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ATTITUDINAL BALANCEBASIL AND HERR

JOURNAL OF CONSUMER PSYCHOLOGY, 16(4), 391–403
Copyright © 2006, Lawrence Erlbaum Associates, Inc.

Attitudinal Balance and Cause-Related Marketing:
An Empirical Application of

Balance Theory

Debra Z. Basil
University of Lethbridge Centre for Socially Responsible Marketing

Paul M. Herr
University of Colorado at Boulder

We examine the effects of pre-existing organizational attitudes on consumer response to cause-
related marketing (CRM) alliances, using a Balance Theory framework. Two experiments dem-
onstrate that balanced attitudes (either both positive or both negative) resulted in perceptions of
appropriateness, but did not necessarily lead to positive affect. The positive balance scenario
led to a synergistic attitudinal boost when both pre-existing attitudes were positive. Attitudinal
contamination was evident when either pre-existing attitude was negative. Fit operated within
the balance scenario to enhance perceptions of the strength of the CRM alliance, leading to
more positive responses.

Cause-related marketing (CRM) involves the pairing of a
firm and a charity in a marketing effort. Alliances are often
formed by well-known firms pairing with well-known orga-
nizations, as in American Express’ CRM alliance with the
Ronald McDonald House. American Express donates to the
Ronald McDonald House for every transaction made on an
American Express card. Presumably, both American Express
and the Ronald McDonald House hope to benefit from ally-
ing with an organization for which consumers hold positive
pre-existing attitudes.

CRM alliances continue to grow in popularity (Cone/
Roper, 1999; PMA/Gable Group, 2000). The body of re-
search addressing CRM issues is also growing, but many
questions remain. Attitudes toward the CRM alliance and the
alliance partners have been examined, but the exact nature of
these attitudes has yet to be assessed. Does affect toward
CRM alliances depend on the perceived appropriateness of
the alliance, or are these issues independent? Pre-existing or-
ganizational attitudes impact attitude toward the CRM alli-
ance, but little if any research has examined the dynamic na-
ture of this impact. For instance, how do these attitudes
jointly influence CRM attitude? Fit between the allying orga-
nizations influences attitude toward the alliance, but, again,
the mechanism remains unknown. Our goal is to clarify the

Correspondence should be addressed to Debra Z. Basil, Associate Pro-
fessor, University of Lethbridge Centre for Socially Responsible Marketing,
Lethbridge, Alberta CANADA, T1K 3M4. E-mail: debra.basil@uleth.ca

role of pre-existing organizational attitudes and fit in
determining consumer response to CRM alliances, using a
Balance Theory framework. Balance Theory addresses situa-
tions where an individual evaluates the pairing of two sepa-
rate elements—precisely the situation with CRM.

LITERATURE REVIEW AND THEORETIC
FRAMEWORK

CRM enhances product choice (Barone, Miyazaki, & Taylor,
2000; Lichtenstein, Drumwright, & Braig, 2004; Yechiam,
Barron, Erev, & Erez, 2003,). However, socially oriented
messages are perceived differently, depending upon the
sponsor (Szykman, Bloom, & Blazing, 2004), and percep-
tions of a firm’s motive for forming the CRM partnership can
impact resulting attitudes (Barone et al., 2000). Tying nega-
tive information to the firm moderates response to CRM
(Dean, 2003/2004; Deshpande & Hitchon, 2002), as do con-
sumers’ elaboration levels (Menon & Kahn, 2003). More-
over, CRM may negatively influence the charity (Basil &
Herr, 2003). Hence, CRM alliances should be considered
carefully, as alliances may not only influence immediate pur-
chase decisions, but attitudes toward the partners as well.

Previous research has examined the impact of pre-existing
firm and charity attitudes on attitude toward the CRM alli-
ance, as well as attitude change toward the alliance partners
(Lafferty, Goldsmith, & Hult, 2004). Pre-existing firm and

mailto:debra.basil@uleth.ca

392 BASIL AND HERR

charity attitudes, and attitude toward the CRM alliance, are
positively correlated. A similar relationship exists for atti-
tude change toward the alliance partners. Although these re-
sults offer insight into the impact of pre-existing attitudes,
they do not address attitude dynamics. How do pre-existing
organizational attitudes interact to impact CRM alliance atti-
tude? We address this question.

Fit between the organizations also influences response to
CRM alliances. “Fit” has been addressed in the branding lit-
erature. Good fit between a brand extension and the firm’s
current brand offerings (Aaker & Keller, 1990), and similar-
ity, typicality, or relatedness between the extension and the
core brand (Bottomley & Holden, 2001; Boush & Loken,
1991; Broniarczyk & Alba, 1994; Dacin & Smith, 1994;
Herr, Farquhar, & Fazio, 1996) foster more favorable con-
sumer attitudes toward a brand extension. Similarly, when
two organizations’ brands and products are viewed as “fit-
ting” together, consumer attitudes toward a cobranding effort
are more favorable (Simonin & Ruth, 1998). Likewise, fit be-
tween an event and its sponsor influences consumer response
(Speed & Thompson, 2000).

Fit is important in cause-related marketing alliances, as
well (Basil & Herr, 2003; Hamlin & Wilson, 2004; Lafferty
et al., 2004; Menon & Kahn, 2003; Sen & Bhattacharya,
2001). Different types of fit have been proposed (e.g.
Lafferty et al., 2004). Although fit matters, the means by
which fit impacts CRM attitudes has received scant attention.
Our goal is to clarify the process by which fit impacts attitude
toward the CRM alliance.

CRM attitude measures vary dramatically in the literature.
Some researchers report attitude toward the CRM alliance as
a summary evaluation (Basil & Herr, 2002). Others report a
blend of affective and cognitive measures, such as whether
the alliance is good, positive, and favorable (Lafferty et al.,
2004). Still others take a behavioral approach to measuring
CRM alliance attitude (Barone et al., 2000; Strahilevitz &
Myers, 1998). Although behavioral responses to CRM alli-
ances have been extensively examined, no research has ad-
dressed the distinction between cognitive and affective re-
sponses to CRM alliances. Do these attitudinal responses
differ? We also address this issue.

Three primary factors are common to CRM alliances.
These include consumers’ pre- existing attitudes toward the
firm, pre-existing attitudes toward the charity, and percep-
tions of an alliance between these two. In some cases, con-
sumers may be unfamiliar with one or the other organization
(see Lafferty & Goldsmith, 2005), but such alliances are not
the focus of this research. Rather, we examine CRM alliances
involving organizations familiar to the individual, for which
attitudes exist.

Different theoretical approaches have been used to exam-
ine responses to CRM alliances, such as information integra-
tion (Lafferty, Goldsmith, & Hult, 2004), cognitive elabora-
tion (Menon & Kahn, 2003), and identification (Lichtenstein
et al., 2004). Each approach has strengths and weaknesses.

We sought a parsimonious framework that effectively ad-
dresses the three issues of interest: (1) the interactive effects
of firm and charity pre-existing attitudes, (2) the mechanism
by which fit impacts responses, and (3) differences between
affective and cognitive attitudinal responses. None of the the-
ories above addresses all of these issues. Balance Theory par-
simoniously addresses each issue and guides hypothesis for-
mation. Hence, we rely exclusively on Balance Theory to
generate and test our specific research hypotheses.

Balance Theory

Balance Theory (Heider, 1946, 1958) examines relational tri-
ads. Relationships between three individuals may be exam-
ined, from the perspective of one of the individuals. For ex-
ample, the relationship between Bob, Brad, and Bill’s
attitude toward Bob and Brad’s relationship, as well as Bill’s
attitude toward Bob and Brad individually, may be examined.
Heider (1946, 1958) proposed that individuals seek balance
among their interpersonal relationships and among attitudes
toward these relationships. Balance may be ascertained by
multiplying the signs in a triad of relationships (Cartwright &
Harary, 1956). A positive result indicates balance (see
Figure 1a).

Balance triads may contain relations between entities
other than people. Relationships between people are referred
to as sentiments, whereas relationships between entities are
referred to as unit relationships (Heider, 1958). In a CRM
scenario, the relationship between a firm and a charity is thus
a unit relationship.

FIGURE 1 Balance Theory Triads.

ATTITUDINAL BALANCE 393

Jordan (1953) proposed that balance leads to a judgment
of propriety or conforming to expectations, but for a situation
to be pleasant both balance and a positive interpersonal rela-
tionship are required. Hence, although two negative attitudes
represent balance, the situation is not deemed pleasant. Judg-
ments of unpleasantness require only the perception of im-
balance or the perception of a negative relationship.
Cacioppo and Petty’s (1981) findings that balance contrib-
utes to a sense of propriety, whereas agreement and attraction
between the individuals contribute to positive affect, further
support this position.

These findings provide a foundation for hypothesizing
consumer responses to CRM alliances. Cognitive and affec-
tive responses to CRM alliances are expected to differ ac-
cordingly. Previous research suggests that affect impacts
judgments, but this area has not been thoroughly researched
(Olsen & Pracejus, 2004; Pham, 2004). Consumers are ex-
pected to judge as “appropriate” alliances for which their
pre-existing attitudes yield balance. Judgments of propriety
represent the cognitive element in a CRM alliance attitude.
Either a positive–positive or a negative–negative alliance
should be judged “appropriate.” Balance does not suggest
positive affect toward the alliance itself. The negative–nega-
tive balance situation may be deemed appropriate, but not be
well liked, per Cacioppo and Petty (1981). This represents
the affective element in a CRM alliance attitude. Thus,

H1: The positive impact of balance will be greater for
judgments of propriety than for judgments of affect, as
evidenced in a balance × judgment type interaction.

An individual’s attitude toward a CRM alliance should
consist of some combination of his or her attitude toward the
firm, the charity, and the pairing of these two, per Balance
Theory. Hence, positive pre-existing attitudes toward the
firm and the charity should contribute to a positive alliance
attitude. Likewise, a positive view of the pair together should
contribute to a positive alliance attitude (discussed later).
However, Jordan’s (1953) findings regarding pleasantness
perceptions demonstrated a benefit for the combination of
balance plus a positive relationship. If, indeed, positive
pre-existing attitudes toward the alliance partners are impor-
tant for generating a positive attitude toward the alliance it-
self, then the combination of balance plus positive pre-exist-
ing attitudes should lead to a more positive response to the
alliance, above and beyond the simple additive effects of
each individual pre-existing attitude. This interactive affect
of organizational attitudes has not been previously examined.
Thus,

H2: Consumers’ pre-existing attitudes toward the firm
and the charity will interact such that attitudes toward
the alliance will be multiplicatively more positive
when both pre-existing organizational attitudes are
balanced and both are positive.

Fit

We propose that fit may be viewed as a measure of the
strength of the relational tie between the two organizations.
In a CRM alliance, the individual’s attitude toward the firm
and the charity are two legs of a Balance triad. The presence
(absence) of an organizational relationship may be viewed as
the third leg of the triad. In Balance Theory’s original con-
ceptualization, all relations were represented dichotomously.
Extensions (e.g. Osgood & Tannenbaum, 1955) viewed the
relations as continuous. This perspective allows for an exam-
ination of the strength of the relationships in the triad. Fit in a
CRM alliance can thus be viewed as strengthening the unit
relationship between the firm and the charity, defining the na-
ture of their association. A positive firm attitude, a positive
charity attitude, and fit between the firm and charity reflect a
strong, positive balance scenario (see Figure 1b).

We expect the relationship between organizations that fit
to be judged stronger than the relationship between organiza-
tions that do not fit. Moreover, if fit at least partly increases
perceptions of relationship strength, then the impact of fit on
attitude toward the CRM alliance should be at least partially
mediated by perceptions of relationship strength. Hence,

H3a: The relationship between organizations that fit
will be viewed as stronger than the relationship be-
tween organizations that do not fit.

H3b: The effect of fit on CRM attitude will be partially
mediated by perceptions of relationship strength.

If fit enhances perceptions of the strength of the relation-
ship between a firm and a charity, then fit should similarly in-
fluence judgments. Specifically, fit between the firm and
charity should be viewed as more appropriate, regardless of
attitudes toward the organizations. This is because fit should
be seen as appropriate, based on individuals’ preference for
balance. The same is not expected for affect, however. Two
organizations may fit well, but an individual may not neces-
sarily like the pairing, simply because they fit. Thus,

H4: Fit will more strongly influence judgments of ap-
propriateness or propriety than judgments of positive
affect, as reflected in a fit × judgment type interaction.

Balance is expected to influence target organizational atti-
tude change in a manner similar to its anticipated effect on al-
liance attitude. Consumers are expected to exhibit more posi-
tive attitude change toward a target alliance member when
they hold positive pre-existing attitudes toward the alliance
partner, and are expected to prefer balanced attitudes. Hence,
balanced attitudes with a liked pre-existing partner should
enjoy additional positive response, beyond the benefit of
simply owning positive pre-existing attitudes. The expecta-
tion here is slightly different than that proposed in Hypothe-

394 BASIL AND HERR

sis 2: Only the partner’s pre-existing attitude valence must be
positive, rather than requiring positive pre-existing attitudes
toward both organizations. Practically speaking, however,
this distinction is irrelevant, as pre-existing attitudes toward
the target alliance member must in fact be positive for both
balanced attitudes and a positive pre- existing attitude toward
the alliance partner to exist. If pre-existing attitudes toward
the partner are positive, then, by definition, pre-existing atti-
tudes toward the target must be positive to attain balance.
Hence, we predict a synergy for balanced attitudes and a pos-
itive pre-existing partner attitude, not driven by pre-existing
target organization attitudes, as follows:

H5: Consumers’ pre-existing attitudes toward the part-
ner organization will interact with attitudinal balance.
When pre-existing partner attitudes are positive and
balanced, attitude change toward the target organiza-
tion will be multiplicatively more positive.

EXPERIMENT 1

Experiment 1 tests these hypotheses. The experiment was ad-
ministered via computer. The firm represents the target orga-
nization and the charity represents the partner organization.

Pretests

All pretest and experiment participants were from the same
major Western university. Pretests were conducted to select
appropriate organizational profiles for fictitious firms and
charities. The profiles were intended to create either positive
or negative attitudes toward the fictitious organizations. Pre-
test 1 involved 36 undergraduate business students, partici-
pating for partial course credit. Participants were asked to list
information about firms and charities that would lead them to
hold either a positive or negative attitude toward the organi-
zation. In Pretest 2, the most commonly cited information
from Pretest 1 was further tested. Forty undergraduate busi-
ness students participated in this Pretest for partial course
credit. Pretest 3 combined these statements into firm and
charity profiles to create reliably positive or negative atti-
tudes toward the fictitious organization. Twenty-eight under-
graduate business students participated for extra course
credit. Pretest 4 determined product and charity categories
that, when paired in a cause-related alliance, “fit” together,
and pairs that did not “fit” together. “Fit” was defined for
subjects in terms of whether the organizations’ purposes
were complementary, and whether the organizations’ alli-
ance “made sense.” Sixty-five undergraduates participated to
partially fulfill a course requirement. The resulting firm and
charity profiles created positive or negative attitudes, as well
as CRM alliances that did or did not fit.

Participants and Design

One hundred sixty-eight undergraduate business students
participated for extra course credit. A 2 (organizational fit) ×
2 (firm attitude: positive or negative) × 2 (charity attitude:
positive or negative) × 2 (judgment type: affect or propriety)
mixed design was used. Fit and judgment type were within-
subjects factors.

Independent Variables

Firm and charity attitudes were manipulated via the ficti-
tious organizational profiles. Each organizational profile
contained five statements about the organization, based on
pretest results. These profiles were used to generate posi-
tive or negative attitudes toward the firm and charity. (See
Appendix A for sample profiles.) Profiles were randomly
generated for each subject, from a pool of 15 possible state-
ments, to assure that results were not due to excessive im-
pact from any single statement. Both the statements dis-
played and their order were randomized. Participants were
randomly assigned to one of four between-subjects attitude
conditions: positive firm attitude/positive charity attitude;
negative firm attitude/negative charity attitude; positive
firm attitude/negative charity attitude; or negative firm atti-
tude/positive charity attitude.

Fit was manipulated through the pairing of firms and char-
ities. Two fictitious firms and two fictitious charities were se-
lected from Pretests. “Bakerman’s Bread” was paired with
“Stop Starvation” in the fit condition, and with “Prevent
Children’s Polio” in the no-fit condition. “Tikes Toys” was
paired with “Prevent Children’s Polio” in the fit condition
and “Stop Starvation” in the no-fit condition. Each partici-
pant evaluated all four pairings.

Each subject was exposed to both propriety-based and af-
fect-based adjectives. This exposure was a within-subjects
factor for analysis purposes. Participants’ actual responses to
these adjectives served as a dependent variable.

Dependent Variables

Attitude toward the CRM alliance was assessed by asking
participants to agree or disagree with adjectives describing
the alliance. These adjectives were: like, dislike, appealing,
unappealing, good, bad, appropriate, and inappropriate. Atti-
tude toward the CRM alliance was also assessed by asking
participants to indicate their attitude toward the CRM on a
7-point scale, anchored by “very negative” at –3 and “very
positive” at +3.

Attitude change toward the firm due to the CRM alliance
was assessed. Participants were asked the extent to which the
CRM alliance would make their attitude toward the firm
more positive, and then asked the extent to which the alliance
would make their attitude toward the firm more negative.

ATTITUDINAL BALANCE 395

Perceptions of the strength of the relationship between the
firm and the charity were measured. Since a CRM alliance in-
volves an overt donation from the firm to the charity, with no
corresponding overt helping behavior from the charity to the
firm, the items assessing relationship strength primarily fo-
cused on perceptions of the firm’s assistance to the charity.
Scale creation is discussed in the next section. Perceptions of
the relationship were assessed through comments made in
the thought-listing exercise also discussed in the next section.

Procedure

Participants were run in groups of 8 to 12. Stimuli were pre-
sented and responses recorded via personal computer. Partic-
ipants were first shown a firm profile containing five state-
ments regarding the fictitious firm. Participants were told to
examine the information until they felt comfortable with it.
Participants then indicated their attitude toward the firm.
They were presented with the charity profile, again contain-
ing five statements, and indicated their attitude toward the
charity. A definition of cause-related marketing was pro-
vided next, along with an example of a CRM alliance. Partic-
ipants completed a thought-listing task regarding their re-
sponse to the CRM alliance between the fictitious firm and
charity. They were given three minutes, and told to type ev-
erything that came to mind when considering the alliance.
Participants then were asked to consider a CRM alliance be-
tween the two organizations, and to either agree or disagree
with adjectives describing the alliance.

Immediately following the adjective-response activity,
participants answered a series of attitudinal questions regard-
ing the firm, charity, and alliance between them. Responses
were collected on a 7-point scale, ranging from –3 to +3. This
procedure was repeated for the remaining three CRM pair-
ings for a total of four randomly ordered iterations per partic-
ipant.

Analyses

First, manipulations were assessed and scales created.
Thought-listing results were used to assess the fit manipula-
tion. Two coders, naïve to hypotheses and study condition,
coded subjects’ open-ended responses. Intercoder agreement
was 91%. The primary researcher resolved disagreements.
Participants made more comments about poor fit in the no-fit
condition, compared to the fit condition (t = –5.4, p < .001), suggesting a successful manipulation.

Mean firm attitudes in the positive attitude conditions (M
= 2.18) were significantly higher than in the negative attitude
conditions (M = –1.89, p < .001). Similarly, mean charity at- titudes in the positive attitude conditions (M = 2.41) were sig- nificantly higher than in the negative attitude conditions (M = –1.13, p < .001). The firm and charity attitude manipulations were thus deemed successful.

Participants’ responses to the positive (appealing, appro-
priate, good, like) and negative (unappealing, inappropriate,
bad, dislike) adjectives were coded “1” for agree and “–1” for
disagree. Adjective responses were combined into scales by
averaging the positive adjectives and averaging the negative
adjectives. The four positive adjectives were assessed for
scale reliability. Scale reliability was good (α = .92). The
four negative adjectives were assessed and the resulting scale
was also reliable (α = .90).

Scales were also created to assess perceptions of propriety
and affect separately. Scores for the negative adjectives were
reverse coded. For the affect-based adjectives (like, appeal-
ing, dislike reverse coded, unappealing reverse coded), reli-
ability was good (α = .96). The affect scale was created by
averaging these scores. Similarly, the propriety-based adjec-
tives scale (good, appropriate, bad reverse coded, inappropri-
ate reverse coded) reliability was good (α = .97). The propri-
ety scale was created by averaging these scores.

A scale was created for the dependent variable firm atti-
tude change. Responses to the negatively framed question
were reverse coded, then combined with the positively
framed question. Scale reliability was good (α = .83).

Results

Hypothesis 1 proposed a distinction between affect-based re-
sponses and propriety-based responses. Specifically, balance
was expected to increase perceptions of propriety more than
feelings of positive affect. A repeated-measures ANOVA was
conducted. The balance condition was recoded into two cate-
gories, balance and imbalance. Two-level attitude balance
(balanced/unbalanced) served as a between-subjects factor,
and judgment type (affect-based adjectives, propriety-based
adjectives) a within-subjects factor. Mean scores for adjec-
tive responses served as the dependent variable. A main ef-
fect for judgment type was evident, F(1, 158) = 48.4, p < .001, ε2 = .26. Responses to propriety-based adjectives (good/bad, appropriate/inappropriate) were significantly more positive than responses to affect- based adjectives (like/ dislike, appealing/unappealing). A significant interaction be- tween judgment type and balance was also evident, F(1, 158) = 5.3, p < .05, ε2 = .03, supporting Hypothesis 1. Attitudinal balance had a significantly larger impact on perceptions of propriety regarding the CRM alliance than on affect toward the alliance (see Figure 2). Specifically, balanced attitudes (positive–positive or negative–negative) generated a judg- ment of propriety (M = 1.26), although they did not necessar- ily generate positive affect (M = .21). Since the adjectives “good” and “bad” have been used in other research to indi- cate affect rather than propriety, an assessment was made us- ing only the adjectives “appropriate” and “appealing.” Con- sistent with the prior analysis, balanced attitudes were judged somewhat appropriate (M = 1.9) but not very appealing (M = .09), t (79) = 2.0, p = .05, per Hypothesis 1.

396 BASIL AND HERR

FIGURE 2 Balance × Judgment Type Interaction.

FIGURE 3 CRM Attitude.

Another repeated-measures ANOVA was run to test Hy-
potheses 2 and 4. Fit and judgment type served as within-sub-
jects factors, firm and charity attitudes as between-subjects
factors. Responses to the valenced adjectives served as the
dependent variable. Hypothesis 2 was supported, F(1, 161) =
4.6, p < .05, ε2 = .03. Firm and charity attitudes interacted such that responses were significantly more positive when both pre-existing attitudes were positive and balanced, above the simple additive effects expected from each of the pre-ex- isting attitudes individually (see Figure 3). Hypothesis 4 was also supported, F(1, 161) = 20.7, p < .001, ε2 = .09. Fit had a stronger impact on perceptions of propriety than on affect. Alliances that fit were judged appropriate even if not well liked.

Hypothesis 3 proposed a main effect for fit on perceptions
of relationship strength (part a) and that perceptions of rela-
tionship strength would mediate the impact of fit on CRM at-
titude (part b). First, responses to the thought-listing exercise

(comments regarding the relationship between the firm and
charity) were examined. A paired-samples t test was con-
ducted. More negative comments regarding the relationship
were made in the no-fit conditions, compared to the fit condi-
tions, t(172) = 2.5, p < .05, supporting Hypothesis 3a.

To further assess Hypothesis 3, a mediation test was con-
ducted (Baron & Kenny, 1986). First, a repeated measures
ANOVA was run with fit serving as the repeated measure,
and perceptions of relationship strength as the dependent
variable. Fit significantly increased perceptions of relation-
ship strength, F(1, 166) = 56, p < .001, ε2 = .25, again sup- porting Hypothesis 3a. Moreover, firm attitude, F(1,155) = 67.4, p < .001, ε2 = .29, and charity attitude, F(1, 166) = 9.9, p < .005, ε2 = .06, both predicted relationship strength. A re- peated-measures ANOVA was then conducted, with fit serv- ing as the repeated measure and CRM attitude as the depend- ent variable. Fit significantly predicted CRM attitude, F(1, 166) = 77, p < .001, ε2 = .32. Finally, a third repeated-mea-

ATTITUDINAL BALANCE 397

FIGURE 4 Firm Attitude Change.

sures ANOVA was conducted, with fit serving as the repeated
measure, perceived strength of the relationship a covariate,
and CRM attitude the dependent variable. Both fit, F(1, 164)
= 23, p < .001, ε2 = .13, and perceived relationship strength, fit F(1, 164) = 47, p < .001, ε2 = .22; no fit F(1, 164) = 15, p < .001, ε2 = .08, significantly predicted CRM attitude. Since the impact of fit was reduced with the inclusion of relation- ship strength (ε2 reduced from .32 to .13), fit was partially mediated by perceived relationship strength, supporting Hy- pothesis 3b.

To test Hypothesis 5, change in attitude toward the firm
was assessed using an ANOVA. Firm and charity pre-exist-
ing attitudes served as between-subjects factors. The firm at-
titude change scale served as the dependent variable. Pre-ex-
isting firm and charity attitudes significantly interacted, F(1,
166) = 7.0, p < .01, ε2 = .04, supporting Hypothesis 5. A syn- ergy of organizational attitudes was evident. When both pre-existing firm and charity attitudes were positive, change in attitude toward the firm was significantly larger than the simple additive effects would suggest (see Figure 4).

Discussion

The results of Experiment 1 support the hypotheses regard-
ing attitude toward the CRM alliance. These results enhance
understanding of the impact of fit on attitudes toward the
CRM alliance. Prior research has demonstrated an impact for
fit, but the nature of this impact has not been thoroughly ex-
amined. This research demonstrates that fit enhances the
sense of relationship strength between the two organizations.
Organizations that fit are seen to have a stronger relationship.
Moreover, more negative thoughts regarding the alliance
come to mind when the organizations do not fit. Thus, fit
strengthens the relationship between the two organizations,
creating a stronger unit relationship. The effect of fit on CRM
attitude is partially mediated by perceptions of strength of the
CRM alliance. Hence, when organizations fit, the CRM alli-

ance is seen as more appropriate, although this alone may not
generate much positive affect. This finding is an important
step toward explicating the nature of the impact of fit.

A similar effect is found for balance. The significant bal-
ance by judgment-type interaction suggests that balanced at-
titudes lead to perceptions of appropriateness, but not neces-
sarily to positive affect. Collectively, these results suggest
that individuals have a sense of propriety for CRM alliances,
with views on whether the pairing is appropriate or not, inde-
pendent of their liking for the CRM alliance.

The results also support hypotheses regarding attitude
change toward the firm. Pre-existing charity attitude is a
strong determinant of attitude change toward the firm. Con-
sistent with Balance Theory, firm attitudes changed to be-
come more consistent with attitudes toward the alliance part-
ner. A synergistic interaction of pre-existing attitudes was
also evident, yielding benefits to the firm attitude given bal-
ance and a positive pre-existing charity attitude.

The interaction between firm and charity attitude consis-
tently attained significance. Both when predicting attitude to-
ward the CRM alliance and when predicting firm attitude
change, an interaction between firm and charity attitude was
evident. This may be due to a synergistic effect when both
balance and positive attitudes are present. When everything
is perfect (pre-existing attitudes are positive and balance ex-
ists), responses are much more positive. Alternatively, this
pattern of results may be due to a “contamination effect.”
Specifically, any one negative element may lead to a more
negative response. In order to assess which of these is the
case, it is necessary to compare responses for positive, neu-
tral, and negative pre-existing organizational attitudes. If
positive firm and charity attitudes lead to more positive eval-
uations than when one or both of these is neutral, a synergy
effect exists. Alternatively, if the difference stems from dif-
ferences between negative and neutral attitudes, rather than
neutral and positive attitudes, a contamination effect is sup-
ported. Thus, the competing hypotheses:

398 BASIL AND HERR

H6a: The interaction between pre-existing firm and
charity attitudes is due to a synergy effect such that
CRM alliance attitudes will experience an enhance-
ment only when both pre-existing attitudes are posi-
tive, compared to neutral attitudes.

-OR-

H6b: The interaction between pre-existing firm and
charity attitudes is due to a contamination effect such
that CRM alliance attitudes will experience a decre-
ment whether one or both pre- existing attitudes are
negative, compared to neutral attitudes.

EXPERIMENT 2

Experiment 1 tested the proposed hypotheses. However, the
stimuli used were of fictitious firms and charities, and organi-
zational attitudes were created as part of the study. Although
germane to newly formed attitudes, it is impossible to deter-
mine whether the results generalize to situations involving
longstanding pre-existing attitudes. In Experiment 2, a con-
ceptual replication is performed. Real firms and charities are
used, allowing a test of the proposed hypotheses with pre-ex-
isting attitudes. The use of real organization names also en-
hances external validity by allowing for a test of the hypothe-
ses in a situation where many complex elements have likely
contributed to attitude formation, as opposed to the simplistic
firm profiles used in Experiment 1. Moreover, a larger num-
ber of pairings is used, to improve the generalizability of re-
sults. Experiment 2 addresses Hypotheses 6a and 6b to fur-
ther clarify the nature of the firm by charity attitude
interaction. Finally, need for cognition (NFC) was added to
this experiment as a covariate, as previous research indicates
that extent of cognitive elaboration affects consumer re-
sponse to advertising efforts (Priester, Godek,
Nayakankuppum, & Park, 2004) and may impact response to
CRM alliances (Menon & Kahn, 2003). NFC was used as a
proxy to control for possible elaboration differences.

Participants and Design

Sixty undergraduate business students participated in Exper-
iment 2 for extra course credit. Males comprised 58% of the

sample. No participant took part in any Pretest or Experiment
1. Experiment 2 used a 2 (fit) × 6 (pairings) within-subjects
design, with firm and charity attitudes serving as measured
(rather than manipulated) variables. Need for Cognition
(Cacioppo & Petty, 1982) served as a covariate. Six firms
were paired with 2 charities each, 1 fit and 1 no-fit charity, for
a total of 12 CRM alliances (see Table 1).

Each participant evaluated all 12 of the CRM alliances in
a random order. Participants were run in four groups, ranging
in size from 12 to 19. Paper and pencil stimuli were used,
which participants completed at their own pace.

Independent Variables

“Fit” was manipulated by the selection of specific firms and
charities, based on pretesting. Each firm was paired with one
charity deemed to fit, and one deemed not to fit. “Pairing”
was a nontheoretical replication variable included to increase
generalizability. Testing multiple CRM alliances helps as-
sure that results are not idiosyncratic.

Pre-existing firm and charity attitudes were measured in-
dependent variables. Participants indicated their pre-existing
attitudes toward the firm and the charity on an 11-point scale
ranging from –5 to +5, with anchors “very negative” and
“very positive.” A larger response scale was used in Experi-
ment 2 than in Experiment 1 (10 point vs. 7 point), in case
measures of pre-existing attitudes toward charities were con-
stricted to positive or neutral scale responses. Efforts were
made to select charities toward which some people held neg-
ative attitudes.

Participants responded to 22 questions regarding each al-
liance. Each question was posed on an 11-point scale, an-
chored by “not at all” at –5 and “very much” at +5. The de-
pendent variables of interest were attitude toward the CRM
alliance, perception that this was a good CRM alliance, atti-
tude change toward the firm, and perceptions of the strength
of the alliance.

Since pre-existing firm and charity attitudes were mea-
sured, rather than manipulated, a standard within-subjects
ANOVA was deemed unsuitable. Within-subjects regression
(Judd, Kenny, & McClelland, 2001) was used instead. This
procedure provides a test of the moderating effects of continu-
ous variables in within-subjects designs. To conduct a
within-subjects regression, the dependent variable of interest

TABLE 1
Firm and Charity Pairings

Fit No Fit

Nike Athletic Shoes/The American Heart Association Nike Athletic Shoes/Feed the Children
Velveeta Cheese/Feed the Children Velveeta Cheese/The American Heart Association
Nintendo Video Games/Youth at Risk Nintendo Video Games/National Rifle Association
Smith & Wesson Guns/National Rifle Association Smith & Wesson Guns/Youth at Risk
Gerber Baby Food/The Pro-Life Action League Gerber Baby Food/Greenpeace Environmental Conservation Charity
Big 5 Sporting Goods/Greenpeace Environmental Conservation Charity Big 5 Sporting Goods/The Pro-Life Action League

ATTITUDINAL BALANCE 399

is regressed on the within-subjects factors for each participant
separately. The resulting betas for the within-subjects factors
represent the relationship between each within-subjects factor
and the dependent variable for each participant. These betas
are then regressed on the between-subjects factors and indi-
vidual difference variables using the data set as a whole. For
example, regressions were performed for each individual par-
ticipant, regressing firm attitude change (one of the dependent
variables) on pre-existing firm attitude, pre-existing charity
attitude, pre-existing firm attitude × pre-existing charity atti-
tude interaction, and fit. The resulting betas for pre-existing
firm attitude represented the relationship between pre- exist-
ing firm attitude and firm attitude change due to the CRM alli-
ance for each individual participant when controlling for other
variables in the equation. Similarly, the resulting betas for fit
represented the relationship between fit and firm attitude
change for each participant, and so forth. The purpose of these
individual regressions, then, is to ascertain the relational pat-
tern between the within-subjects independent variables and
the dependent variables for each participant, not to determine
any form of statistical significance. After this step, the result-
ing within-subjects beta weights were used in a series of be-
tween-subjects regressions that regressed the beta weight on
NFC(Cacioppo&Petty,1982) inorder toassessstatistical sig-
nificance.Thiswasrepeatedforeachdependentvariable.Fora
more detailed description of this procedure, see Judd et al.
(2001).

Pre-existing firm and charity attitudes were tested as con-
tinuous variables, but trichotomized to simplify reporting.
Responses between 1 and 5 were grouped as positive pre-ex-
isting attitudes (N = 477 for firms, N = 521 for charities). Re-
sponses between –1 and –5 were grouped together as nega-
tive pre-existing attitudes (N = 107 for firms, N = 109 for
charities). Responses of zero were categorized “neutral” (N =
136 for firms, N = 88 for charities).

Results

Throughout Experiment 2, NFC served as a control variable.
This variable did not attain significance in any of the analyses
(p > .05), so it is not discussed further.

Hypothesis 2 was tested using a within-subjects regres-
sion. Pre-existing firm and charity attitudes significantly in-
teracted to predict attitude toward the CRM alliance (t = 2.5,
p < .05, ε2 = .09), supporting Hypothesis 2. The synergistic effect of positive pre- existing attitudes and balance was evi- dent, demonstrating more positive attitudes toward the CRM alliance in the positive–positive condition.

Hypothesis 3 was tested to examine the effect of fit.
B-weights calculated from responses to the statement “This
will be a long-lasting alliance,” answered on an 11-point
scale, served as the dependent variable. Baron and Kenny’s
(1986) approach to testing mediation was used, adapted to a
within-subjects design. First, a within-subjects regression
was conducted to assess whether fit and pre-existing firm and

charity attitudes served to predict relationship strength. Fit
significantly predicted perception of relationship strength (t
= 11.6, p < .001), supporting Hypothesis 3a. Additionally, firm attitude and charity attitude significantly interacted to predict perceptions of strength (t = 3.0, p < .005). In the sec- ond step of the mediation test, fit significantly predicted atti- tude toward the CRM alliance (t = 6.2, B = 1.3, SE = .21, p < .001). Finally, with perception of relationship strength and fit included in the calculation of the B-weights, strength signifi- cantly predicted CRM attitude (t = 15, B = .71, SE = .05, p < .001), as did fit (t = 2, B = .22, SE = .11, p < .05). To assess the difference in the predictive power of fit with the inclusion of perceived strength, thus assessing mediation, the change in unstandardized betas was compared in terms of standard er- rors. Specifically, the unstandardized beta with strength in- cluded (.22) was subtracted from the unstandardized beta without strength included (1.3), and this amount was divided by the standard error for the unstandardized beta without strength included (.21). The unstandardized betas differed by 5.1 standard errors, suggesting a significant difference (dif- ferences exceeding 2 standard errors are significant). The ef- fect of fit was reduced when perceived strength was included, suggesting the effect of fit is partially mediated by percep- tions of relationship strength; this supports Hypothesis 3b.

To test Hypothesis 5, the effect of the CRM alliance on at-
titudes toward the firm was assessed next. Pre-existing firm
and charity attitudes interacted marginally to predict firm at-
titude change (t = 1.9, p = .06, ε2 = .06). The positive–positive
condition elicited more attitude change than the other condi-
tions, marginally supporting Hypothesis 5.

Hypothesis 6 queried whether the interactive effect of
pre-existing organizational attitudes was due to a synergy or
a contamination effect. In order to assess this, trichotomized
firm and charity attitudes were examined using t tests. The
dependent variable attitude toward the CRM alliance was
used. When both firm and charity attitudes were positive,
CRM attitude was significantly more positive than when ei-
ther attitude was neutral, t (418) = 4.3, p < .001, suggesting a synergy, supporting Hypothesis 6a (see Figure 5).

However, when either firm or charity attitude was nega-
tive, CRM attitude was less favorable than when both atti-
tudes were at least neutral (all p < .001). A single negative or- ganizational attitude served to contaminate CRM attitude, supporting Hypothesis 6b (see Figure 6).

Discussion

These results are consistent with and clarify the findings of
Experiment 1. Pre-existing firm and charity attitudes interact
to determine attitude toward the CRM alliance. Two distinct
effects occur. First, positive pre-existing attitudes synergisti-
cally enhance attitude toward the CRM alliance. This effect
is magnified when both attitudes are positive, suggesting a
“balance boost.” Attitude toward the CRM alliance becomes
multiplicatively more positive when both pre-existing atti-

400 BASIL AND HERR

FIGURE 5 Synergy Effect.

FIGURE 6 Contamination Effect.

tudes are positive. A synergy is obtained by “having every-
thing right.” A contamination effect also occurs, as a result of
“having anything wrong.” If either the firm or the charity atti-
tude is negative, attitude toward the CRM alliance deterio-
rates.

These findings do not simply reflect ordinal results
whereby neutral attitudes fall between negative and positive
attitudes. Rather, one negative pre-existing attitude is equiva-
lent to both attitudes being negative, suggesting contamina-
tion. Similarly, only when both pre-existing attitudes are pos-
itive is a multiplicative enhancement to CRM attitude

evident. When either one or both of the pre-existing attitudes
are neutral, CRM attitudes are depressed. This again demon-
strates a deviation from ordinal results. Everything must be
“right” to obtain multiplicative attitudinal benefit; if anything
is “wrong,” an attitudinal penalty occurs.

Balance Theory helps to explicate the effect of fit in a
CRM alliance, as well. Fit consistently influenced attitudes.
Fit positively impacted both CRM attitude and attitude
change toward the firm. Moreover, fit led to perceptions of a
stronger unit relationship between the firm and the charity,
partially mediating the impact of fit.

ATTITUDINAL BALANCE 401

GENERAL DISCUSSION

Prior work demonstrated that fit impacts consumer response
to CRM alliances, but the nature of this impact was uncertain.
Fit’s role was clarified in the present research. Fit increased
perceptions of the relationship between the firm and the char-
ity. This effect may be understood in terms of Balance The-
ory (Heider, 1946, 1958). The beneficial impact of fit in a
CRM alliance appears partly to stem from a perception that
the relationship between the firm and the charity is stronger
when fit exists. In Balance Theory terms, the unit relation-
ship between the CRM (firm and the charity) becomes stron-
ger when fit exists. Fit’s impact on alliance attitudes was par-
tially mediated by perceptions of relationship strength. In
part, fit influences CRM attitude by strengthening percep-
tions of the unit relationship between the firm and the charity.
These results suggest that when contemplating an alliance, fit
should be a primary consideration.

Previous research has also demonstrated that pre-existing
firm and charity attitudes impact attitude toward the CRM al-
liance. This research advances our understanding of the role
of pre- existing attitudes by demonstrating that this impact is
interactive: The effect of pre-existing firm attitude depends
upon the valence of pre-existing charity attitude, and vice
versa. Specifically, a synergistic benefit was evident when
pre-existing attitudes toward both of the organizations were
positive. If pre-existing attitudes toward the target organiza-
tion are negative, pre-existing attitudes toward the partner or-
ganization become less important. This suggests that if con-
sumer attitudes toward a firm are negative, adding a CRM
partner will have reduced impact. Partner attitudes do have a
significant impact on attitude toward the target organization,
so if a firm with negative pre-existing attitudes partners with
a charity with positive pre-existing attitudes, the firm will
benefit from the alliance, but the benefit is far less than what
would be enjoyed by a more positively viewed firm. If
pre-existing firm attitudes are positive, the firm stands to gain
a good deal through a CRM alliance, but only if the alliance
partner enjoys positive consumer attitudes as well. These re-
sults represent a synergistic effect for having both positive
firm and charity attitudes, and a contamination effect for hav-
ing either a negative firm or a negative charity attitude.

Attitudinal balance has differential impact depending
upon the type of judgment being made. Balanced attitudes
are seen as appropriate. It is appropriate for an organization
to partner with another organization toward which pre-exist-
ing attitudes are comparable. Balance, however, has far less
influence on affect toward the alliance. Positive attitudes are
necessary to generate positive affect, whereas only balance is
necessary to generate a sense of propriety. This effect was
mirrored with fit. Specifically, fit between two organizations
has a stronger impact on perceptions of propriety than on
positive affect. Collectively, these results suggest that when
two organizations appear to “go together,” either because
they share a common attitude valence (balance) or they share

a common purpose (fit), their alliance is seen to be appropri-
ate. This does not indicate that the alliance will be well liked,
however. Positive organizational attitudes are necessary to
generate positive affect toward the alliance.

Practical Implications

The interaction between firm and charity pre-existing atti-
tudes suggests that the organizations most likely to benefit
from a CRM alliance may in fact be those that need it least.
The greatest benefit is attained (a multiplicative enhance-
ment to attitudes) when pre-existing attitudes toward both
firm and charity are positive. Firms already enjoying positive
consumer attitudes may be particularly good candidates for
CRM campaigns, to further solidify their attitudinal advan-
tage.

These results also suggest that an organization may not be
able to overcome negative consumer attitudes by simply
forming a CRM alliance. If attitudes toward the firm are neg-
ative, it makes little difference whether the charity has posi-
tive or negative consumer attitudes. Attitudes toward the firm
change very little either way as a result of a CRM alliance.

Finally, fit is important for CRM alliances. CRM alliances
are seen as more appropriate when they fit. At least in part, fit
operates by strengthening perceptions of the firm and charity
relationship. Given that consumers are often skeptical about
firms’ motives for helping charities, enhancing perceptions
of the strength of the firm/charity relationship may help to re-
duce skepticism and thus should benefit the firm.

Limitations

This research faces the limitations common to many labora-
tory experiments in which student participants are used, in-
cluding questions of generalization. The homogenous sam-
ple, however, is acceptable for theory testing (Calder,
Phillips, & Tybout, 1981). Replications with “real-world”
samples are clearly warranted before extending our results
very far.

The benefit of a within-subjects design is that more CRM
alliance pairings could be tested without increasing sample
size. This also helps to assure that our results are not due to an
idiosyncratic CRM pairing. The within-subjects design may,
however, increase experimental awareness of the study par-
ticipants. Future research should seek to replicate this work
in a between-subjects design.

ACKNOWLEDGMENTS

We gratefully acknowledge funding from the University of
Colorado at Boulder.

402 BASIL AND HERR

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APPENDIX

Subjects rated their attitudes toward the following atti-
tude-formation statements on 11-point Likert scales. The av-
erage rating for each statement was then compared against
the scale midpoint (5), using a one-sample t test (or z test).
Mean scores significantly below five indicate statements that
generated negative attitudes. Mean scores significantly
above 5 indicate statements that generated positive attitudes.
Statements not significantly different from five represent
neutral attitudes. Each organizational profile contained three
valenced statements (positive or negative) and two neutral
statements.

Charity Statements

Average volunteer tenure is over 5 years, M = 7.0, t = 6.5, p < .0001

Average volunteer tenure is 3 months, M = 4.2, t = 4.3, p < .0001

http://www.pmalink.org

In an organization-wide survey, volunteers ranked their job
satisfaction as “very high”, on average, M = 8.3, t = 16.6, p < .0001

In an organization-wide survey, volunteers ranked their job
satisfaction as “somewhat low”, on average, M = 2.7, t =
12.2, p < .0001

An independently conducted survey of those charity X has
worked to help demonstrated very high levels of satisfaction,
M = 8.5, t = 15.6, p < .0001

An independently conducted survey of those Charity X has
worked to help demonstrated low to moderate levels of satis-
faction, M = 3.3, t = 6.8, p < .0001

An industry consortium of charities voted to honor the presi-
dent of Charity X for his exceptional management, M = 7.4, t
= 8.6, p < .0001

The president of Charity X is under investigation for misuse
of organization funds, M = 1.2, t = 18.2, p < .0001

Charity X has been operating for over 50 years, M = 7.9, t =
12.1, p < .0001

Charity X has been operating for almost 1 year, M = 4.5, t =
2.5, p = .016

Charity X was voted best overall charity by a consortium of
charities in their field, M = 8.6, t = 16.1, p < .0001

Charity X has not received any honors from the consortium
of charities, M = 4.3, t = 3.2, p = .003

Charity X has never been reported to the Better Business Bu-
reau for inappropriate fund-raising methods, M = 7.2, t = 6.6,
p < .0001

The Better Business Bureau recently received several com-
plaints regarding fund-raising methods of Charity X, M =
1.9, t = 13.4, p < .0001

Less than 10% of all funds donated go toward overhead, M =
7.4, t = 8.6, p < .0001

Approximately 50% of all funds donated go toward over-
head, M = 3.6, t = 4.9, p < .0001

Charity X operates in eight states, M = 5.4, t = 1.8, p = .078

Charity X has been in operation for 6 years, M = 5.6, t = 2.6, p
= .012

Charity X is headquartered in Tucson, Arizona, M = 5.1, t =
.62, p = .54

Firm Statements

ATTITUDINAL BALANCE 403

Average employee tenure is over 5 years, M = 6.3, t = 5.3, p < .0001

In a firm-wide survey, employees ranked their job satisfac-
tion as “very high”, on average, M = 8.5, t = 21.4, p < .0001

Average employee tenure is 3 months, M = 2.9, t = 8.5, p < .0001

In an organization-wide survey, employees ranked their job
satisfaction as “somewhat low”, on average, M = 2.5, t =
14.9, p < .0001

An independently conducted survey of customers demon-
strated very high levels of customer satisfaction, M = 8.1, t =
13.5, p < .0001

An industry consortium of businesses voted to honor the
president of Firm Y for his exceptional management, M =
7.5, t = 13.5, p < .0001

The president of Firm Y is under investigation for misuse of
corporate funds, M = 1.7, t = 17.6, p < .0001

Firm Y has been operating for over 50 years, M = 7.7, t =
12.3, p < .0001

Firm Y has been operating for almost 1 year, M = 4.6, t = 3.6,
p < .005

Industry analysts have ranked Firm Y as the best overall in-
vestment in its industry, M = 8.3, t = 14.6, p < .0001

Firm Y has never been ranked by industry analysts, M = 5.3, t
= .9, p < .4

Firm Y has never been reported to the Better Business Bu-
reau for inappropriate marketing methods, M = 6.6, t = 5.2, p
< .0001

The Better Business Bureau recently received several com-
plaints regarding marketing methods of Firm Y, M = 2.5, t =
13.8, p < .0001

Firm Y uses only the highest-quality materials/ingredients in
all aspects of production, M = 7.7, t = 10.2, p < .0001

The ingredients and materials used by Firm Y minimally
meet legal requirements, M = 3.8, t = 4.5, p < .0001

Firm Y operates in eight states, M = 5.7, t = 4.3, p < .0001

Firm Y has been in business for 6 years, M = 5.6, t = 4.8, p < .0001

Firm Y is headquartered in Tucson, Arizona, M = 4.9, t = .5, p
< .6

Soc (2011) 48:131–135
DOI 10.1007/s12115-010-9408-1

SYMPOSIUM: CONSUMER CULTURE IN GLOBAL PERSPECTIVE

Neuromarketing: The New Science of Consumer Behavior

Christophe Morin

Published online: 14 January 2011
# Springer Science+Business Media, LLC 2011

Abstract Neuromarketing is an emerging field that bridges
the study of consumer behavior with neuroscience. Contro-
versial when it first emerged in 2002, the field is gaining rapid
credibility and adoption among advertising and marketing
professionals. Each year, over 400 billion dollars is invested
in advertising campaigns. Yet, conventional methods for
testing and predicting the effectiveness of those investments
have generally failed because they depend on consumers’
willingness and competency to describe how they feel when
they are exposed to an advertisement. Neuromarketing offers
cutting edge methods for directly probing minds without
requiring demanding cognitive or conscious participation.
This paper discusses the promise of the burgeoning field of
neuromarketing and suggests it has the potential to signifi-
cantly improve the effectiveness of both commercial and
cause-related advertising messages around the world.

Keywords Neuromarketing . Advertising . Marketing
research . Consumer behavior . fMRI . EEG . Neuroscience

Imagine John, a healthy middle-aged man entering a
room filled with somber people dressed in white lab coats.

C. Morin (*)
110 Sir Francis Drake Blvd,
San Anselmo, CA 94960, USA
e-mail: christophe@salesbrain.com

John is worried. Maybe this is a mistake, he thinks. But
already one of the earnest technicians whose smile seems
just a little too forced is shaking his hand and spurring him
forward. He ensures him everything will go according to
plan. “It takes about 30 minutes to do the scan” he says
“and as long as you don’t pay attention to the noise, you
will be fine in the tunnel”. John does not feel nearly as
relaxed now as he was when he agreed to do this experiment.
What if the magnetic field in which I agreed to put my entire
body kills some of my vital cells? In an instant, he goes from
being worried to being terrified. What if the radiation alters
my mental abilities? Reluctantly, John lies down on the table
and tries to ignore the grinding sound of the pulley propelling
him to the center of the tunnel. In a matter of seconds, the
machine begins to bombard his head with subatomic particles.
“Too late now”, he mumbles.

So, who is John? Is he a patient coming for a clinical
evaluation or a fresh recruit taking part in a neuromarketing
study? John is a consumer, like you. But today, he agreed to
be part of a new breed of studies involving the use of the
latest tool available to investigate the workings of your
mind: an fMRI scanner. The brain has been long described
as the most complex structure in the universe. Many
consider fMRI the best technological innovation ever
developed to conduct clinical and experimental research
on the brain. No wonder there has been such tremendous
enthusiasm for neuroimaging technology since its emer-
gence in the mid-1980s. Additionally, the rapid progress in
mapping the brain’s circuitry has fueled the growth of
vibrant fields of study such as neuropsychology (under-
standing psyche through the study of cognitive processes),
neurophysiology (understanding the function of our ner-
vous system), neuroethology (understanding animal behav-
ior through the comparative study of our nervous systems),
and neuroanatomy (understanding the neural structures of
our nervous system).

Clearly, it was only a matter of time before marketers
and advertisers would also start considering the possibilities

mailto:christophe@salesbrain.com

132 Soc (2011) 48:131–135

of probing consumers’ brains using the same equipment
favored by neurologists and scientists around the world.
Could neuroscience be the holy grail of the study of
consumer behavior? Can neuromarketing succeed in devel-
oping predictive models that can explain why we buy
anything? These are questions that make some people
smile, and others cringe.

The (Short) History of Neuromarketing

The combination of neuro and marketing implies the
merging of two fields of study (neuroscience and market-
ing). The term neuromarketing cannot be attributed to a
particular individual as it started appearing somewhat
organically around 2002. At the time, a few U.S. companies
like Brighthouse and SalesBrain became the first to offer
neuromarketing research and consulting services advocat-
ing the use of technology and knowledge coming from the
field of cognitive neuroscience. Basically, neuromarketing
is to marketing what neuropsychology is to psychology.
While neuropsychology studies the relationship between
the brain and human cognitive and psychological functions,
neuromarketing promotes the value of looking at consumer
behavior from a brain perspective.

The first scholarly piece of neuromarketing research was
performed by Read Montague, Professor of Neuroscience at
Baylor College of Medicine in 2003 and published in
Neuron in 2004. The study asked a group of people to drink
either Pepsi or Coca Cola while their brains were scanned
in an fMRI machine. While the conclusions of the study
were intriguing, Dr Montague failed to provide a rationale
for how our brain handles brand choices. Nevertheless, the
study did reveal that different parts of the brain light up if
people are aware or not aware of the brand they consume.
Specifically, the study suggested that a strong brand such as
Coca Cola has the power to “own” a piece of our frontal
cortex. The frontal lobe is considered the seat of our
executive function (EF) which manages our attention,
controls our short-term memory, and does the best of our
thinking—especially planning. So according to the study,
when people know they are drinking Coca Cola, they
actually say they prefer the Coke brand over Pepsi and their
EF lights up. However, when they don’t know which
brand they are consuming, they report that they prefer
Pepsi instead. In this latter event, the part of the brain
which is most active is not the EF but an older structure
nestled in the limbic system. This brain area is responsible
for our emotional and instinctual behavior. The Coke and
Pepsi study may have not been enough to convince many
marketing researchers that neuroscience could help crack
the neural code of our decisions, but it was certainly
enough to worry many about its potential power.

Indeed, this study triggered a wave of heavy criticism
towards neuromarketing because of the fear that it harbored
a hidden code to tweak our perceptions below the level of
our consciousness. The journal Nature Neuroscience
published an article in 2004 entitled “Brain Scam” raising
the question of ethics behind neuromarketing studies.
Morality of neuromarketers was strongly questioned in the
paper. In response, Dr. Michael Brammer, the CEO of
Neurosense, a company who was mentioned in the article,
eloquently replied to the editor of the journal stating:

I would agree .. in urging caution in the exploitation
of any new technology. Scientific rigor and ethical
considerations are of paramount importance, but these
questions are not confined to commercial activities
but rather must apply to all our activities as scientists.
Only time will tell whether neuromarketing using
fMRI will become an established tool. If our crime is
to investigate its value in understanding behavior, and
to be paid in the process, we plead guilty.

Notably, this short-lived attack from the media did not
dissuade Harper Collins from adding the word “neuro-
marketing” to its dictionary in 2005. And by 2006, neither
the critical article from Nature Neuroscience nor the efforts
deployed by the consumer advocacy group Commercial
Alert succeeded in curbing the popularity and growth of
neuromarketing. Let’s explore why.

For too long, both marketers and advertisers have relied
on ancient ways to create and assess effective advertising
campaigns. Millions of dollars are poured each year into
developing products that will never see the light of day.
Countless campaigns fail to attract consumer attention and
successfully impact our memory banks. Ignoring neuro-
imaging as a way to understand consumer behavior would
be as absurd as astronomers refusing to use electronic
telescopes. Placing legitimate worries on ethics aside, there
is no question that neuroimaging provides powerful lenses
through which we can observe and understand the mind of
a consumer.

Understanding the Consumer’s Brain

For decades, marketing research methods have aimed to
explain and predict the effectiveness of advertising cam-
paigns. For the most part, however, conventional techni-
ques have failed miserably. Since emotions are strong
mediators of how consumers process messages, under-
standing and modeling cognitive responses to selling
messages has always been a methodological challenge.
For instance, researchers have primarily relied on consum-
ers’ abilities to report how they feel about a particular piece
of advertising, either in a confidential setting such a face-to-

133 Soc (2011) 48:131–135

face interview, a survey, or in a group setting such as a
focus group. Unfortunately, these methods have consider-
able limitations. First, they assume that people are actually
able to describe their own cognitive process which we now
know has many subconscious components. Second, numer-
ous factors motivate research participants to distort the
reporting of their feelings, including incentives, time
constraints, or peer pressure.

In this challenging context, the emergence of neuro-
imaging techniques has offered exciting methodological
alternatives. Such techniques finally allow marketers to
probe the consumers’ brains in order to gain valuable
insights on the subconscious processes explaining why a
message eventually succeeds or fails. They do so by
removing the biggest issue facing conventional advertising
research, which is to trust that people have both the will and
the capacity to report how they are affected by a specific
piece of advertising.

While the field of neuroscience has grown dramatically
in the last decade, it has not yet fully penetrated the dark
and reclusive hallways of advertising research academia.
Why? First, very few marketing researchers have formal
training in cognitive neuroscience. Second and more
importantly, marketing researchers have long feared the
public outcry against potential ethical and privacy issues
introduced by the use of neuroimaging technology for
commercial purposes. As a result, few scientific neuro-
marketing studies on advertising effectiveness have yet
been published. However, the situation is changing quickly.

Indeed, neuromarketing is fast becoming mainstream.
Today, tracking the popularity of the word “neuromarket-
ing” on Google shows a phenomenal progression from just
a few hits in 2002 to thousands in 2010. Meanwhile,
advertising agencies are beginning to clearly understand the
importance of predicting the effectiveness of campaigns by
using brain-based tools such as eye tracking, EEG, or fMRI.
Finally, the recent weakened economy continues to put
pressure on executives to predict and measure the return on
the massive dollars they invest in advertising campaigns of
all forms. Taking all these factors into account demonstrates
that the need for innovative advertising research using the
latest discoveries on the brain is both strong and timely.

Measuring Brain Response to Advertising Messages

There are many ways to measure physiological responses to
advertising but there are only three well established non-
invasive methods for measuring and mapping brain
activity: electroencephalography (EEG), magnetoencepha-
lography (MEG) and functional magnetic resonance imag-
ing (fMRI). All three imaging techniques are non-invasive
and therefore can be used safely for marketing research

purposes. That is why they constitute the bulk of studies
that have been published in the last five years. Each method
has its pros and cons.

EEG is a rather old technology in neurology but is still
considered a good way to measure brain activity. The cells
responsible for the biological basis of our cognitive
responses are called neurons. We have over 100 billion
neurons and trillions of synaptic connections which
represent the basis of neural circuitry. In the presence of a
particular stimulus like a piece of advertising, neurons fire
and produce a tiny electrical current that can be amplified.
These electrical currents have multiple patterns of frequen-
cies called brainwaves which are associated with different
states of arousal. When EEG is used for a marketing
research experiment, electrodes are placed on the scalp of a
test subject, typically by using a helmet or a band.
Brainwaves can be recorded at very small time intervals.
Some of the new EEG bands can record up to 10,000 times
per second. This is valuable considering the speed at which
we acquire information through our senses and the speed of
our thoughts. The limitation of EEG however is that it does
not have good spatial resolution which means it cannot
precisely locate where the neurons are firing in the brain,
especially in deeper, older structures. This is simply
because the electrodes on the scalp cannot pick up electrical
signals that reside much beyond the cortex. Lastly, since it
is estimated that nearly 80% of our brain activity is used to
sustain a critical state called “rest time” or “the default
mode” or simply “baseline”, it is hardly possible to claim
that the brainwaves generated by specific advertising
stimuli are entirely produced by the stimuli.

The first psychological studies done using EEG date as
far as 1979. Davidson was one of the first cognitive
scientists to propose a framework for linking affect and
electrical patterns in the brain. His studies and others later
validated that electrical patterns were lateralized in the
frontal region of the brain. Generally, the measure of
alpha-band waves (8–13 Hz) in the left frontal lobe
indicates positive emotions. It is further speculated that
such activity is a good predictor of how motivated we are
to act. On the other hand, electrical activity in the right
frontal lobe is typically correlated with negative emotions.
Such emotions generally prepare us to withdraw from an
experience.

Though the relative low cost of using EEG has made the
technology very popular among neuromarketing agencies
in the last 5 years, it is widely considered by cognitive
scientists as weak if not dubious for the purpose of
understanding and predicting the effects of advertising.
While insights gained by using EEG can be helpful to
assess the value of a piece of advertising, they are
insufficient to help us understand the cognitive process
responsible for triggering activity in the entire brain.

134 Soc (2011) 48:131–135

Considered a cousin to EEG, MEG emerged in the mid-
sixties and has gained considerable attention in the last
decade because of the tremendous improvements made in
measuring and imaging magnetic fields in the brain. As we
discussed earlier, brain activity is a function of electro-
chemical signals between neurons. Neuronal activity
creates a magnetic field that can be amplified and mapped
by MEG. MEG has excellent temporal resolution, but more
importantly, a better spatial resolution than EEG. However,
like EEG, MEG is somewhat limited to picking up activity
at the surface of the brain; hence it is not a good method for
imaging subcortical areas. While the technology is very
expensive and has limitations, a few valuable studies have
demonstrated that specific frequency bands correlate to
controllable cognitive tasks such as recognizing objects,
accessing verbal working memory, and recalling specific
events. This in fact suggests that the best way to use MEG
is to measure activity in areas known or expected to
produce activity given specific tasks rather than to conduct
exploratory experiments.

So, while MEG is continuing to improve and provides
an excellent way to record nearly real-time responses to
cognitive events, it is not ideal to conduct marketing
research studies investigating both higher cognitive func-
tions (cortical) and emotional (subcortical). Most research-
ers working with MEG combine both MEG and fMRI in
order to optimize both temporal and spatial resolution
issues and/or provide the added value of time stamping
critical cognitive sequences at the incredible speed of just a
few milliseconds.

Unlike both EEG and MEG, the fMRI modality is based
on using an MRI scanner to image the change of blood flow
in the brain. When neurons fire, they need to use energy
which is transported by the blood flow and quickly
metabolized. The key element for a marketing researcher
to understand is the contrast of the BOLD signal measured
by the fMRI. BOLD is an acronym for Blood Oxygen Level
Dependant. When faced with a particular stimulus such as
an ad, areas of a subject’s brain receive more oxygenated
blood flow than they do at rest time. This change creates
distortions in the magnetic field emitted by hydrogen
protons in the water molecules of our blood. The basis of
all fMRI studies is to consider that the change in the BOLD
signal is an accurate measure of neuronal activity, even
though it does not directly measure electrochemical signals
generated by our neurons. While the spatial resolution of
fMRI is 10 times better than EEG by providing researchers
the ability to image the activity of a voxel (Volume-Pixel), a
cube of neurons (1 mm x 1 mm x 1 mm in size), the
temporal resolution of the technology is considered rather
slow. Indeed, there is a delay between the times a neurons
fires and the time it takes for the BOLD signal to change:
usually a couple of seconds. Nevertheless, fMRI has the

major advantage of being able to image deep brain
structures, especially those involved in emotional
responses. fMRI scanners are also quite expensive but
more widely available than MEG equipment. All these
factors combined explain why fMRI is the most frequently
used brain imaging techniques in the world today and in
most likelihood will become the preferred option for
neuromarketing scientists for years to come.

What Can We All Learn from Neuromarketing?

If neuroscience is considered to be in its infancy, neuro-
marketing is clearly at an embryonic stage. Marketers are
just awakening to the possibilities offered by unveiling the
brain circuits involved in seeking, choosing, and buying a
product. While many of the studies done by neuromarketers
are commercial and as such don’t go through the standards
and review process imposed by academics, enough evi-
dence has been already published to highlight a few core
neurocognitive principles at play when consumers perceive
advertising messages. Back in 2002, I co-authored the first
book on neuromarketing outlining such principles without
having the benefit of validating many of my assumptions.
Since then however, I have collected tremendous scientific
and empirical evidence to support the basis of a sound
neuromarketing model. It looks like this:

The brain is responsible for all our consumer behaviors.
To function properly, it needs to use a lot of energy. Even
though the brain is only 2% of our body mass, it burns
nearly 20% of our energy. Most of the functions we need to
go through a day are managed by the brain below our level
of consciousness. This explains why nearly 80% of our
brain energy is necessary to sustain our rest state or default
mode, a critical aspect of brain functioning which continues
to puzzle neuroscientists. Clearly, we only use about 20%
of our brain consciously. Worse, we do not control the bulk
of our attention since we are too busy scanning the
environment for potential threats. Because nothing matters
more than survival, we are in fact largely controlled by the
most ancient part of our brain known as the R-complex or
the reptilian brain.

The reptilian brain has developed over millions of years.
It is pre-verbal, does not understand complex messages, and
seeks pain avoidance over thrills. It is the part of the brain
that makes us extremely selfish and drives our strong
preference for mental shortcuts over long deliberations. The
most powerful aspect of the reptilian brain is the fact that it
is able to process visual stimuli without the use of the visual
cortex. This is why we prefer images over words and
experiences over explanations. Antonio Damasio, a well-
known neuroscientist and respected author once said, “We
are not thinking machines that feel, we are feeling machines

135 Soc (2011) 48:131–135

that think”. What Damasio and many others have demon-
strated is that while we appreciate and even worship our
cognitive abilities, the brain has been dependent on
instinctual responses for millions of years. And it will
continue to do so for a long time since biological adaptation
to a fast changing environment is too slow. What does this
mean from a neuromarketing perspective? It means that
there are specific principles that should apply to advertising
messages in order to optimize the processing of information
at the level of our brain. In today’s world, we receive an
average of 10,000 messages per day. This volume of data is
largely irrelevant unless it speaks directly to the reptilian
brain.

Back at the lab, John feels better. The scan is done. This
was not so hard, he thinks. Plus he took advantage of the
opportunity to insert a picture of his family at the end of the
experiment. The neuroscientist in charge of the study told
him that he would love to see his brain at the precise
moment he would feel love and attachment. Wow!

Neuromarketing is here to stay. And it will evolve, like
humans—and even brands—do. Consumers like you may
never see the difference in the messages that are refined or
produced as a result of gaining a better understanding of
our buying decision process. Ethical issues will continue to
surface but standards have already been adopted to make
sure that neuromarketing research is conducted with respect
and transparency. Let’s also remember that many advertis-
ing messages are not commercial either. Countless cam-
paigns aim at changing people’s self-destructive behaviors.
For example, there is a tremendous need to improve our

ability to convince people not to smoke or not text and
drive. Words don’t work. Pictures do. Why? It is a reptilian
brain thing!

Further Reading

Ariely, D., & Berns, G. S. 2010. Neuromarketing: The hope and hype of
neuroimaging in business. Nature reviews Neuroscience (March).

Fugate, D. L. 2007. Neuromarketing: A layman’s look at neuroscience
and its potential application to marketing practice. Journal of
Consumer Marketing, 24(7), 385–394.

Glimcher, P. W. 2009. Neuroeconomics: Decision-making and the
brain. London: Elsevier.

Kenning, P., Plassmann, H., & Ahlert, D. 2007. Applications of
functional magnetic resonance imaging for market research.
Qualitative Market Research, 2, 135–152.

Knutson, B., Rick, S., Wimmer, E. G., Prelec, D., & Loewenstein, G.
2007. Neural predictors of purchases. Neuron, 53, 147–156.

Lee, N., Broderick, L., & Chamberlain, L. 2006. What is ‘neuro-
marketing’? A discussion and agenda for future research.
International Journal of Psychophysiology, 63, 200–204.

Christophe Morin received his MBA in Marketing Research and
Organizational Behavior from Bowling Green State University and is
currently pursuing a PhD in Media Psychology with Fielding
Graduate School in Santa Barbara, California. Before co-founding
SalesBrain in 2002, he held several key executive positions in
technology, retail, and leadership companies. Since 2002, he has
lectured extensively on the subject of neuromarketing in the US, in
Europe and Asia delivering over 500 workshops on the subject. He is
co-author of Neuromarketing: Understanding the Buy Buttons in Your
Customer’s Brain (Nelson).

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