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What Do Restaurant Brands Really Mean?
By
Michael Richarme and John Colias
Brands are conceptualized in various literature as bundles of attributes,
bundles of benefits, or even bundles of promises from the producer to the
consumer. These bundles can be challenging for consumers to vocalize, because
often the brand meaning is intuitively known at a subconscious level. That
causes a challenge for marketers attempting to describe and define their own
brands, much less strategically position their brands against perceived
competitors.
Brand awareness is a widely utilized metric, particularly in highly fragmented
or competitive industries, such as the restaurant industry (Kardes, et al.,
1993). This metric captures all the brand names that people are able to recall
on an unaided basis, and scores them from those "highest in awareness" to those
"lowest in awareness." From the broad list of brands that a consumer can
recall, consumers form a short list that they actually utilize in making
purchase decisions, generally called the consideration set (Roberts, et al.,
1997).
Consideration Set and Decisions
The consideration set may vary from situation to situation. For example, a
restaurant consideration set is different for lunch with coworkers than it is
for an elegant dinner with a significant other. Proximity, intervening
competitors, and other similar factors can also impact a consideration set
formation (Shocker, et al., 1991).
Group dynamics often come into play as well. Ask a small group of coworkers to
lunch, and each person may have two or three restaurant brands that immediately
jump to the top of their consideration sets. A brief negotiation process
ensues, basically comparing consideration sets until a restaurant brand emerges
that is acceptable to the group. An eminent social psychologist, Herbert Simon
(1955), described the process of looking at alternatives until one emerged that
was good enough as "satisficing." It doesn't involve an evaluation of all the
alternatives, or even selection of the optimal choice for the group. But it is
"good enough," which typically works.
Traditional economic theory would suggest that a mathematical approach
resulting in a selection of the restaurant choice with the highest overall
utility score would be appropriate. Rank everybody's choices from 1 to 5, with
1 being their first choice, and sum all the choices across the group members.
It is a good theory, and a good approach for business-to-business purchases
where cognitive decisions predominate.
But consumers, particularly when faced with simple or repetitive decisions,
tend to rely upon heuristics. And heuristics are based on both the affective
and cognitive decision processes that we all have. The emotional context of the
decision ("I don't feel like eating Mexican food today") can be as important as
the cognitive context ("We can get fast service at a reasonable price at
Joe's"). These heuristics, or rules-of-thumb, are combinations of both affect
and cognition, and are readily utilized for many day-to-day decisions.
Brand Positioning Approaches
So how do restaurant executives position their brands such that when the
consideration set is evoked in a consumer, or when a group discussion generates
a "good enough" alternative, that their brand is selected? To borrow from an
old television game show, that is the $64,000 question.
Some people use satisfaction and loyalty measures to give them an indication of
how they are doing. Others use brand awareness scores for the same purpose.
Both approaches give some glimpses into the minds of consumers, but often
aren't very satisfying or insightful (Lehmann and Pan, 1994).
Another approach is to create a perceptual map of consumer choices for a
particular vertical market. For restaurants, it might make sense to have
consumers generate an awareness map of restaurants, regardless of the industry
categorizations such as quick serve restaurant (QSR), full serve restaurant
(FSR), fast casual, steakhouse, etc. It might also make sense to ask consumers
to describe their restaurant usage habits, such as frequency, occasion, and
brand selection. And then it might make sense to ask the consumers about their
evaluation of the importance of both physical characteristics and attitudinal
characteristics of different attributes (lighting, meal quality, price point,
length of wait, etc.). This may be a good place to start thinking about (and
asking consumers about) different occasion scenarios, because an attribute
lighting may be very important for some occasions and not important at all for
other occasions. It is also important to gather a lot of different types of
attributes, because focusing on just a few visible ones will result in
everything being evaluated as important.
The next step in the process is to have the consumers evaluate specific
restaurant brands across a set of attributes. Not every consumer has recent
experience with every restaurant brand, so an agile and flexible computer
program that only presents those brands identified in the prior usage questions
is important. It is also possible to have consumers make a choice between two
restaurants; this task is often a good one when attributes don't adequately
capture everything going on with a selection process or when a cross-check of
the attribute evaluation process is desired. With sophisticated methodologies
for setting up these programs, not every consumer needs to evaluate every
possible combination, so the evaluation task can be constructed as less onerous
than it otherwise might be.
Another consideration, alluded to in the opening of this paper, is that
consumers may not always be able to clearly identify different attributes and
the relative importance levels of those attributes. Sometimes it is as simple
as a halo effect lending a certain level of importance to all attributes of a
specific brand, and sometimes it is as complex as combinations of affective and
cognitive factors operating below the threshold where consumers can readily or
correctly identify the factors.
To help consumers with the latter situation, latent class analysis can be
utilized. In this technique, the latent factors (dimensions) are identified,
and brands are positioned along the different axes in relationship to each
other. This technique has emerged in the past dozen years as a strong candidate
to replace weaker techniques for segmentation such as cluster, factor, and
regression analysis. By the inclusion of discrete unobserved variables, the
analysis is able to identify perceptual distances between brands by clustering
respondents along the different dimensions uncovered.
This relates closely to the concept of brand personality. Per Aaker (1997),
brand personality can be defined as "the set of human characteristics
associated with a brand." Consumers personify different brands, so that one
brand of restaurant might be viewed as "cool and sophisticated," while another
brand of restaurant might be viewed as "sedate and boring."
Perceptual Maps
With this data, different perceptual maps can be constructed. As mentioned
previously, the type of restaurant and the type of occasion are important means
by which consumers form specific consideration sets. Therefore, a perceptual
map for QSR and lunch might be an appropriate combination, as it would capture
the occasion of coworkers on their lunch break.
For this paper, a perceptual map of Quick Service Restaurant (QSR) brands has
been constructed, as shown in Figure
1. The data were extracted from the Decision Analyst Health
and Nutrition Strategist™, a quarterly tracker of attitudes and behaviors
about food, wellness, and restaurants. This database consists of 4,000 nationally
representative adult U.S. respondents per year, with data collected each quarter.
Interpretation
The perceptual map shows eight major benefits that drive restaurant choice.
Stronger benefits have longer rays. For example, "Good Selection of Healthy
Foods" strongly drives customer choices. Rays with large angles between them
indicate benefits that do not correlate and do not coincide in the mind of the
customer. Based on the map, one can see that "Good Kid's Menu/Kids Like It" and
"Has One of My Favorite Foods I Can't Get Elsewhere" do not naturally come
together in the mind of the customer. The further a restaurant projects along a
ray, the more customers associate that restaurant with the particular benefit
represented by that ray. For example, Baja Fresh offers "Great Salads or Salad
Bar" and "Good Selection of Healthy Foods." Chuck E. Cheese's has the strongest
positioning along the "Good Kid's Menu/Kids Like It" benefit.
Conclusions and Recommendations
From this data, it is possible to gain insight into where consumers believe
(whether explicitly or implicitly) different brands are positioned relative to
each other along a variety of dimensions. This may or may not match with the
overt positioning strategies of the companies themselves. If there is not a
match, or if a brand is hovering in the unpositioned "wasteland" near the
origin of the benefit rays on the map, " an opportunity exists to develop and
execute a positioning strategy to draw the brand into a different, more tenable
part of the perceptual map. One final consideration: all things change with
time. As consumer preferences change, and as different brands alter their
messaging and positioning strategies, the perceptual map also changes. This
type of analysis should be done on a regular basis to identify the positioning
of your brand, and to identify what your brand means to consumers.
References
Jennifer L. Aaker (1997), "Dimensions of Brand Personality," Journal of
Marketing Research, 34 (August, 1997), 347-356.
Frank R. Kardes, Gurumurthy Kalyanaram, Murali Chandrashekarun, and Ronald J.
Dornoff (1993), "Brand Retrieval, Consideration Set Composition, Consumer
Choice and the Pioneering Advantage," Journal of Consumer Research," 0
(June), 6 -75.
Donald R. Lehmann and Yigang Pan (1994), "Context Effects, New Brand Entry, and
Consideration Sets," Journal of Marketing Research, 31 (3), 364-374.
John H. Roberts and James M. Lattin (1997), "Consideration: Review of Research
and Prospects for Future Insights," Journal of Marketing Research, 34
(August), 406-11.
Allan Shocker, Moshe Ben-Akiva, Bruno Boccara, and Prakash Nedungadi (1991),
"Consideration Set Influences on Consumer Decision Making and Choice: Issues,
Models, and Suggestions," Marketing Letters, (August), 181-98.
Herbert A. Simon, (1955), "A Behavioral Model of Rational Choice," Quarterly
Journal of Economics, 69, 99-118.
Copyright � 2007 by Decision Analyst, Inc.
This article may not be copied, published, or used in any way without written
permission of Decision Analyst.
Additional Resources from Decision Analyst
To contact the authors, Michael Richarme (mrichar@decisionanalyst.com)
and John Colias (jcolias@decisionanalyst.com)
please email or call 1.800.262.5974.
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