Deriving Wine Marketing Strategies By Combining Means-End Chains With an Occasion Based Chaid Segmentation Analysis

ABSTRACT - In this paper we attempt to address three issues: first to investigate the suitability of using situations as a segmentation base, secondly to assess the importance and role that values play in this segmentation process and thirdly to assess the effectiveness of CHAID as a segmentation methodology when using means-end chain analysis. The paper first reviews the literature on situation or occasion-based behaviour and means-end research. A brief summary of the interview process for the data collected based on wine consumption occasions is provided before the analysis is discussed. The paper concludes by discussing the theoretical and managerial implications of this research.


John Hall, Peter P. Oppenheim, and L. Lockshin (2001) ,"Deriving Wine Marketing Strategies By Combining Means-End Chains With an Occasion Based Chaid Segmentation Analysis", in E - European Advances in Consumer Research Volume 5, eds. Andrea Groeppel-Klien and Frank-Rudolf Esch, Provo, UT : Association for Consumer Research, Pages: 82-89.

European Advances in Consumer Research Volume 5, 2001      Pages 82-89


John Hall, Victoria University, Australia

Peter P. Oppenheim, University of Ballarat, Australia

L. Lockshin, University of South Australia, Australia


In this paper we attempt to address three issues: first to investigate the suitability of using situations as a segmentation base, secondly to assess the importance and role that values play in this segmentation process and thirdly to assess the effectiveness of CHAID as a segmentation methodology when using means-end chain analysis. The paper first reviews the literature on situation or occasion-based behaviour and means-end research. A brief summary of the interview process for the data collected based on wine consumption occasions is provided before the analysis is discussed. The paper concludes by discussing the theoretical and managerial implications of this research.


The goals of this paper are three-fold: first to investigate the suitability of using situations as a segmentation base, secondly to assess the importance and role that values play in this segmentation process and thirdly to assess the effectiveness of CHAID as a segmentation methodology when using means-end chain analysis. The paper first reviews the literature on situation or occasion-based behaviour and means-end research. A brief summary of the interview process for the data collected based on wine consumption occasions is provided before the analysis is discussed.



Situational influences have a theoretical foundation in Lewin’s field theory (1936) and the modern interactionism conception of human behaviour. These perspectives asserted that human motivations, intentions, and behaviour are a function of the interaction between consumers and situations. According to these theories different individuals view their physical and social settings somewhat differently.

A limited number of researchers have investigated situational factors as a determinant of choice behaviour. Sandell (1968) presented subjects with an inventory of beverages and found that personal differences and differences in situations, considered separately, were poor predictors of product preference. Their interaction, however, provided a better predictor of beverage preference. The same type of interaction between product choice and usage situation was found by Green and Rao (1972), Belk (1974), and Srivastava, Shocker, and Day (1978). In a later study, Srivastava (1980) examined the appropriateness of financial services in a particular situation and found it to be relatively stable across situations, thus providing further support for using consumption situations as a basis for segmenting the market. Dickson (1982) combined these previous studies into a call for more research after creating a person/situation segmentation model. Dubow (1992) compared occasion-based and user-based segmentation for the wine market in the US and concluded that the occasion-based segmentation was richer and more relevant for brand positioning and advertising strategy.

It is evident that there is merit in including product characteristics, consumer characteristics and specific situations in a combined analysis. Although little conclusive research has been reported in using consumption situations to groups of consumers, the above review indicates that adding situations to either product or consumer characteristics may improve the predictive nature of such market clustering techniques.


Values are responsible for the selection and maintenance of the ends or goals toward which individuals strive (Vinson, Scott and Lamont 1977). A value is a centrally held, enduring belief which guides actions and judgements across specific situations and beyond immediate goals to more ultimate end states of existence (Kamakura and Mazzon 1991). Various combinations of values significantly differentiate individuals (Rokeach 1968). Personal values have a major influence on a person's lifestyle, interests, outlook and consumption priorities and therefore can play an important role in the development of strategies to understand markets (Muller 1991).

Studies using value orientations to enrich the segmentation process have become increasingly popular (Boote 1981; Holman 1984; Kahle 1986; Muller 1989, 1991; Kamukakura and Novak 1992; Blarney and Braithwaite 1997; Thrane 1997; Jago 1998). The most frequently used instrument for measuring values is the Rokeach Value Survey which consists of 18 instrumental values and 18 terminal values (Kamakura and Mazzon 1991). The List of Values (LOV) developed by Kahle (1983) modifies Rokeach's scale of terminal values into a smaller set of nine primarily person-oriented terminal values more directly related to a person's daily life roles and situations (Beatty et at 1985; Kamakura and Mazzon 1991) and as such, it has been utilised in a variety of segmentation studies (Kahle 1986; Muller 1989, 1991; Kamakura and Mazzon 1991; Kamukakura and Novak 1992; Blarney and Braithwaite 1997; Jago 1998). In order to identify values and value chains, means-end analysis (Gutman 1982, Reynolds and Gutman 1988) provides a methodological approach used for identifying values as well as the attributes, benefits and consequences related to these values.

Means-end Chains

The means-end chain is a conceptual model that relates salient values of the consumer with evaluative criteria (attributes) of the product (Howard, 1977; Vinson, Scott, & Lamont, 1977; Gutman, 1984). The model offers a procedural guide that establishes linkages connecting values important to the consumer to specific attributes of products, through psycho-sociological and functional benefits called 'consequences. A sequence of in-depth probes traces the network of connections or associations in memory that eventually lead to values. This laddering process is accomplished by asking a "Why is that most important to you?" question at each level and uses the response as the basis for the next probe. The process continues until both a consequence and a personal value are elicited from the consumer, or the consumer has no further answers to the probes (Reynolds and Perkins 1987). Gutman's original model (1982) used situation in the theoretical description as one part of the matrix. Situation was deemed an input to the process of consumer decision-making. However, in various empirical examinations of the model, situation was not included (Reynolds and Gutman 1984; Reynolds and Gutman 1988; Gengler and Reynolds 1989). This research proposes to use situation instead of product or brand as the central focus of the means-end analysis.

Market Segmentation

Market segmentation is the process of partitioning a heterogeneous market into segments. The various segments that are identified should be homogeneous within themselves with respect to critical marketing variables, but heterogeneous in total. Market segmentation may be accomplished using a variety of methodologies (see Struhl (1992) for a review). A frequent problem of using inappropriate marketing variables to partition the total market has been noted by Riquier (1997) who states that variables used as a basis for segmentation are often chosen for their availability, or exotic nature, rather than their relationship to differences in buyer preference. A preferred approach to segmentation therefore requires consumers to be classified into groups according to their likely response to some marketing stimulus, rather than background variables such as age or gender. In this study occasion is used as an a priori basis for segmentation and the factors associated with wine choice are investigated to determine the category of factors that drives wine choice on various occasions.

CRAID Analysis

To determine the factors that drive choice a segmentation modelling approach was adopted. Wine choice for various occasions acted as a convenient dependent variable to guide the segmentation process. Wine is a useful category for segmentation studies, because it offers a wide set of prices, product characteristics, and usage situations. Personal values, consequences and attributes of wine acted as predictor variables. Implementation of the CHAID algorithm operationalized this analysis. CHAID (Chi-squared Automatic Interaction Detector) is a multivariate criterion-based approach to cluster analysis (Magidson 1993). The CHAID algorithm assumes that the population represents a heterogeneous grouping with respect to some dependent variable and divides the population into two or more distinct groups based on the categories of the most significant predictor variable. Statistical significance is measured using the chi-square test of independence. CHAID assesses each of the predictor variables based on the appropriate chi-squared significance test. The categories of the most significant predictor are used to divide the sample into subgroups. Then the next most significant predictor is identified and used to split the subgroups again. Any subgroup, which cannot be further subdivided, because there are no other significant predictor variables or because some user-defined stopping rule is met, becomes a terminal subgroup or segment (Magidson 1993). The CRAID algorithm therefore effectively performs segmentation analysis by dividing the sample population into segments that differ with respect to a designated criterion. In addition the CHAID procedure has the advantage that it also identifies those factors that are most significantly related to the criterion under consideration, in this case -occasion.


This study is based on a sample of wine buyers and was conducted in Melbourne Australia. The product selected for this study is wine. Previous research in occasion-based segmentation has shown that wine is chosen and consumed for different reasons in different situations (Dubow 1992; Lockshin, McIntosh and Spawton, 1997). Wine has a wide variety of attributes and as shown by Dubow (1992), a number of different consequences and values associated with its use. Therefore, the means-end approach adopted for this study used occasion as a factor for each ladder, rather than brand as in previous research. Indeed the seminal article in the means-end chain literature relies on data collected about wine coolers (Reynolds and Gutman, 1988).

A sample of 233 respondents was interviewed using a means end analysis procedure. A convenience sampling approach was used. Respondents were required to be over 25 years of age and to have consumed the wine, which they had purchased in the last three months. The survey was administered in Melbourne, Australia. The interview schedule was based on the identification of personal values, consequences and values which provided an underlying structure for the in-depth interviews. Trained interviewers were asked to follow the means-end procedure for a specific purchase and consumption situation (some respondents discussed the last two occasions). The interviews thus produced 648 ladders for 356 occasions. Attributes, consequences and values were identified through the inter-viewing process and confirmed by independent researchers. A realistic representation of age and gender was obtained from the sample. In addition as the and respondents had purchased a variety of both red and white wines, responses were not biased by being wine type specific.


The 356 individual consumption occasions were aggregated into eight specific occasions that summarised and reflected the occasions presented by respondents (Table 1). All three researchers independently classified the individual occasions into the categories. Differences were resolved through discussion. Based largely on the work of Rokeach (1973) the nine terminal values developed by Kahle (1983) were used to measure personal values in this study. The nine personal values are: Fun and enjoyment in life, Being well respected, Warm relationships with others, Self-fulfilment, Security, Self-respect, Sense of belonging, Sense of accomplishment, and Excitement. The values elicited from the respondents were coded to reflect those of the LOV scale.

Most frequently cited attributes, consequences and values

Respondents were asked what had influenced their selection of a particular wine for a particular occasion. Following the interviews, the attributes were categorised. Table 2 shows these categories and the number of chains on which each attribute occurred. Taste (n = 285), price (n = 22 1), type (n = 215), and brand (n = I 11) were the attributes of wine most frequently listed.

Table 3 lists the consequences identified and the corresponding number of ladders. A number of consequences were frequently suggested as a result of attributes associated with selected wines. Selected attributes were indicators of quality - a consequence appearing in most means-end chains (n = 212). Other frequently cited important consequences included: Socialise(n= 168),Complement Food (n = 135), Impress Others (n = 131), Value for Money (n = 123), and Mood Enhancement (n = 118).

Table 4 lists the values (from the LOV Scale) and corresponding number of ladders. All values except Excitement (n = 6) and Sense of Accomplishment (n = 35) were well represented. Fun and enjoyment in Life (n = 226) was the most represented value on the means-end chains. Other popular values were: Being well respected (n = 148), Warm relationship with others (n = 121), Self fulfilment (n = 119) and Security (n = 109).

To identify more specifically the factors associated with occasion based consumption of wine, a CRAID analysis was conducted using the buying occasion variable as a binomial dependent variable and the entire set of value, consequence and attribute statements as predictor variables. SPSS Answer Tree' 2.0 was used to estimate a CHAID Tree for each occasion. To illustrate the nature of the results obtained, three of the resultant trees obtained from the analysis of the eight occasions are included in this paper. The initial node at the top of the tree diagram contains a frequency distribution for the binomial occasion variable.









For example in Figure 1, the total number of individual responses (ladders) equalled 648. Of these respondents 62 had purchased wine for an intimate dinner within the previous 12 weeks. The CHAID procedure then identified the most significant variable that discriminated between those respondents that had and those respondents that had not purchased wine for this occasion. In this instance the value "A warm relationship with others" is identified as being the most significant (p=0.0001; Chi square=14.97; df=1). Using this variable the CHAID procedure then divides the population into two groups; group 0 being respondents that had not identified "A warm relationship with others" as being appropriate and group 1, as those respondents who had identified "A warm relationship with others" as being appropriate.



As a result of this division 23 respondents are identified as having both purchased wine for an intimate dinner and responding positively to the value statement "A warm relationship with others". These respondents account for 18.85 % of the 122 respondents who felt that a warm relationship with others was important. In a similar way this group is then divided by the CHAID algorithm according to responses to the next most significant variable, in this case the value of "Self-fulfilment". Finally as a result of the second division a third division occurs using the third most significant variable, a consequence "Complements Food". Following this division, inspection of the terminal nodes reveals that there are two nodes or segments with relatively concentrated representations of "Intimate dinner" consumers, one node has 44.44% of the node's respondents while the other node has 31.03% of the node's respondents.

The results displayed within the CHAID tree can now be used for two purposes. First, if the objective of this research was to target "Intimate dinner" consumers it would now be appropriate to profile the respondents represented within these nodes in order to devise a targeting strategy as these nodes provide the greatest probability of reaching "Intimate dinner" consumers. On the other hand if the objective of this research was to identify the variables that most significantly discriminates between "Intimate dinner" consumers and "non-intimate dinner" consumers, the tree clearly shows that various values are of primary significance followed by a consequence. It should be noted that the relatively small numbers of sample respondents in the terminal nodes is not necessarily of concern as our objective at this point is to identify discriminating variables as opposed to market targets.

Inspection of the remaining CHAID trees revealed a consistent pattern, in virtually all occasion based CHAID trees, values were found to be of primary significance in discriminating between occasion based wine purchases. Various consequences were invariably of secondary importance while attributes were ranked in third place.



For example, using a different situation, the business related occasion, the most important factor discriminating between those who purchased wine for a business related occasion and those who did not, was the value, "Being Well Respected". Another value "Security" differentiates between those whose ladder had the value, "Being Well Respected" and those that did not. As in the previous analysis, a consequence, "Avoiding Negatives" in this case, discriminates between those who had the value, "Security" and those that did not.

Figure 3 shows that the third occasion also results in a value as being the most significant segmenting variable between those that consumed wine for this occasion and those that did not. "Fun and Enjoyment in Life " not surprisingly was the value that was most significant on this occasion. It was followed by the consequence, "Complement Food" which itself was delineated by another consequence, "Sense of Belonging ".


The results of our investigation using CHAID to develop segments from wine drinking occasions and associated means-end chains has shown that higher order personal values are the best discriminator between different occasions. This adds to our knowledge that values can be used for segmentation (Kahle 1986; Muller 1989,1991; Kamakura and Mazzon 1991; Kamukakura and Novak 1992; Blarney and Braithwaite 1997; Jago 1998). Our work extends this usage to situations rather than individuals. Research on wine has shown that the same person often buys low priced and high priced wines (Lockshin, Spawton and Macintoch 1997). We are better able to account for the fact that the same person often purchases different products by associating the purchase with different usage occasions. Contrary to previous situation research, which focused on the product attributes and situation for segmentation (Green and Rao 1972; Belk 1974; Srivastava, Shocker, and Day 1978; Srivastava 1980; Dickson 1982), our work has found that personal values are a better predictor of the usage situation. The same person typically has multiple terminal values (Kahle 1983), but the importance of each in driving product choice changes with the situation.

The means-end chain approach for eliciting attributes, consequences, and values has been used to develop positioning and advertising messages for differentiating specific brands (Reynolds and Gutman 1984; Reynolds and Gutman 1988; Gengler and



Reynolds 1989). The same method can be used to develop positioning and advertising platforms for individual brands for specific occasions. For example, a wine can be positioned as a serious and risk free choice for that important business dinner by visually showing the purchaser achieving respect and assurance for making the right choice of wine. A different wine could be positioned as the perfect drink for that BBQ or picnic by showing the fun and enjoyment inherent in that occasion along with a perfect match for the foods being served. As Reynolds and Gutman (1988) showed in their article, a powerful positioning statement can be made by showing the attributes, consequences, and values linking the brand by means of the most common ladder. The consumers viewing such an ad feel comfortable associating the product with the desired end state values being demonstrated. Our research validates the depiction of specific usage situations along with the means-end chain as a more powerful positioning tool.

Another use for the segmentation we have provided is at the point of purchase. The salesperson in a wine shop or waiter in a restaurant can ascertain the situation for which the wine is being purchased. This can be done through simple questioning in a wine shop or often by observation in a restaurant. It is then possible to suggest the right choice of wine by alluding to the value associated with the situation at hand. For example, a waiter may observe an intimate dinner occasion and suggest a wine that accentuates the mood and feeling by complementing the food and at the same time providing that 'warm' feeling.

Our contribution should be evaluated in light of the limitations of this particular research. We have only analysed data for one product category in one major city. Other product categories should be tested before usage situation and terminal values are used indiscriminately for segmentation. It is possible that wine choice behaviour differs in other countries outside Australia and this research should be replicated elsewhere. The sample was a convenience sample of wine drinkers. Although, it had a wide range of demographic characteristics, such as age, income, and amount of consumption, it may not represent Australian wine drinkers on average. Future research might seek to address these issues and build upon them. For example, a series of products might be examined within a number of different cultural contexts.

We have demonstrated the use of personal values as a segmentation variable for distinguishing among products used for different occasions. Our contribution is threefold: first we provide evidence that segmenting on the basic of usage situation is both useful and feasible; second, we show that means-end chains can be used in a CHAID analysis to create the segments; and finally, we found that personal values are the most powerful segmenting variable across the different usage situations.


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John Hall, Victoria University, Australia
Peter P. Oppenheim, University of Ballarat, Australia
L. Lockshin, University of South Australia, Australia


E - European Advances in Consumer Research Volume 5 | 2001

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