Marketing Action Based on Consumer Decision Processes: the Case For Micro-Behavioral Simulation

ABSTRACT - This case history describes how a number of sophisticated methodologies were brought to bear upon the strategic issues facing an established brand, and how results were eventually implemented by management. The research design was based on the SCIMITAR Research system. Techniques discussed include Conjoint Measurement, Correspondence Analysis, Brand Progress Analysis, Brand Impact Analysis, Hierarchical Cluster Analysis, and Micro-Behavioral Simulation.


Richard A. Westwood and Harry S. Sunenshine (1981) ,"Marketing Action Based on Consumer Decision Processes: the Case For Micro-Behavioral Simulation", in NA - Advances in Consumer Research Volume 08, eds. Kent B. Monroe, Ann Abor, MI : Association for Consumer Research, Pages: 332-337.

Advances in Consumer Research Volume 8, 1981      Pages 332-337


Richard A. Westwood, The Beaumont Organization, Ltd.

Harry S. Sunenshine, Heublein Inc.


This case history describes how a number of sophisticated methodologies were brought to bear upon the strategic issues facing an established brand, and how results were eventually implemented by management. The research design was based on the SCIMITAR Research system. Techniques discussed include Conjoint Measurement, Correspondence Analysis, Brand Progress Analysis, Brand Impact Analysis, Hierarchical Cluster Analysis, and Micro-Behavioral Simulation.


Designing medium-term marketing strategy poses difficult challenges for researcher and manager alike. By its very nature, strategic design demands that several facets of the current and future market be synthesized within an action plan -- including for example, immediate and more distant competitive frames; potential cannibalization between company brands; and the vulnerability of strategies to competitive response.

In attempting to deal with such broad ranges of issues, traditional research methods have generally adopted abstract views of the market. Psychographic segmentation provides a current, and popular, example of this type of abstraction. But, although abstract research results are often fascinating and insightful, their translation into action decisions tends to be vague and ambiguous. On the other hand, more specific and directly actionable methods run the risk of lacking generalizability, even of being trivial to the issues facing the strategic designer.

A number of technically advanced research methods, in particular micro-behavioral simulation, offer more powerful ways to approach strategic issues. The primary appeal of simulation lies in its ability to be sufficiently specific to relate directly to decision making yet, at the same time, sufficiently flexible to encompass a wide range of issues and contingencies.

This case history discusses how several sophisticated techniques, including simulation, were used to design strategy for a Heublein brand. The particular methodology described is Beaumont's SCIMITAR system, which comprises a suite of data gathering, analytic, and simulation approaches. Central to this system is the use of a model of the consumer brand choice process to integrate perceptual data with Conjoint Measurement, leading to several powerful analysis and simulation possibilities.

At the time of publication, early phases of the strategy have already been successfully implemented. Other aspects of the plan will be deployed in the future and, accordingly, the overall strategy remains confidential. In order to safeguard Heublein's security interests, while presenting data that have integrity for the research audience, this paper adopts the expedient of changing labels. The market under discussion, its attributes, and the key demographic groups, have been disguised. In the main, the actual results reported have not been changed, except in those few cases where they would permit the alert reader to infer which of Heublein's markets is the subject of this discussion


For a number of years, Heublein's brand had dominated the packaged goods category that was its primary source of business. Although two major national competitors existed, much of the remaining competition was limited to several small regional brands that were unable to dislodge the Heublein brand from its brand leader position in their markets.

More recently, the brand had begun to mature. Concurrently, its product category was becoming increasingly competitive. Where there had been one or two major brands, there were now four or five, some of whom posed serious competitive challenges.

Complicating matters, the competitive frame was by no means clear-cut. Although Heublein's brand belonged to a product category that was clearly definable in manufacturer terms, it also appeared to compete with members of certain other categories. The fact that some of these adjacent product categories were growing more rapidly than Heublein's brand, or its immediate category as a whole, suggested that they might be limiting its opportunities.

Given the pressures upon its brand, management faced a two-fold challenge: to mount an effective defense against the recent, and vigorous, immediate competitors; and to create new growth at the expense of adjacent product categories. There was a need for research that would identify how Heublein might achieve these goals.


It was clear that descriptive research methods would not be sufficient to address these objectives. Instead, it would be necessary to explain the process whereby consumers made their brand choice decisions, and to predict how these decisions might be changed by a variety of marketing actions.

The SCIMITAR research system was adopted for this research because it provided such a focus on the consumer decision process. The methodologies within the system were used to construct a three-component research program.


The three components within the overall research program were as follows:

Preliminary Qualitative Research was conducted to provide the basis for questionnaire design.

An Immediate Category Study was the largest scale component within the research program, reflecting management's prioritization of the need to regain ground that had been lost to recent competitors, and to strengthen its brand against further attack.

A Total Market Perceptual Study was conducted in order to reveal the broader competitive perspective, and to be able to assess the more general implications of strategic actions.


The preliminary phase of a strategic research program is the foundation upon which all subsequent results are built, and as such is to crucial to project success.

As a first step, all pertinent past research was reviewed. This review was then augmented by qualitative Protocol Interviews with 16 individuals, including a variety of demographic and behavioral consumer types.

Protocol Interviews are a depth research methodology, designed to probe the brand choice process by having individual respondents perform a series of "choice tasks". For example, one task requires respondents to make a brand choice from seven blank packs, using the interviewer as a totally reliable information source. The interviewer uses each session to elicit the information used in brand choice decisions, the form in which information is cognitively structured, and the manner in which it is processed. The parameters appearing in individuals' choices are then generalized, and re-expressed in questionnaire form.

The semantic and conceptual structures within a strategic questionnaire act as a common language between the manufacturer and the market. To be effective, they must be capable of translating manufacturer concerns into consumer terms, and vice versa. Accordingly, consumer variables derived from the exploratory research were tested against management's own decision criteria. This resulted in some minor modifications to the questionnaires, including the addition of two attributes to the list of market descriptors.


In this, the central component of the research program, 1,000 category users were interviewed in their own homes. using a 90 minute questionnaire. Based on the fact that differences between men and women were known to be important in the market, the sample was structured into two representative samples of 500 men and 500 women respectively.

The questionnaire was based on SCIMITAR methodology, which has been discussed in detail elsewhere (see Beazley and Westwood, 1976, Palmer and Westwood, 1976) and is therefore reviewed here only briefly.

In essence, the methodology reconstructs respondents' choice behavior, based on measurements of their requirements from the product field, and their perceptions of brands.

Conjoint Measurement is employed to measure requirements from the product field, using the approach discussed in Westwood (1973). The respondent states "trade-offs" between pairs of attributes, providing data that indicates the utility he derives from each attribute, and how he processes the attribute when making choices. The respondent also rates several brands across the same list of attributes. Conjoint and brand rating data are integrated at the individual respondent level, thereby explaining current choices, and simulating new choices under changing conditions.

22 attributes, derived from the Preliminary Qualitative Research, were investigated in the questionnaire. Additionally, extensive data ware gathered regarding each respondent's purchase and usage behavior, demographics, and psychographics.

Role of the Heavy User

Analysis of usage patterns revealed heavy users to be extremely important to the product category, 75% of all consumption being accounted for by only 28% of consumers.

Furthermore, these heavy users tended to be demographically distinct and hence directly approachable through marketing action. For example, they were much more prevalent among men than among women. Based on this finding, much of the subsequent analysis focussed on the heavy user: In particular, how to attract him to Heublein's brand.

Brand Progress Analysis

The extent of the threat posed by recently launched national competitors was gauged using Brand Progress Analysis. This simple, but effective, analysis of brand strength pictures sales results in terms of a flow of consumers between various experiential states -- from lack of awareness to awareness; from trial to acceptance; etc. In the current application, it was used to diagnose the limits to each major competitor's growth.

Among heavy category users, Heublein's brand compared to one of its newer national competitors as follows:



While Heublein's brand still benefited from higher awareness levels, the competitor appeared to be able to match its trial and acceptance levels once awareness had been developed, and was superior in converting occasional users to regular users.

It appeared that this competitor had the potential eventually to gain brand leadership among heavy users, provided that it could increase its awareness level while simply maintaining its performance in other respects. Comparison of share patterns among consumers aware and unaware of the brand tended to confirm this finding:



Brand Progress Analysis had revealed a major competitive threat, especially among the heavy users who had been shown to be of major importance to the category. Heavy users who became aware of the new competitor accorded it them majority of their usage. Unless countered, this brand could be expected to make significant inroads into the core of category volume, largely at Heublein's expense.

Management's prioritization of defensive strategy was thus strongly endorsed by research findings, and attention was now focussed on how such a strategy might be developed.

Consumer Wants

The logical starting point for strategic development is the examination of the factors that determine consumers' brand choices. In this study, the importances of choice criteria were measured in terms of utility scores derived from Conjoint Measurement. Figure 1 displays the overall utilities attached to various attributes by the average consumer:



Similar analyses were conducted within demographic and behavioral groups, and significant differences were found. For example, heavy users were shown to attach considerably more importance to children's enjoyment of the product-a factor that Heublein had not promoted actively, but that was a central aspect of a growing competitor's positioning. Attributes such as naturalness and wholesomeness, that had been the basis of recent Heublein advertising campaigns, were less important to heavy users.

Satisfaction with Brands

While the analysis of consumer wants showed what was important to consumers, and provided first suggestions regarding. how the market segmented, it did not reveal where leverage might exist against current competition. Accordingly, Brand Impact Analysis was used to combine utility and brand rating data, and thereby to reveal the extent of "unfulfilled utility" remaining within each attribute.

Figure 2 provides an example of Brand Impact Analysis, referring specifically to Heavy Users' images of the brands they consume regularly. The overall length of each bar represents the total utility associated with a particular attribute; the shaded portion shows the extent to which brands currently satisfy consumers' wants; and the remaining unshaded area reveals the extent of unfulfilled utility within the attribute. Thus, an attribute displaying a sizeable unshaded area would comprise a vulnerability of current brands that might profitably be attacked.



Trend Impact Analysis revealed a high degree of product satisfaction among heavy users. It suggested that major share gains could not be expected to result from improvements on isolated individual attributes, since these would not provide a compelling point of superiority. Significant leverage might only be possible if images were shifted on several attributes in concert.

Other Brand Impact Analyses, among various brand user groups, showed that the users of major competitors perceived a number of disadvantages in Heublein's brand. These could, in the main, be attributed to known aspects of product formulation, and their rectification was made an immediate marketing priority.


The Total Market Perceptual study was conducted to investigate the nature and extent of inter-category competition. In-home interviews were conducted among a representative sample of 350 respondents. The questionnaire required respondents to assemble 32 brands into groups of potentially substitutable items; to indicate which brand groups were suitable for use in each of a list of 21 situations; and to indicate which attributes were associated with each brand group. Volume usage data were also gathered for each situation.

The resultant data were subjected to a variety of multivariate and multidimensional scaling analyses, of which two are discussed below.

Market Structure

Johnson's Hierarchical Cluster Analysis was applied to the brand grouping data to determine the consumer's categorization of the market, providing a "family tree" of brand relationships as illustrated in Figure 3.



In general, the results suggested that consumers classified brands in much the same way as manufacturers. Thus, the primary competition to Heublein's brand was the immediate product category as the company had traditionally defined it. However, there were also some surprises elsewhere in the market structure. For example, two product categories that shared certain key ingredients, but that had previously been regarded as distinct, were shown to be highly substitutable, and virtually a single product category from the consumer standpoint.

Usage Patterns

The fact that brands and products belong to different perceived categories should not be taken to imply that they are non-competitive. Danish pastry and sausages belong to different categories, but compete for usage at breakfast. Taxis and bicycles are different products, but the consumer may choose between them during a transit strike. In general, categories that consumers regard as distinct may nonetheless compete within particular usage situations.

In the current study, patterns of cross-category competition were revealed by applying Correspondence Analysis to the 'brands by situations' data referred to above. This analytic method, analogous to both multidimensional scaling and principal components analysis, plotted brands and situations into a single space, as illustrated in Figure 4.



Like its major competitors A and B, Heublein's brand was found to be positioned towards a few high-volume situations (3, 8, and 5). However, within this positioning, its usage skewed towards the 'special purpose' Situation 5 rather than to the more mainstream Situations 3 and 8. Short term volume gains appeared to be possible if the brand could become more competitive in mainstream contexts.

Taking a longer term perspective, the Correspondence Analysis suggested that major gains might derive from a strategy that moved Heublein into more direct competition with Brands H, L, and N. These brands were regarded by both management and consumers as a separate product category. Their very heavy consumption derived from a wide range of usage situations which offered little volume usage individually, but a major opportunity cumulatively.

Approaches that might reposition the Heublein brand against new usage contexts were explored by superimposing attribute ratings data on the map shown in Figure 4. The resultant map suggested several approaches that could contribute to a more effective defensive positioning, including attention to those attributes where competitors' users perceived Heublein's brand to warrant improvement. A different set of considerations seemed relevant to expansion into new high volume opportunities.


While the Immediate Category Study had revealed some defensive needs and some possible approaches to a heavy user strategy, it had also suggested that a successful strategy would probably require a number of mutually supportive elements. The Total Market Perceptual Study had reinforced these findings, and furthermore suggested that longer term expansion might imply different actions than shorter term defense.

In a traditional market study, these results would have concluded the project. Furthermore, the study would have been deemed a success in research terms, since it had hypothesized several promising directions for management consideration. However, in our view, data analysis --even sophisticated multivariate analysis -- is not sufficient to address management concerns. As a case in point, the analyses in the current study had not provided a firm basis for evaluating alternative strategies, or for assembling them into coherent marketing programs. If it is to be truly actionable, strategic research must proceed one step beyond data analysis, and use other approaches to provide definitive statements regarding the corporate implications of each strategic possibility.

The methodology used for this study made such a next step possible. Through micro-behavioral simulation, it offered the ability to evaluate a virtual infinity of possible strategies. This simulation capability was an especially powerful feature of the research program, enabling broad directional hypotheses to be translated into specific action plans that could be acted upon directly.

The technical details of SCIMITAR's simulation approach are beyond the scope of the current paper, and are dealt with thoroughly elsewhere (see Beazley and Westwood, 1976, Palmer and Westwood, 1976). We shall therefore make only a few general explanatory remarks.

The SCIMITAR simulation model is a planning tool that tests strategic ideas through "what-if questions" addressed to a data base held within the computer. The user can create new brands, delete brands, and change brand perceptions inside the computer, which provides estimated results in terms of share potential, target group, and source of business.

Internally, the model operates by first "imitating" the ways in which individual respondents make brand choices, then aggregating individual responses into estimates of market potential. The simulation of individual respondent choice is based on the integration of brand image and utility data through a series of "decision rules" that replicate simple human thought processes:

1. Which brands is the respondent aware of?

2. Do any brands have completely unacceptable characteristics? (If so, reject them.)

3. Is any remaining brand unique in having an advantage on any important attribute? (If so, accept it as the predicted choice.)

4. Are any remaining brands inferior on the moat important screening criterion; the second; and so on? (if so, screen them out of the set under consideration.)

5. What is the total utility associated with the attributes of each remaining brand? (Select brand with highest utility.)

Simulation runs were used to test the implications of a wide variety of image changes -- first on single attributes, then on several attributes together. The results of some of the simulations based on single attributes are shown in Table 3



Several of the simulated changes replicated strategies that had previously been test marketed, and the results accorded well with the company's experience. As is customary in SCIMITAR projects, the simulation model had already been validated internally in terms of its ability to reconstruct the current brand choices of individuals interviewed, with satisfactory results. But the external validation against historical events, was, perhaps, a more profound test of the model, and the management credibility it generated was of great assistance in implementing the model's recommendations concerning new strategic possibilities.

Simulation results provided clear confirmation of one of the major hypotheses previously emerging from data analysis showing that Heublein's competitive position would not be improved dramatically by an isolated action on any single market dimension. In passing, we might note that this is by no means a typical result from the model, which often identifies individual attributes with significant competitive power (see, for example, Colvin, 1976, Gunter and Beazley, 1976).

Since no single attribute changes provided promising market potential, the simulation model was next used to test various attribute combinations that could be assembled within a brand strategy. Table 4 displays the results of some of these simulation runs.



It was apparent that, although strategies based on single attributes ware unlikely to be effective, certain combinations of attributes appeared to offer sizeable opportunities. This, of course, was a major finding in its own right, stressing the need for management to move away from individual tactical changes, and towards an integrated program of strategic activities.

More specifically, the model was able to point to the particular combinations of actions that would be expected to maximize market impact. For example, rectification of the defects that had been found in the brand's image among competitors' users was shown to offer good results, especially if incorporated with certain new benefits.

Simulation produced particular dramatic findings regarding overall business development, revealing that it was possible to merge shorter and longer term objectives within a single brand plan. Some of the attributes relevant to expansion beyond the current competitive frame were also found to be powerful within the more narrowly defined immediate category, provided that they were made part of a broader program.

Thus, through its use of market simulation, Heublein was able to develop a coherent multi-component strategy, that could be phased over time in a way that would build progressively more impact on the market. Early strategic phases would be concerned primarily with defensive considerations within the brand's immediate product category. These early phases, however, would pave the way for subsequent actions that would expand the brand's competitive horizons, and create the preconditions for new growth.


Although we have necessarily simplified and disguised this case history, we hope that we have communicated its considerable value to Heublein's strategy development.

For the future, we anticipate that Heublein's strategic research will continue to be firmly centered on consumer decision processes, and that attention will broaden beyond the issue of brand choice to embrace the full set of decisions that consumers make -- including whether or not to purchase a category, how often to purchase it, and so on. This behavioral focus seems to us to be the natural and proper approach to strategy, since all marketing actions seek ultimately to influence consumer decisions in one respect or another. The recent advances in Information Processing Theory offer a framework, and to some extent a set of methodologies, that are suited to this purpose.

Furthermore, we expect that micro-behavioral simulation will continue to feature prominently in Heublein's attempts to understand how it can influence markets. Simulation promises to take research an important next step in its progress from description to explanation and eventually to prediction. It produces results in a form that is definitive, rather then vague and ambiguous, a form, furthermore, that is readily understood and implemented by management. Most importantly of all, it enables the strategy designer to move beyond the bounds of the problem at hand to a wider exploration of the multiple issues facing a brand in the real world.


Beazley, D., and Westwood, R. A. (1976) "Modelling Choice Behavior," Proceedings of the Market Research Society Annual Conference, 79-92.

Colvin, M. (1976), "Market Modelling at Ford," Paper presented at the Market Research Society Seminar on Market Modelling, Banbury, Oxon, UK. (Copies available from the authors.)

Gunter, Pieter, and Beazley, David (1976), "An Application of Micro-Simulation Modelling to the Marketing of a Consumer Durable," Proceedings of the ESOMAR Annual Conference, Special Groups, 629-649.

Palmer, J. B., and Westwood, R. A. (1976), "Designing Advertising Strategy - the New Technology," Proceedings of the Advertising Research Foundation Annual Conference, 51-81.

Westwood, R. A. (1973), "The Use of Models to Determine the Importances of Beliefs," Proceedings of the ESOMAR Seminar on Developments in Consumer Psychology, 165-189.



Richard A. Westwood, The Beaumont Organization, Ltd.
Harry S. Sunenshine, Heublein Inc.


NA - Advances in Consumer Research Volume 08 | 1981

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