 143-154.

Bucklin, Louis P. (1966), "Testing Propensities to Shop," Journal of Marketing, 30, 20-27.

Bucklin, Louis P. (1971), "Consumer Search, Role Enactment, and Market Efficiency," Journal of Business, 44, 69-72.

Calantone, Roger J. and Sawyer, Alan G., (1978), "The Stability of Benefit Segments," Journal of Marketing Research, 15, 375-404.

Carman, James (1969), "Some Insights Into Reasonable Grocery Shopping Strategies," Journal of Marketing, 33, 69-72.

Claxton, John; Fry, Joseph, and Portis, Bernard (1974), "A Taxonomy of Prepurchase Information Gathering Patterns," Journal of Consumer Research, 1, 35-42.

Darden, William and Ashton, Dub (1974-1975), "Psychographic Profiles of Patronage Preference Groups," Journal of Retailing, 50, 99-112.

Darden, William R. and Reynolds, Fred D. (1971), "Shopping Orientation and Product Usage Rates," Journal of Marketing Research, 8, 505-508.

Doyle, Peter and Fenwick, Ian (1974-1975), "How Store Image Affects Shopping Habits in Grocery Chains," Journal of Retailing, 50, 39-52.

Farley, John U. (1964), "Brand Loyalty and the Economics of Information," Journal of Business, 37, 370-381.

Katona, George and Mueller, Eva (1964), "A Study of Purchase Decisions in Consumer Behavior," Consumer Behavior, Lincoln Clark (ed.), New York: New York University Press, 30-87.

Kenny-Levick, C. (1969), "Consumer Motivations: Some Examples from the Grocery Trade," British Journal of Marketing, 3, 2-8.

Monroe, Kent and Guiltinan, Joseph (1975), "A Path-Analytic Exploration of Retail Patronage Influences," Journal of Consumer Research, 2, 19-28.

Moschis, George P. (1976), "Shopping Orientations and Consumer Uses of Information,' Journal of Retailing, 52, 61-70, 93.

Newman, Joseph W. (1977), "Consumer External Search: Amount and Determinants," Consumer and Industrial Buying Behavior, P. D. Bennett, J. N. Sheth, and A. G. Woodside, (eds.), New York: Elsevier North-Holland, 79-94.

Nicosia, Francesco (1966), Consumer Decision Processes, Englewood Cliffs, New Jersey: Prentice-Hall, Inc.

Reynolds, Fred; Darden, William; and Martin, William (1974-1975), "Developing an Image of the Store-Loyal Customer," Journal of Retailing, 50, 73-84.

Stephenson, Ronald (1969), "Determinants of Retail Patronage," Journal of Marketing, 33, 57-61.

Stone, Gregory P. (1954), "City Shoppers and Urban Identification: Observations on the Social Psychology of City Life," The American Journal of Sociology, 60, 36-45.

Tauber, Edward (1972), "Why Do People Shop?", Journal of Marketing, 36, 46-49.

Wells, William and Tigert, Douglas (1971), "Activities Interests, and Opinions," Journal of Advertising Research, 11, 27-35.

Williams, Robert H.; Painter, John J.; and Nicholas, Herbert R. (1978), "A Policy-Oriented Typology of Grocery Shoppers," Journal of Retailing, 54, 27-42.

Wright, Peter (1975), "Consumer Choice Strategies: Simplifying vs. Optimizing," Journal of Marketing Research, 12, 60-67.



Joseph P. Guiltinan, University of Kentucky
Kent B. Monroe, Virginia Polytechnic Institute and State University


NA - Advances in Consumer Research Volume 07 | 1980

Share Proceeding

Featured papers

See More


Self-Deprecation Signals Humility, but Not as Much as Self-Deprecators Assume

Clayton R Critcher, University of California Berkeley, USA
Michael O'Donnell, University of California Berkeley, USA
Minah Jung, New York University, USA

Read More


Do Altruistic Individuals "Share" More Contents on Social Media?

Travis Tae Oh, Columbia University, USA
Keith Wilcox, Columbia University, USA

Read More


O13. Pain of Loss: How Losing in a Promotional Competition Influences Consumer Attitude

Arash Talebi, ESSEC Business School
Sonja Prokopec, ESSEC Business School
Ayse Onculer, ESSEC Business School

Read More

Engage with Us

Becoming an Association for Consumer Research member is simple. Membership in ACR is relatively inexpensive, but brings significant benefits to its members.