Consumer Decision-Making Models, Strategies,
and Theories, Oh My!
How do consumers make decisions? This question is at the core of much of marketing examination over the past 60 or 70 years. As marketers manipulate the various
principles of marketing, so do the consumers they seek to reach—choosing which products and services to buy, and which not to buy, choosing which brands
to use, and which brands to ignore. The focus of this paper is to examine the major decision-making models, strategies, and theories that underlie the decision
processes used by consumers and to provide some clarity for marketing executives attempting to find the right mix of variables for their products and services.
Three Decision-Making Models
Early economists, led by Nicholas Bernoulli, John von Neumann, and Oskar Morgenstern, puzzled over this question. Beginning about 300 years ago, Bernoulli developed
the first formal explanation of consumer decision-making. It was later extended by von Neumann and Morgenstern and called the Utility Theory.
This theory proposed that consumers make decisions based on the expected outcomes of their decisions. In this model consumers were viewed as rational actors who
were able to estimate the probabilistic outcomes of uncertain decisions and select the outcome which maximized their well-being.
However, as one might expect, consumers are typically not completely rational, or consistent, or even aware of the various elements that enter into their decision-making.
In addition, though consumers are good at estimating relative frequencies of events, they typically have difficulty translating these frequencies into probabilities.
This Utility model, even though it had been viewed as the dominant decision-making paradigm, had serious shortcomings that could not be explained by the model.
Nobel Laureate Herbert Simon proposed an alternative, simpler model in the mid-1950s. This model was called Satisficing, in which
consumers got approximately where they wanted to go and then stopped the decision-making process. An example of this would be in the search for a new apartment. Under
the Utility Theory, consumers would evaluate every apartment in a market, form a linear equation based on all the pertinent variables, and then select the
apartment that had the highest overall utility score. With Satisficing, however, consumers might just evaluate apartments within a certain distance to their
desired location, stopping when they found one that was "good enough." This theory, though robust enough to encompass many of the shortcomings of Utility
Theory, still left significant room for improvement in the area of prediction. After all, if a marketing executive can't predict consumer behavior, then what
use is a decision-making paradigm. Simon and others have extended this area in the investigation of the field of bounded rationality.
Following Simon, additional efforts were made to develop better understandings of consumer decision-making, extending beyond the mathematical optimization
of Utility Theory and the somewhat unsatisfying Satisficing Theory. In the late 1970s, two leading psychologists, Daniel Kahneman and Amos Tversky, developed
Prospect Theory, which expanded upon both Utility Theory and Satisficing Theory to develop a new theory that encompassed the best
aspects of each, while solving many of the problems that each presented.
Two major elements that were added by Kahneman and Tversky were the concepts of value (replacing the utility found in Utility Theory)
and endowment, in which an item is more precious if one owns it than if someone else owns it. Value provided a reference point and
evaluated both gains and losses from that reference point. Additionally, gains and losses have a marginally decreasing increase from the reference point. For
example, there is a much greater value for the first incremental gain from the reference point than for subsequent gains.
Seven Decision-Making Strategies
What this all led to was the development and exploration of a series of useful consumer decision-making strategies that can be exploited by marketers. For
each product, marketers need to understand the specific decision-making strategy utilized by each consumer segment acquiring that product. If this is
done, marketers can position their product in such a manner that the decision-making strategy leads consumers to select their product.
The first two strategies are called compensatory strategies.
In these strategies, consumers allow a higher value of one attribute to compensate for a lesser value of another attribute. For example, if a consumer is looking
at automobiles, a high value in gas mileage might compensate for a lower value in seating space. The attributes might have equal weight (Equal
Weight Strategy) or have different weights for the attributes (Weighted Additive Strategy). An example of the latter
might be to place twice as much importance on gas mileage than seating space.
The next three strategies are called noncompensatory strategies. In these strategies, each attribute of a specific product is evaluated without
respect to the other attributes, and even though a product may have a very high value on one attribute, if it fails another attribute, it is eliminated from
consideration. From Simon, the first of these is Satisficing, in which the first product evaluated to meet cutoff values for all attributes
is chosen, even if it is not the best. The second of these strategies, Elimination by Aspects, sets a cutoff value for the most important attribute,
and allows all competing products that meet that cutoff value to go to the next attribute and its cutoff value. The third strategy, Lexicographic,
evaluates the most important attribute, and if a product is clearly superior to others, stops the decision process and selects that product; otherwise, it
continues to the next most important attribute.
The next two strategies are called partially compensatory strategies, in that strategies are evaluated against each other in serial fashion and higher
values for attributes are considered. The first of these strategies is called Majority of Conforming Dimensions, in which the first
two competing products are evaluated across all attributes, and the one that has higher values across more dimensions, or attributes, is retained. This winner
is then evaluated against the next competitor, and the one that has higher values across more dimensions is again retained. The second partially compensatory
strategy is called Frequency of Good and Bad Features, in which all products are simultaneously compared to the cutoff values for each
of their relevant attributes, and the product that has the most "good" features that exceed the cutoff values is the winner.
There are other expansions upon these seven basic consumer decision-making strategies, but they are generally captured as shown above. However, two major
areas of marketing theory also help to provide additional explanatory power to these strategies.
Two Marketing Theories
The first marketing theory is called Consideration. In this theory, consumers form a subset of brands from which the decision-making
strategies are applied. For example, if asked to enumerate all the restaurants that one could recall, the list might be quite extensive for most consumers.
However, when a consumer first addresses the question of where to dine that evening, a short list of restaurants that are actively considered is utilized
for the decision-making process. Multistage decision-making models were summarized by Allan Shocker, in which the increasing complexity of a decision produces
more steps in the decision process. In essence, more cognitive effort would be expended in evaluating members of the consideration set and reducing that
number to an eventual choice.
The second marketing theory is called Involvement, in which the amount of cognitive effort applied to the decision-making process
is directly related to the level of importance that the consumer places on acquisition of the specific product. For example, there is rarely a significant amount of
decision-making applied to the selection of a pack of chewing gum at the grocery store checkout counter, but there is a much greater amount of decision-making
effort applied to the purchase of a new cell phone. This degree of involvement is not necessarily a function of the price, but is more related to the perceived
impact on the quality of life of the consumer. The quality of life can come directly from the benefits supplied by the product, or can come indirectly from
the social accolades or sanctions provided by members of the peer group.
Application of the three decision-making models, the seven decision-making strategies, and the two marketing theories can be seen in current efforts by
marketing practitioners and academicians to tease apart the complex decisions made by consumers. For example, choice models and conjoint models are multivariate
analysis techniques based on these understandings. Consumers are presented with choices in controlled environments that, hopefully, control for other confounding
variables, and then the choices are decomposed to understand both the conscious and unconscious elements driving the consumers' choices.
One caveat for practitioners is important to address at this point. When one is attempting to manipulate marketing variables such as price or promotion, or
even conduct research into consumer decision-making, it is critical that a solid theoretical base be used. Without this base, the surveys have the
potential of producing contradictory or misleading answers, and the attempts to manipulate the variables at hand may produce less than satisfying results.
In summary, this area of investigation is complex and uncertain, though extremely promising. The fields of economics, psychology, sociology, and marketing are
all deeply involved in trying to move this research forward, with often-conflicting research streams and terminology. However, the end result—gaining a better
understanding of how consumers make decisions—is of great theoretical and practical value to all involved. As such, it will continue to be a major
research area in all the above fields.
Note: Both information and insights were provided for this paper by Dr. Daniel Levine, Professor of Psychology, University of
Texas at Arlington.
Copyright © 2004 by Decision Analyst, Inc.
This article may not be copied, published, or used in any way without written permission of Decision Analyst.
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