ArticlePDF Available

Brand Familiarity and Advertising Repetition Effects



A crucial communication task for unknown brands is to build the knowledge in consumers' minds necessary to become established. However, communication effectiveness may depend on prior familiarity of the advertised brand. The findings of two experiments using television ads and computer Internet ads revealed that brand familiarity influenced repetition effectiveness. In particular, repetition of advertising attributed to an unfamiliar brand showed decreased effectiveness; when the same advertising was attributed to a known, familiar brand, repetition wearout was postponed. Negative thoughts about tactic inappropriateness were seen to arise with repetition, particularly for an ad for an unfamiliar brand, driving, in part, the decreases in repetition effectiveness. Copyright 2003 by the University of Chicago.
2003 by JOURNAL OF CONSUMER RESEARCH, Inc. Vol. 30 September 2003
All rights reserved. 0093-5301/2004/3002-0010$10.00
Brand Familiarity and Advertising Repetition
A crucial communication task for unknown brands is to build the knowledge in
consumers’ minds necessary to become established. However, communication
effectiveness may depend on prior familiarity of the advertised brand. The findings
of two experiments using television ads and computer Internet ads revealed that
brand familiarity influenced repetition effectiveness. In particular, repetition of ad-
vertising attributed to an unfamiliar brand showed decreased effectiveness;when
the same advertising was attributed to a known, familiarbrand, repetition wearout
was postponed. Negative thoughts about tactic inappropriateness were seen to
arise with repetition, particularly for an ad for an unfamiliar brand, driving, in part,
the decreases in repetition effectiveness.
The influence of repetition on communication effective-
ness is an important issue that has generated a consid-
erable body of research. Consumer researchers, psycholo-
gists, and marketers have attempted to understand the
relationship between repetition and an audience’s reception
of a message. The leading theory is that there is a non-
monotonic relationship between message repetition and
message effectiveness (cf. Anand and Sternthal 1990; Vak-
ratsas and Ambler 1999). Message effectiveness is believed
to increase at low levels of repetition and then to decrease
as message repetition increases (cf. Berlyne 1970; Cacioppo
and Petty 1979). There is strong evidence in support of such
a curvilinear relationship (cf. Anand and Sternthal 1990;
Batra and Ray 1986; Pechmann and Stewart 1989). There
is also, however, substantial research that shows no rela-
tionship between ad repetition and message effectiveness
(Belch 1982; Mitchell and Olson 1977; Rethans, Swasy, and
Marks 1986) or mixed effects in terms of the curvilinear
relationship (Calder and Sternthal 1980; Messmer 1979).
A review of the literature on repetition effects suggests
that there is no simple answer to the question of how rep-
*Margaret C. Campbell is assistant professor of marketing, University
of Colorado at Boulder, Leeds School of Business, Boulder, CO 80309; e-
mail: Kevin Lane Keller is E. B. Osborn
Professor of Marketing, Amos Tuck School of Business, Dartmouth Col-
lege, Hanover, NH 03755; e-mail:
from Jennifer Aaker, Julie Edell, John Lynch, and seminar participants at
Dartmouth College, San Diego State University, the University of Florida,
the University of North Carolina at Chapel Hill, and the University of
Texas at Austin, and ad design from MAKE are greatly appreciated. The
authors also thank the JCR review team for their beneficial input. Financial
assistance from the University of California, Los Angeles, Marketing Study
Center is appreciated. Correspondence should be addressed to the first
etition affects message effectiveness. Several researchers
have called for and turned their attention to factors that
moderate the relationship between repetition and message
effectiveness. For example, research has identified several
message factors that influence the effects of repetition, in-
cluding message complexity (Cox and Cox 1988), “grabber
versus nongrabber” ads (Ray and Sawyer 1971), and ease
of processing of the message (Anand and Sternthal 1990).
We propose an important source factor as a moderator of
repetition effects. Specifically, we propose that the famil-
iarity of the brand sponsor of an ad will moderate the way
in which repetition influences consumer response to that ad.
Additionally, we contribute to existing research by describ-
ing more completely the mechanism by which a decrease
in attitudes with an increase in repetition may occur. We
begin by describing the two-factor theory of repetition ef-
fects. We then apply the two-factor theory to examine how
familiarity with the brand sponsor might influence the ef-
fectiveness of repeated exposure to an ad. Two experiments
demonstrate that brand familiarity is an important moderator
of repetition effects and provide insight to the process by
which this moderation occurs.
The leading explanation of repetition effects is based on
Berlyne’s (1970) two-factor theory. This theory proposes a
two-part process by which repetition influences message
response. The first phase, sometimes called “wearin,” is one
of habituation. In this phase, there may be a certain amount
of what is called hostility or uncertainty about an unfamiliar
message. Initial levels of message repetition serve to in-
crease positive habituation by reducing negative responses
to the novel stimulus, thus increasing effectiveness at lower
levels of repetition (Cox and Cox 1988). The second phase,
sometimes called “wearout,” is when continued repetition
results in the onset of tedium such that the message decreases
in effectiveness (Anand and Sternthal 1990; Blair and Ra-
buck 1998; Calder and Sternthal 1980). Tedium arises be-
cause of boredom, less opportunity to learn, and reactance
against the repeated message.
Two important conceptual contributions have been made
to the two-factor theory of repetition effects. First, Cacioppo
and Petty (1979) examined the processing and memory ef-
fects underlying Berlyne’s theorizing. They demonstrated
that cognitive responses to the message appear to mediate
the effects of repetition on the overall evaluations engen-
dered by an ad: support arguments first increase and then
decrease with repetition; counterarguments, by contrast, may
first decrease and then increase with repetition. Cacioppo
and Petty (1979) show that repetition has its greatest effect
at moderate levels of repetition. It appears that under low
levels of repetition resources are not sufficient for complete
processing but that high levels of repetition prompt coun-
terargumentation. Second, Anand and Sternthal (1990) show
that, in addition to the important effects of resource avail-
ability, resource requirements for processing influence the
effect of repetition. They show that the ease of processing
moderates the influence of repetition on brand attitude.
Greater processing difficulty slows the habituation and te-
dium experienced by the consumer so that the point atwhich
ad wearout occurs is delayed, while low processing difficulty
speeds up the point at which wearout occurs. Anand and
Sternthal (1990) conclude that both resource availability and
resource requirements influence when repetition effects will
be greatest.
Brand Familiarity
We draw on this theorizing to propose that brand famil-
iarity is an important variable that can influence consumer
processing and the stages of habituation and tedium. Brand
familiarity reflects the extent of a consumer’s direct and
indirect experience with a brand (Alba and Hutchinson
1987; Kent and Allen 1994). Brand familiarity captures con-
sumers’ brand knowledge structures, that is, the brand as-
sociations that exist within a consumer’s memory. Although
many advertised products are familiar to consumers, many
others are unfamiliar, either because they are new to the
marketplace or because consumers have not yet been ex-
posed to the brand (Stewart 1992).
Familiar and unfamiliar brands differ in terms of the
knowledge regarding the brand that a consumer has stored
in memory. Consumers tend to have a variety of different
types of associations for familiar brands. Consumers may
have tried or may use a familiar brand, they may have family
or friends who have used the brand and told them something
about it, they may have seen prior ads or marketing com-
munications for the brand, or they may know how the brand
is positioned, packaged, and so on, from the press. Con-
sumers lack many associations for unfamiliar brands be-
cause they have not had any of these types of experiences
with them.
Processing and Brand Familiarity. One possibility
might be that consumers would have negative reactions to
the repetition of ads for familiar brands more quickly than
they would to ads for unfamiliar brands. Because consumers
already know something about familiar brands, ads for these
brands might seem less interesting than ads for novel brands
that consumers do not know. Following this line of reason-
ing, ads for unfamiliar brands might seem less boring than
those for familiar brands, such that wearout would be post-
poned for unfamiliar brands. However, consideration of the
processing engendered by unfamiliar versus familiar brands
actually suggests the hypothesis that ads for unfamiliar
brands can wearout more quickly than ads for familiar
brands, as follows.
Because of knowledge differences, consumers are likely
to have different processing goals when exposed to ads spon-
sored by unfamiliar and familiar brands. People tend to at-
tempt to learn about and evaluate novel stimuli (e.g., Sujan
1985). Thus, when consumers are exposed to an ad for an
unfamiliar brand, they are more likely to have a goal of
learning about and forming an accurate impression of the
brand (Hilton and Darley 1991). To put it another way, if
ads for unfamiliar brands appear more novel and interesting,
they will therefore elicit more extensive processing.
When exposed to an ad for a familiar brand, by contrast,
consumers already have some knowledge about the brand
and, therefore, are more likely to update their existing
knowledge (Snyder and Stukas 1999). Since consumers al-
ready know something about familiar brands, they are likely
to engage in relatively less extensive, more confirmation-
based processing when exposed to an ad for a familiar brand
(Keller 1991; MacKenzie and Spreng 1992). In fact, fa-
miliarity can itself use cognitive capacity such that pro-
cessing of a familiar, relative to an unfamiliar, stimulus is
diminished (Britton and Tesser 1982), although it should be
recognized that consumers may not always engage in highly
involved processing, in an absolute sense, in either case.
The more extensive processing elicited by ads for unfamiliar
brands increases the resource availability; since, as noted
above, excess resource availability leads to wearout (Ca-
cioppo and Petty 1979; Calder and Sternthal 1980), these
ads should show decreased repetition effectiveness at a
lower number of ad exposures relative to ads for familiar
Effects of Habituation and Tedium. Habituation is the
process by which initial uncertainty or negativity to an un-
familiar stimulus is attenuated (Berlyne 1970; Vakratsas and
Ambler 1999). When a consumer first sees an ad for an
unfamiliar brand, there are two sources of unfamiliarity to
which the consumer could respond negatively: the ad itself
is novel, and the brand is also novel. The first time that a
consumer sees a new ad for a familiar brand, there is only
one source of unfamiliarity—the ad. Thus, negative uncer-
tainty created by unfamiliarity should be higher for a new
ad from an unfamiliar as compared with a familiar brand
Tedium arises from boredom and reactance or annoyance
to the repeated message (Anand and Sternthal 1990; Berlyne
1970). When consumers are repeatedly exposed to an ad for
an unfamiliar brand, they process primarily in order to learn
about the brand, and once they have been exposed to the
same ad several times, there is very little left to process or
learn (Krugman 1972). As noted above, consumers have
stored knowledge in memory for familiar, but notunfamiliar,
brands and thus are likely to process ads for familiarbrands
less extensively than those for unfamiliar brands. In addition,
the stored knowledge provides processing material for fa-
miliar brands that does not exist for unfamiliar brands. Thus,
to the extent that consumers continue to process an ad for
a familiar brand over repeated exposures to the ad, in ad-
dition to the material presented in the ad itself, the brand
knowledge that exists in memory provides context for con-
tinued processing (Britton and Tesser 1982). Since no such
additional knowledge exists for unfamiliar brands, consum-
ers are likely to “run out” of material to process with re-
peated exposure to the same ad. In other words, because of
a lack of stored knowledge, the processing requirementsare
much lower for the same ad for an unfamiliar than for a
familiar brand, which is likely to hasten the onset of wearout
(Anand and Sternthal 1990).
Effects on Cognitive Responses. As noted above, ear-
lier research suggests that consumers’ cognitive responses
to repeated messages may mediate the effects of repetition
on attitudinal response (Cacioppo and Petty 1979). This
work showed that support arguments first increase and then
decrease with message repetition, whereas counterargu-
ments show the opposite pattern. More extensive processing
should increase the rate at which these patterns of support
and counterargumentation occur relative to less extensive
processing. A consumer who engages in more extensive
processing of an ad should deplete support arguments and
therefore generate counterarguments at a lower level of rep-
etition than a consumer who engages in less extensive pro-
cessing. This adds support to our proposition that ads for
unfamiliar brands will wear out more quickly than ads for
familiar brands.
In addition, we propose that a specific type of thought is
likely to arise with ad repetition, contributing to wearout
effects. Recently, there has been growing interest in how
consumers’ thoughts about marketers’ persuasion tactics af-
fect their responses to marketing activities (see Friestad and
Wright 1994; Kirmani and Wright 1989). Consumers have
been shown to consider the inappropriateness of advertising
tactics sometimes (Campbell 1995; Sagarin et al. 2002).
Research has shown that cognitive capacity is necessary for
consumers to access and use thoughts about marketers’ per-
suasion tactics (Campbell and Kirmani 2000). Importantly,
prior research indicates that consumers are likely to focus
on message content at low levels of processing but are more
likely to access “negative tactics-related thoughts” when
processing is more extensive (Shiv, Edell, and Payne 1997,
p. 290).
As noted above, consumers are likely to process an ad
more extensively when it is for an unfamiliar rather than a
familiar brand. Additionally, because of the lack of stored
knowledge, consumers are likely to deplete possible brand-
related processing at a lower level of repetition of ads for
unfamiliar rather than familiar brands. Because of these pro-
cessing differences, consumers should be more likely to
have the cognitive capacity to think about the appropriate-
ness of advertising tactics at comparatively lower levels of
repetition of an ad for an unfamiliar brand as compared with
a familiar brand (Campbell and Kirmani 2000; Shiv et al.
1997). Moreover, in general, brand reputation has been
shown to decrease the extent to which consumers consider
persuasion inappropriateness (Campbell 1999). It follows
that consideration of tactic inappropriateness should increase
to a greater extent with repetition of an ad for an unfamiliar
rather than a familiar brand.
Effects of Ad Attitudes on Brand Attitudes. Finally,
the extent of consumer processing elicited by a message
should also affect the relation between attitude toward the
ad and brand evaluations. Specifically, when consumers are
unfamiliar with an advertised brand, they lack prior knowl-
edge on which to base attitudes toward the brand. Thus,
they are more likely to rely on attitudes toward the ad in
forming attitudes toward the brand. Consumers with prior
brand familiarity, by contrast, are more likely to draw on
their existing brand knowledge, attenuating the influence of
attitude toward the specific ad on attitude toward the brand.
Thus, the effect of attitude toward the ad on brand evalu-
ations should be greater when the ad is for an unfamiliar
rather than a familiar brand (Machleit, Allen, and Madden
1993; Machleit and Wilson 1988). That is, ad and brand
attitudes may be expected to be more divergent in the case
of familiar versus unfamiliar brands.
Prior Research. Although the impact of brand famil-
iarity on repetition effects has not been systematically stud-
ied, there is some research that is consistent with the notion
that brand familiarity will attenuate advertising wearout
(e.g., Edell and Burke 1986; Kardes 1994; Kent and Allen
1994; Lodish et al. 1995). An earlier study that examined
advertising repetition effectiveness used two products as
replicates: one product was “relatively unfamiliar to partic-
ipants,” whereas the other was “well known to the research
participants” (Calder and Sternthal 1980, p. 176). Interest-
ingly, while brand familiarity was not a focus of the research
and was not discussed, there were different patterns of re-
sults for the two brands. Although there was support for
wearout for the relatively unfamiliar brand, there was limited
evidence of wearout for the more familiar brand.
Likewise, as noted above, there have been mixed findings
on the relationship between repetition and advertising ef-
fectiveness. Although brand familiarity cannot fully account
for differing effects, it is interesting to note that several of
the studies that fail to support the curvilinear relationship
between repetition and effectiveness have used familiar
brands (e.g., Messmer 1979; Rethans et al. 1986). Relatedly,
research on other communication issues has shown that
brand familiarity can be an important variable that moderates
advertising interference (Kent and Allen 1994), humor in
advertising (Stewart and Furse 1986), and comparison ad-
vertising (Pechmann and Stewart 1990). All of this research
is consistent with the notion that brand familiarity will mod-
erate the effects of ad repetition.
In short, we propose that consumers will respond differ-
ently to the repetition of an ad sponsored by a familiar as
compared with an unfamiliar brand. Consumers willprocess
an ad with an unfamiliar brand sponsor more extensively
than an ad with a familiar brand sponsor. Because of the
processing differences, consumers will be more likely to
consider advertising (in)appropriateness for unfamiliar
rather than familiar brands. As a result, the number of ex-
posures at which wearout occurs and advertising effective-
ness begins to decrease will be lower when the ad comes
from an unfamiliar as compared with a familiar brand. Ad-
ditionally, attitudes engendered by an ad are less likely to
influence attitudes toward familiar than toward unfamiliar
We report results from two experiments that examine ad-
vertising repetition effects for familiar and unfamiliar brands
in terms of both attitude toward the ad and attitude toward
the brand. In study 1, we demonstrate that advertising wear-
out occurs with fewer repetitions of an ad for unfamiliar
rather than familiar brands and begin exploring the types of
thoughts that underlie this effect. In study 2, we replicate
these effects and specifically measure perceptions of ad-
vertising inappropriateness and demonstrate the mediation
of the effects of repetition and brand familiarity on ad
Subjects and Design
Ninety-four adult staff members at a West Coast univer-
sity participated in an hour-long study in exchangefor $5.00
and a chance for a cash prize. Subjects were randomly as-
signed to a 2 (brand familiarity: familiar or unfamiliar) #
(ad repetition: 1, 2, or 3 exposures (product: bank,3)#3
women’s clothing, or health-care plan) factorial design.
Brand familiarity was a between-subject factor, and ad rep-
etition and product were within-subject factors.
All subjects watched a half-hour local news show from
a different state. The news program included three ad breaks.
Each break included three ads: the first break showed two
filler ads and one test ad, the second break showed one filler
and two test ads, and the third break had three test ads. The
test ad shown in the first break also appeared in the second
and third breaks (repetition level of three). The test ad first
shown in the second break was also in the third (repetition
level of two). The ad that first appeared in the third break
was seen only once (repetition level of one). The ads were
rotated and counterbalanced for order and repetition level;
each ad appeared in each position in each ad break.
Test ads were selected from compilation videos of “good”
advertising, that is, either the advertising agency or an out-
side judge considered the commercials to represent effective
advertising. Ads were selected that had aired in regions
different from the study locale. A familiar and a fictitious
brand name were chosen for each product category. Pretests
indicated that people drawn from the same subject pool as
the actual study had (1) not seen the ads, (2) were familiar
with the familiar brand, but (3) were unfamiliar with the
fictitious brand. A professional video editor replaced the
original brand name frames in each ad with either the fa-
miliar or the unfamiliar brand name frames to create two
ads from each original ad. A final pretest indicated that
subjects felt that the test ads were typical and of good qual-
ity. No one in the pretest suggested that the ads were not
Subjects were asked to watch a television news program
and then to answer questions about the programming. After
watching for a half-hour, subjects completed filler questions
about the news show. They then completed measures of
uncued recall, brand recall cued by product category, open-
ended thought listing, and brand and ad attitudes. Brand
attitudes (Ab) were measured with a four-item, seven-point
differential scale, anchored by bad–good, low quality–high
quality, unappealing–appealing, and unpleasant–pleasant,
and the items were averaged (Cronbach’s ). At-alpha p.88
titude toward the ad (Aad) was measured with a four-item
scale with the same anchors (Cronbach’s ). Af-alpha p.91
ter completing these measures for the test ads, subjects com-
pleted manipulation checks and covariate measures. Sub-
jects indicated how familiar they were with each brand prior
to seeing the ads and how many times they remembered
seeing an ad for each brand. Subjects then indicatedproduct
category involvement, gender, age, and education level.
A full model that included interactions among the product
category, ad order, brand type, and ad repetition factorswas
analyzed to determine whether the data could be pooled.
The lack of any significant interactions with product cate-
gory or ad order indicated that the pattern of effects of the
experimental factors did not depend on the particular prod-
uct category or the order in which the ads were seen. Thus,
the data were collapsed across the three product categories
and three different ad orders.
Analyses were conducted with
a model that included brand familiarity as a between-subject
factor and ad repetition as a within-subject factor.
Manipulation Checks. Consistent with pretest results,
analysis of the measure of prior brand familiarity revealed
only a significant main effect of brand type (F(1,87) p
, ): ratings for familiar brands ( )94.6 p!.0001 Mp5.05
were substantially higher than for unfamiliar brands
( ). Analysis of recall of message content revealedMp1.95
a significant effect of repetition ( ,F(2,184) p81.1 p!
and no other significant effects; recall increasedwith.0001)
repetition. Similarly, there was a main effect of repetition
on self-reports of ad repetition ( ,F(2,172) p365.1 p!
) and no other significant effects. Subjects demon-.0001
strated quite accurate memory for the number of times they
had seen each ad ( , , ).TheMp1.02 Mp2.16 Mp2.90
results suggest a successful manipulation of both the brand-
familiarity and ad-repetition variables.
Attitude Effects. We examined the effects of ad repe-
tition on message effectiveness by exploring both attitude
toward the ad (Aad) and attitude toward the brand (Ab). An
ANOVA of Aad revealed a significant main effect of rep-
etition ( , ), qualified by a significantF(2,157) p4.1 p!.02
interaction effect between brand familiarity and ad repetition
( , ). A follow-up analysis revealed aF(2, 157) p3.5 p!.03
significant increasing linear trend in Aad for familiar brands
( , ). The Aad for unfamiliar brands,F(1,32) p4.4 p!.04
as expected, showed a significant quadratic trend
( , ), first increasing (F(1,36) p5.0 p!.03 F(1, 158) p
, ) and then decreasing (10.3 p!.002 F(1,158) p5.3, p!
; see fig. 1). These results show that, over this repetition.02
schedule, ads for unfamiliar brands exhibited a decline in
ad attitudes, but ads for familiar brands did not. This sup-
ports the idea that ads for unfamiliar brands show wearout
more quickly than do ads for familiar brands.
Analysis of Ab showed significant effects of brand fa-
miliarity ( , ) and ad repetitionF(1,90) p4.5 p!.04
( , ), qualified by a significant in-F(2,158) p3.76 p!.03
teraction effect between brand familiarity and ad repetition
( , ). The Ab showed a directionalF(2, 158) p4.1 p!.02
increasing linear trend for familiar brands ( ,F(1,32) p1.9
). When the brand was unfamiliar, there was a sig-p!.17
nificant quadratic trend ( , ): Ab in-F(2,37) p8.7 p!.005
creased from one to two exposures ( ,F(1,158) p11.8 p!
) and decreased from two to three exposures.001
(,).F(1,158) p5.2 p!.03
As discussed above, because consumers are likely to update
existing attitudes toward a familiar brand but to form an
attitude toward an unfamiliar brand, the extent to which at-
titudes toward the ad affect brand attitudes should vary by
One of the three ads, the ad for the health-care plan, was liked better
than the others. While the well-liked ad resulted in higher attitudes toward
the ad (5.77 vs. 3.90 and 4.52; , ) and the brandF(2, 147) p34.0 p!.001
(5.02 vs. 4.26 and 4.42; , ) than the two moderatelyF(2,147) p8.2 p!.001
liked ads, these were main effects. There were no significant interactions,
showing that the pattern of effects was not affected by ad likability.
brand familiarity. To test this, we conducted a regression of
Aad, brand familiarity, and their interaction on Ab. Not sur-
prisingly, Aad was a significant predictor of Ab ( ,bp.40
, ), as was brand familiarity ( ,tp7.6 p!.0001 bp.97
, ). Importantly, the interaction was alsotp2.63 p!.01
significant ( , , ). The significance andbp.14 tp2.0 p!.05
direction of the interaction parameter estimate show that, as
predicted, Aad had a significantly greater influence on Ab
when the brand was unfamiliar than when it was familiar.
These results indicate that ads for unfamiliar brands show
declines in attitudinal response—that is, they show wearout—
more quickly than do ads for familiar brands. This also
shows that attitude toward the ad has a more powerful im-
pact on brand attitudes for unfamiliar than for familiar
brands. We next explore the respondents’ thoughts in re-
sponse to the ads in order to gain a better understanding of
the processing that people engage in when messages are
Processing Effects. Thoughts were coded in terms of
support arguments, counterarguments, negative tactic-
related thoughts, and irrelevant thoughts. Following the lit-
erature, support arguments were thoughts that agreed with
or bolstered the message advocacy, while counterarguments
were those thoughts that disagreed with or countered the
advocacy position (Wright 1973). Negative tactic-related
thoughts were defined as “thoughts that indicate that the
subject is considering the persuasive, tactical nature of the
ad; thoughts about the advertiser’s strategy and the appro-
priateness of the strategy.” Thus, negative tactic-related
thoughts were a separate category, not just a subset of coun-
terarguments. Examples of negative tactic-related thoughts
from the data include, “I thought poorly of the company’s
marketing folks for advertising like that,” “it was very ob-
vious that they were trying to promote this ad by using sex,”
and “ad ploy to get one to recall ad over those of another
Level of repetition
Familiar Unfamiliar
Dependent measure 1 2 3 1 2 3
Attitude toward the ad 4.56
(1.71) 4.73
(1.87) 5.24
(1.66) 4.14
(1.93) 5.26
(1.60) 4.41
Attitude toward the brand 4.67
(1.16) 4.65
(1.46) 5.06
(1.16) 3.94
(1.39) 4.79
(1.22) 4.26
Total thoughts 1.33
(1.63) 1.93
(1.42) 2.55
(1.52) 1.52
(1.64) 3.06
(2.16) 3.17
Support arguments .63
(.94) .67
(1.05) .98
(1.25) .76
(1.30) 1.40
(1.52) .64
Counter arguments .54
(1.17) .70
(.89) .49
(.69) .52
(.91) .75
(1.21) 1.14
Difference score: Support—
counter .08
(1.61) .49
(1.65) .24
(1.75) .65
Negative tactic-related
thoughts .14
(.36) .33
(.47) .55
(.62) .19
(.45) .36
(.48) 1.02
company based on number of times shown.” Two indepen-
dent coders, blind to experimental conditions, coded sub-
jects’ listed thoughts with 93% agreement; differences were
resolved through discussion.
Analysis of the total number of thoughts showed main
effects of brand familiarity ( , ) and adF(1,89) p5.6 p!.02
repetition ( , ), qualified by a sig-F(2,182) p34.7 p!.0001
nificant interaction between brand familiarity and ad repe-
tition ( , ). Total thoughts increasedF(2,182) p4.4 p!.01
with repetition both when the advertised brand was familiar
and when it was unfamiliar, but the patterns differed (see
table 1). Trend analysis revealed a significant quadratictrend
over ad repetition for the unfamiliar brands (F(1,54) p
, ) and showed only a significant increasing lin-9.4 p!.005
ear trend, but no quadratic trend, for the familiar brands
(linear: , ; quadratic: ).F(1,45) p23.4 p!.0001 F(1, 45) !1
Interestingly, there was no significant difference between
the total thoughts for familiar versus unfamiliar brands at
the first ad exposure ( , ;Mp1.33 Mp1.52 F(2,182) !
, ). Total thoughts for the unfamiliar brands were1p1.65
significantly higher at the second ( , ;Mp1.93 Mp3.06
, ) and third ( ,F(1, 182) p21.7 p!.0001 Mp2.55
; , ) exposures than forMp3.17 F(1,182) p5.8 p!.01
familiar brands. Given that total thoughts indicate more ex-
tensive processing (Sujan 1985), these analyses are consis-
tent with the proposition that ads for unfamiliar brands are
processed more extensively with repetition than are ads for
familiar brands.
Consistent with prior research, we examined subjects’
thoughts more specifically (Anand and Sternthal 1990; Ca-
cioppo and Petty 1979). Support and counterarguments were
negatively correlated ( , ). Support ar-rp.25 p!.0001
guments and negative tactic-related thoughts were not
strongly related in the data ( , ). However,rp.08 p!.02
not unexpectedly, negative tactic-related thoughts showed
some positive correlation with counterarguments ( ,rp.15
An ANOVA of support arguments showed a significant
interaction effect between brand familiarity and ad repetition
( , ). Repetition did not signifi-F(2,182) p6.07 p!.003
cantly affect support arguments for familiar brands
( , ), but when the brand was un-F(1, 138) p1.45 p1.24
familiar, support arguments first increased ( ,Mp.76
; , ) and then decreasedMp1.40 F(1,138) p6.0 p!.01
( ; , ). CounterargumentsMp.64 F(1,138) p8.6 p!.004
also showed an interaction effect between brand familiarity
and ad repetition ( , ). Counterargu-F(2,182) p2.9 p!.05
ments did not show a significant change with repetition for
familiar brands ( , ) but significantly in-F(2,138) !1p1.54
creased with repetition for unfamiliar brands (F(1, 138) p
,).3.3 p!.04
The difference between support and counterarguments
was examined to understand the overall tenor of subjects’
thoughts (Greenwald 1968). This analysis showed only a
significant interaction effect between brand familiarity and
ad repetition ( , ). Follow-up anal-F(2,182) p5.24 p!.006
yses revealed no effect of repetition for familiar brands
( , ), but a significant effect for unfa-F(2, 90) p1.2 p1.3
miliar brands ( , ). For unfamiliarF(2,90) p4.8 p!.01
brands there was a quadratic trend ( ,F(1,45) p5.2 p!
) such that the difference score first increased (.03 Mp
, ; , ) and then signifi-.24 Mp.68 F(1,182) p1.3 p1.25
cantly decreased ( ; , ),Mp.52 F(1,182) p9.8 p!.002
showing that with repetition, counterarguments outnum-
bered support arguments for unfamiliar brands.
Finally, negative tactic-related thoughts were examined.
An ANOVA revealed significant main effects of brand fa-
miliarity ( , ) and ad repetitionF(1,91) p5.86 p!.02
( , ), as well as a significant in-F(2,177) p34.1 p!.0001
teraction effect between brand familiarity and ad repetition
( , ). When the advertised brandF(2,177) p5.05 p!.007
was familiar, negative tactic-related thoughts showed a linear
trend ( , ). When the advertisedF(1,45) p15.25 p!.0003
brand was unfamiliar, negative tactic-related thoughts
showed a linear trend ( , ), qual-F(1, 41) p39.27 p!.0001
ified by a quadratic trend ( , ) causedF(1,41) p5.47 p!.02
by a sharp increase in negative tactic-related thoughts at the
third ad exposure.
These results suggest that repetition of the same ad in-
duces somewhat greater processing when the advertised
brand is unfamiliar than when it is familiar. Repetition of
ads for unfamiliar brands results in a decline in support
arguments but an increase in both counterarguments and
negative tactic-related thoughts. It thus appears that the
greater processing of ads for unfamiliar brands results in
more negative thoughts that then lead to advertising wearout.
In particular, this suggests that a higher repetition of an ad
for an unfamiliar brand results in cognitive capacity that
allows the consumer to consider the (in)appropriateness of
the advertiser’s tactics. We examine this process more di-
rectly in study 2.
Summary and Discussion
Overall, the results of study 1 support our conceptualiza-
tion. Ad repetition in a television news program produced
wearout when the advertised brand was unfamiliar—bothAad
and Ab showed similar patterns in that they first increased
and then decreased with repetition of an ad. For a familiar
brand, wearout did not appear over three repetitions—Aad
showed an increasing linear trend, and Ab showed a direc-
tional increase. When the brand was familiar, neither Aad nor
Ab showed any decrease over the repetition schedule,whereas
both Aad and Ab showed definite decreases when the brand
was unfamiliar. Analysis also demonstrated that Aad has a
greater influence on Ab for unfamiliar than for familiar
The results of study 1 also suggest that consumers’ cog-
nitions while viewing ads may drive the effects of repetition
on advertising effectiveness. An increase in counterarguments
and a decrease in support arguments with ad repetition led
to a decrease in overall ad effectiveness in terms of bothAad
and Ab. Importantly, this also shows that negative tactic-
related thoughts increased with repetition and that these
thoughts increased more rapidly for unfamiliar than for fa-
miliar ads. The largest number of negative tactic-related
thoughts coincided with the wearout seen for the unfamiliar
Study 1 provided basic support for the idea that brand
familiarity moderates the attitudinal effects of repetition.
This also provides some initial exploration of the processing
that gives rise to advertising wearout and to the differential
effects of repetition on processing of ads for familiar and
unfamiliar brands. Study 1 demonstrated that there was a
greater increase in the level of processing with repetition of
an ad for an unfamiliar brand and suggested that, as pro-
posed, the respondents were more likely to think about the
(in)appropriateness of advertising tactics at comparatively
lower levels of repetition with an ad for an unfamiliar as
compared with one for a familiar brand. A second study
was designed to explore in more detail the consumer pro-
cessing evoked with repetition. In particular, this study was
designed to measure specifically consumers’ perceptions of
tactic inappropriateness and to assess the role that perceived
tactic inappropriateness plays in the different wearout pat-
terns for familiar and unfamiliar brands. This second study
also allows replication of the moderating role of brand fa-
miliarity with a different advertising medium, and with dif-
ferent brands, ads, and repetition schedules. Showing the
same important role of brand familiarity under differentcon-
ditions will provide greater confidence in the generalizability
of the results.
Subjects and Design
One hundred and four adult staff members at a private,
eastern university participated in a study in exchange for $10
and a chance for a cash prize. Subjects were randomly as-
signed to a 2 (brand familiarity: familiar or unfamiliar) #4
(ad repetition: 1, 2, 3, or 5 exposures (product: cereal,)#4
laundry detergent, pain reliever, toothpaste) factorial design.
Higher repetition was used in study 2 than in study 1 because
of the different repetition requirements of static (e.g., print)
versus dynamic (e.g., television) advertising (Belch and Belch
2001). Brand familiarity was a between-subject factor, and
ad repetition and product were within-subject factors.
Stimuli and Procedure
All subjects read a cover story about a new service
whereby consumers could get free Internet access by agree-
ing to view a set of ads prior to accessing the Internet.Each
participant individually started a computer-controlled pro-
gram that displayed a series of ads on a personal computer
screen. The program began with a filler ad and then showed
the test ads and another filler ad at different levels of rep-
etition, ending with a repeat of the first filler ad and a new
filler ad. Thus, subjects saw three filler ads, one of which
was repeated once, and four test ads, with each test ad
appearing at a different level of repetition. The first test ad
to appear was seen five times during the course of the pro-
gram, the second was seen three times, the third was seen
twice, and the fourth was seen once. All ads had at least
two other ads in between any repetition of the ad, and ads
were rotated and counterbalanced for order and repetition
levels such that each ad appeared in each position and at
each repetition level for different subjects. Each test ad was
displayed for 13 seconds (a pretest revealed that this was
long enough for subjects to read the entire ad without feeling
rushed). All ads were created by a professional designer to
include a relevant, high-quality graphic (e.g., a photo of a
couple at a breakfast table with a bowl of cereal, newspaper,
etc., for the cereal ad), a headline, and copy that stressed
product benefits (e.g., nutrition and taste for the cereal ad).
Dependent measures
Level of repetition
Familiar Unfamiliar
Attitude toward the ad 4.70
(1.69) 4.74
(1.31) 5.07
(1.44) 4.61
(1.37) 4.83
(1.47) 4.95
(1.47) 5.07
(1.41) 4.16
Attitude toward the brand 5.62
(1.48) 5.29
(1.54) 5.39
(1.40) 5.52
(1.37) 5.13
(1.28) 5.01
(1.28) 5.05
(1.28) 4.34
Total thoughts 2.41
(1.49) 2.49
(1.14) 2.88
(1.42) 2.71
(1.27) 2.04
(1.34) 2.45
(1.17) 2.36
(1.40) 3.12
Negative tactic-related
thoughts .14
(.40) .31
(.55) .29
(.50) .76
(.81) .08
(.34) .12
(.45) .27
(.77) 1.18
Tactic inappropriateness 3.53
(1.95) 3.20
(1.66) 3.35
(1.73) 3.42
(1.79) 2.80
(1.37) 2.55
(1.24) 2.99
(1.45) 3.87
Two versions of each ad were created with either a familiar
or a fictitious brand name (names were pretested to verify
that the familiar brands were well known and that the fic-
titious brands were not).
After the ads ended, subjects completed a questionnaire,
beginning with several filler questions about the Internet ser-
vice. Next, they completed thought protocols of what they
thought and felt the last time that they viewed each ad. Sub-
jects completed the same measures of Ab (Cronbach’s
) and Aad (Cronbach’s ) used inalpha p.95 alpha p.95
study 1. Next, subjects were asked to indicate perceived tactic
inappropriateness on two seven-point agree–disagree scales:
(1) “I thought that the way BRAND tried to persuade people
seemed acceptable,” and (2) “I felt that this advertising for
BRAND was fair in what was said and shown” ( ,rp.61
). The second measure was similar to the negativep!.0001
tactic-related thought measure used by Shiv et al. (1997).
Higher numbers reflect greater perceived tactic inappropri-
ateness. After completing these measures for all test ads, sub-
jects indicated prior brand familiarity, product category in-
volvement, gender, age, and education level.
A full model with the experimental factors, product cate-
gory, involvement, and ad order was analyzed. The lack of
significant interactions between experimental factors and the
other variables indicated that the data could be pooled across
these variables. Unless otherwise stated, the following anal-
yses were conducted with a 2 (brand familiarity (rep-)#4
etition) ANOVA. Table 2 contains cell means.
Manipulation Checks. Analysis of prior brand famil-
iarity revealed a significant main effect of brand type on
prior brand familiarity ( , ) andF(1, 102) p1500.6 p!.0001
no other significant effects. Prior familiarity was higher for
familiar brands than for unfamiliar brands ( ,Mp5.82
). Analysis of subjects’ self-report of how manyMp1.09
times they remembered seeing each ad showed a significant
main effect of ad repetition ( , )F(3,303) p254.1 p!.0001
and no other significant effects. As in study 1, subjects
demonstrated good memory for the number of times they
viewed an ad ( , , ,Mp1.41 Mp2.24 Mp2.85 Mp
Attitude Effects. An ANOVA was used to examinethe
effects of brand familiarity and ad repetition on Aad and
Ab. Analysis of Aad showed a significant main effect of ad
repetition ( , ) and no other signif-
F(3,295) p5.01 p!.002
icant effects. We next conducted a series ofplanned contrasts
and trend analyses, as recommended by Rosenthal, Rosnow,
and Rubin (2000), among others, to test for planned dif-
ferences. For familiar brands, examination of Aad revealed
no effect of ad repetition (exposure 1 was contrasted with
exposure 2, and exposure 2 was contrasted with exposure
3, ; contrasts of exposure 3 to exposure 5 showed a
marginal decrease, ; linear and
F(1,295) p3.14, p!.08
quadratic trends: ). For unfamiliar brands, there
F(1,46) !1
was a significant quadratic trend ( , )
F(1,50) p7.1 p!.01
for Aad. This trend was driven by a sharp decrease in Aad
from three ( ) to five exposures ( ;
Mp5.05 Mp4.16
F(1,295) p12.63 p!.0004
An analysis of Ab showed main effects of brand familiarity
( , ) and of ad repetition
F(1,102) p7.83 p!.006
( , ), and it indicated a significant in-
F(3,299) p2.8 p!.05
teraction effect ( , ). Follow-up anal-F(3,299) p3.7 p!.01
ysis showed no significant effect of repetition on Ab for fa-
miliar brands (contrast ). For unfamiliar brands, AbF’s!1.1
showed a significant linear trend ( , )F(1,50) p9.4 p!.001
and a quadratic trend that approached significance
( , ). Importantly, Ab significantly de-F(1, 50) p2.5 p!.11
creased from three ( ) to five ( ) exposuresMp5.05 Mp4.34
for unfamiliar ( , ), but not for fa-F(1,299) p10.14 p!.002
miliar ( ), brands. Both of these analyses provide someF!1
support for a differential effect of repetition as a function of
the familiarity of the sponsoring brand. There was no evidence
of wearout for familiar brands, either in terms of Aad or Ab,
but there were decreases in both Aad and Ab after three
exposures for unfamiliar brands.
Regression analysis was conducted to examine whether
the influence of Aad on Ab depended on prior brand fa-
miliarity. Regression of Aad, brand familiarity, and their
interaction on Ab replicated the results found in study 1.
All three variables were significant ( , ,ßp.44 tp7.7
;,,;p!.0001 ß p1.26 tp3.28 p!.001 ß p
, , ). Importantly, the significant.16 tp2.01 p!.05
interaction revealed that Aad had a significantly greater in-
fluence on Ab when the brand was unfamiliar than when it
was familiar.
Processing Effects. Thoughts were coded and analyzed
to explore the process underlying the different wearout ef-
fects observed for unfamiliar and familiar brands. The total
number of thoughts was analyzed to provide insight as to
whether consumers processed ads for unfamiliar brands
more than for familiar brands. The total number of thoughts
reported by subjects showed a significant main effect of
repetition ( , ), qualified by a sig-F(3,300) p6.72 p!.0002
nificant interaction effect ( , ). TotalF(3,300) p3.54 p!.02
thoughts showed a significant linear increase for both fa-
miliar brands ( , ) as well as unfa-F(1,55) p5.38 p!.02
miliar brands ( , ). For unfamiliarF(1,55) p28.15 p!.0001
brands, however, this was qualified by a significant cubic
trend ( , ), with a large increase inF(1,55) p5.72 p!.02
total thoughts from the third ( ) to the fifth ex-Mp2.35
posure ( ; , ). BecauseMp3.12 F(1,300) p11.94 p!.0006
of this sharp increase, there were more thoughts at the fifth
exposure when the brand was unfamiliar than when it was
familiar ( , ; ,Mp3.12 Mp2.71 F(1,300) p3.5 p!
). It is possible that the main effect of repetition merely.06
reflects that ads’ thoughts are better recalled with more ad
repetition. The interaction results, by contrast, are suggestive
of greater processing with repetition of ads for unfamiliar
relative to familiar brands.
Negative tactic-related thoughts were coded as described
in study 1. In addition, as described above, perceived tactic
inappropriateness was explicitly measured. Consistent with
expectations, the perceived tactic inappropriateness scalewas
significantly correlated with the negative tactic-related
thoughts coded from the open-ended protocols ( ,rp.20
). Given this positive correlation and the conceptualp!.0001
connection between the two, MANOVA was utilized to ex-
amine the effects of repetition and brand familiarity. This
revealed main effects of repetition (Wilks’s ;lambda p.66
, ) and familiarity (Wilks’sF(6,582) p22.79 p!.0001
; , ) and an interac-lambda p.97 F(2,291) p3.85 pp.02
tion effect (Wilks’s ; ,lambda p.93 F(6, 582) p3.81 pp
). The ANOVA results of subjects’ coded negative tactic-.001
related thoughts revealed a main effect of ad repetition
( , ), as well as an interaction ef-F(3,292) p47.48 p!.0001
fect ( , ). While tactic-relatedF(3,292) p5.22 p!.001
thoughts increased with repetition for both familiar and un-
familiar brands, there was a larger increase for unfamiliar
brands. Although tactic-related thoughts were the same for
unfamiliar and familiar brands at the first exposure to the ad
( ), they were significantly higher at the fifth exposureF!1
to the ad for an unfamiliar than for a familiar brand
(;,).Mp1.18, Mp.76 F(1,292) p12.90 p!.0004
There was a significant linear ( , )F(1,55) p63.65 p!.0001
and quadratic ( , ) trend in negativeF(1,55) p15.91 p!.0002
tactic-related thoughts for unfamiliar brands.
Similarly, an ANOVA of perceived tactic inappropri-
ateness revealed a significant main effect of repetition
4.91, ) and a significant interaction ef-(F(3, 292) pp!.002
fect ( , ). There was no effect of rep-F(3,292) p3.31 p!.02
etition on perceived tactic inappropriateness for familiar
brands ( ). For an unfamiliar brand, perceived tacticF!1
inappropriateness significantly increased with repetition of
an ad ( , ). There was a linearF(3, 220) p6.74 p!.0002
( , ) and a cubic trend (F(1,52) p8.76 p!.005 F(1, 52) p
, ) for unfamiliar brands with a sharp increase16.70 p!.0002
in perceived tactic inappropriateness between three and five
Mediation. Analysis showed significant experimental
effects on Aad and Ab. Likewise, significant effects were
revealed for total thoughts, negative tactic-related thoughts,
and perceived tactic inappropriateness. These analyses fulfill
the first two steps for potential mediation of the experimental
effects on attitudes by these variables (Baron and Kenny
1986). Thus, the last step examining potential mediation by
these variables of the effects of brand familiarity and rep-
etition on attitudes was conducted by including each of them
separately as a covariate in the standard ANOVA modelfor
Aad and Ab.
Total thoughts did not appear to mediate the experimental
effects. Total thoughts did not achieve significance as a co-
variate in the analysis of either Aad or Ab, suggesting that
it is not the amount of thought itself that is driving the
different effects of repetition for familiar and unfamiliar
Negative tactic-related thoughts were also examined for
mediation of the effects of ad repetition and brand famil-
iarity. Tactic-related thoughts was a marginally significant
covariate for Aad ( , ) and reducedF(1,288) p2.51 p!.11
the effect of repetition on Aad (from ,F(3, 295) p5.01
to , ). Tactic-relatedp!.002 F(3,288) p2.37 p!.07
thoughts was a significant covariate for Ab (F(1,292) p
, ), eliminated the significant effect of repetition4.74 p!.03
on Ab ( ), and significantly reducedF(3,292) p.65, p1.58
the interaction effect ( , ) but not theF(3,292) p2.23 p!.09
effect of brand familiarity on Ab ( ,F(1,100) p8.37 p!
). This suggests that negative tactic-related thoughts par-.005
tially mediate the differing wearout effects for familiar ver-
sus unfamiliar brands.
Finally, perceived tactic inappropriateness was examined
as a potential mediator. Perceivedtactic inappropriateness was
a significant covariate for Aad ( ,F(1,293) p62.7 p!
) and reduced the effect of repetition on Aad (from.0001 ,to ,).F(3,295) p5.01 p!.002 F(3, 293) p3.03 p!.03
Perceived tactic inappropriateness was also a significant co-
variate for Ab ( , ) and eliminatedF(1,295) p20.58 p!.0001
the significant effect of repetition on Ab ( ,F(3,295) p2.1
) and the interaction effect ( ,p1.1 F(3,295) p2.48 p!
These analyses demonstrate that negative tactic-related
thoughts and perceived tactic inappropriateness provide
some mediation of the effect of ad repetition on Aad and
mediate the effects of repetition and the interaction of brand
familiarity and ad repetition on Aad and Ab. Combined,
these results support the notion that thoughts about the in-
appropriateness of advertising tactics are one important type
of the consumer thoughts that underlie ad wearout.
Summary and Discussion
Study 2 replicates the findings from study 1 that ads for
unfamiliar brands can wearout more quickly than ads for
familiar brands. As with study 1, study 2 also provides
results that suggest that processing of the ad is different
when the brand is unfamiliar versus when it is familiar.
Additionally, study 2 suggests that the greater processing
accorded during ad repetition for an unfamiliar brand may
give rise to consideration of the appropriateness of adver-
tisers’ tactics.
Two experiments were conducted in which ad content
and repetition were carefully controlled and only the fa-
miliarity of the brand sponsor was varied. These provide
consistent evidence that ads for unfamiliar brands wear out
faster, showing decreased effectiveness at lower levels of
repetition relative to ads for familiar brands. The results also
provide insight to the consumer psychology underlying the
effect of brand familiarity on ad wearout.
Across both studies, processing of the ads was seen to
differ with repetition depending on the familiarity of the
brands. Ads for unfamiliar brands were processed more ex-
tensively with repetition than were ads for familiar brands.
Just as a marketer’s focus is often on building market knowl-
edge for new brands and on maintaining presence for fa-
miliar brands, consumer focus may be on learning about
unfamiliar brands but also on updating existing knowledge
for familiar brands. Increases in processing because of rep-
etition and brand unfamiliarity lead to more negative and
fewer positive thoughts. Additionally, the studies provide
evidence to suggest that at higher levels of ad repetition,
consumers may use more extensive processing to consider
the inappropriateness of advertising tactics for unfamiliar
brands. Tactic inappropriateness was seen to mediate the
effects of ad repetition and brand familiarity on message
effectiveness. Finally, the results demonstrated that attitude
toward the ad had a greater influence on attitude toward the
brand for unfamiliar brands compared with familiar brands.
A third study was conducted that provides an additional replication of
both the moderating effect of brand familiarity on advertising repetition
effects and the mediating role of perceived tactic inappropriateness.
This research has important implications for both aca-
demic and practitioner research. This contributes to the ex-
isting research on advertising repetition by both identifying
brand familiarity as an important moderator of repetition
effects and providing insight on thoughts about tactic in-
appropriateness as one possible mediator of these effects.
This provides replication of the curvilinear relationship be-
tween ad repetition and attitudes found earlier (e.g., Ca-
cioppo and Petty 1979; Calder and Sternthal 1980) and
builds on the existing research by providing a more nuanced
view of when and how negative effects of repetition are
likely to occur. In particular, this addsto the existing research
on the processing underlying repetition effects (e.g., Anand
and Sternthal 1990) by providing a greater understanding
of the processing that consumers do with repeated exposures
to a message.
The findings reported here on the important moderating
role of brand familiarity have general implications for re-
search. It is common for researchers to use fictitious brands
to provide greater experimental control. The use of fictitious
brands should be carefully reviewed for any project in terms
of the likelihood that the use of familiar versus unfamiliar
brands could change the conclusions that are drawn. Care
must be taken such that research with fictitious brands does
not provide incomplete or incorrect insights to how con-
sumers respond to “real,” familiar brands (Smith 1993;
Stewart 1992).
The research reported here sheds some light on issues
surrounding brand equity. One oft-cited benefit of creating
a strong brand is to increase communication effectiveness
(Aaker 1991; Keller 1998). However, we are unaware of
research that has carefully examined whether strong brands
beneficially affect communication effectiveness. Brand fa-
miliarity is an important component of brand equity (Aaker
1991; Jacobson and Lane 1995; Keller 1998); thus, these
research findings provide some empirical support for the
beneficial effect of brand equity on communications. The
study findings can be interpreted as showing that high-equity
brands (i.e., familiar brands) were able to maintain positive
attitudinal responses over higher levels of repetition than
were unfamiliar brands with little brand equity. Postponing
the onset of advertising wearout may be one way in which
strong brands increase communications effectiveness.
The study findings also have implications for unfamiliar
brands. Marketers of unfamiliar brands need to build fa-
miliarity to compete better with more familiar brands, but
they must be careful in how they use concentrated, high-
repetition ad schedules in order to avoid alienating consum-
ers. Memory cannot be built at the expense of attitudes.
Memory results from study 1 showed a main effect of brand familiarity
on uncued brand recall such that familiar brands were better recalled than
were unfamiliar brands ( , ; ,Mp.65 Mp.29 F(1,89) p35.6 p!
). While repetition also had a main effect such that recall improved.0001
with repetition ( , ), there was no interaction ef-F(2,176) p28.5 p!.0001
fect. That is, memory for unfamiliar brands never “caught up” with memory
for familiar brands.
Rather than simply employing a high-frequency ad schedule,
care should be taken to keep consumers engaged by match-
ing the processing required to the processing available, per-
haps by showing a variety of messages or increasing mes-
sage complexity and content for processing to avoid
advertising wearout. Unfamiliar brands may have to work
harder to build positive attitudes concurrent with brand
Limitations and Future Research
It is interesting to note that the different rate of wearout
for unfamiliar versus familiar brands occurred under two
different types of repetition. In study 1, the ads were em-
bedded in television programming, and repetition was
spaced within the programming. In study 2, repetition fol-
lowed a more concentrated schedule. Ads were all shown
together, as at the beginning of many magazines, and rep-
etition was massed, separated only by other ads, not by
content. Brand familiarity was seen to influence repetition
effects in both of these cases.
However, it should be noted that even the spaced repe-
tition in study 1 showed more repetition within a half-hour
time period than consumers typically see. Although some
research suggests that massed and spaced repetition sched-
ules show the same patterns of effects (cf. Pechmann and
Stewart 1989), it is possible that the fairly concentrated
repetition used in our experimental settings influenced the
results. Although the repetition schedules to which consum-
ers are typically exposed involve much higher levels of
repetition than were used here, the repetition is also usually
more spread out. Future research could strive to replicate
these results in more naturalistic settings to examine the
possibility that these results were influenced by the exper-
imental settings themselves, that is, potentially greater pro-
cessing involvement and more concentrated repetition. Like-
wise, future research should examine the effects of different
types of communication schedules on consumer access of
tactic-related thoughts. For example, do more concentrated
schedules increase the consideration of tactic inappropriate-
ness? How does the use of multiple media influence access
of such tactic-related thoughts? Is the consumer who is ex-
posed to two different but integrated communication vehi-
cles, such as an ad for a brand and then a coupon containing
the same graphic, more or less likely to consider the ad-
vertiser’s tactics?
There are also methodological limitations to the research.
First, the thought protocols were taken prior to other mea-
sures in all experiments. This was done in order to keep the
measures themselves from contaminating the thoughts listed
by subjects. Whereas the measure order cannot account for
the differential effects of repetition by brand familiarity, it
is possible that subjects thought more about the ads than
they would have if we had not asked them to list their
thoughts. If this were the case, these additional thoughts
could have influenced the results seen here. Second, the
measure of perceived inappropriateness, while drawing from
earlier work (Shiv et al. 1997), is a fairly new and untested
measure. Further examinations of possible order effects and
of measures of perceived tactic inappropriateness are de-
serving of future research.
Other brand knowledge structures should be explored for
their effects on advertising wearout. Because brands in this
study were both familiar and somewhat positively evaluated
by consumers, it remains for future research to examine the
separate effects of familiarity and favorability of brand as-
sociations. While most established brands are somewhat
positively evaluated, there may be brands that are negatively
evaluated by a fair number of consumers but liked strongly
enough by others so that they are still able to succeed in
the marketplace (e.g., niche brands such as Spam). Brand
familiarity may play a more important role in whether con-
sumers are able successfully to expend processing effort as
a result of an ad designed to elicit greater processing. Brand
favorability, by contrast, may play a more important role in
whether consumers are willing to expend such effort, as
well as the nature of their reactions to the ad and ad tactics.
Additionally, as noted above, an interesting and important
avenue for future research is to explore how best to build
knowledge for an unfamiliar brand while maximally in-
creasing message effectiveness. Finally, this research sug-
gests a positive role of brand familiarity in communication
effectiveness. Research should continue to explore whether,
in the words of Shakespeare, “familiarity breeds contempt”
or, rather, as suggested here, there are conditions under
which familiarity breeds contentment.
[David Glen Mick served as editor and Wayne D. Hoyer
served as associate editor for this article]
Aaker, David A. (1991), Managing Brand Equity, New York: Free
Alba, Joseph W. and J. Wesley Hutchinson (1987), “Dimensions
of Consumer Expertise,” Journal of Consumer Research, 13
(March), 411–454.
Anand, Punam and Brian Sternthal (1990), “Ease of Message Pro-
cessing as a Moderator of Repetition Effects in Advertising,”
Journal of Marketing Research, 27 (August), 345–353.
Baron, Reuben M. and David A. Kenny (1986), “The Moderator-
Mediator Variable Distinction in Social Psychological Re-
search: Conceptual, Strategic and Statistical Considerations,”
Journal of Personality and Social Psychology, 51 (6),
Batra, Rajiv and Michael L. Ray (1986), “Situational Effects of
Advertising Repetition: The Moderating Influence of Moti-
vation, Ability and Opportunity to Respond,” Journal of Con-
sumer Research, 12 (March), 432–445.
Belch, George E. (1982), “The Effects of Television Commercial
Repetition on Cognitive Response and Message Acceptance,”
Journal of Consumer Research, 9 (June), 56–65.
Belch, George E. and Michael A. Belch (2001), Advertising and
Promotion: An Integrated Marketing Communications Per-
spective, 5th ed., New York: McGraw-Hill.
Berlyne, Donald E. (1970), “Novelty, Complexity, and Hedonic
Value,” Perception and Psychophysics, 8, 279–286.
Blair, Margaret Henderson and Michael J. Rabuck (1998), “Ad-
vertising Wearin and Wearout: Ten Years Later—More Em-
pirical Evidence and Successful Practice,” Journal of Adver-
tising Research (September–October), 7–18.
Britton, Bruce K. and Abraham Tesser (1982), “Effects of Prior
Knowledge on Use of Cognitive Capacity in Three Complex
Cognitive Tasks,” Journal of Verbal Learning and Verbal
Behavior, 21 (4), 421–436.
Cacioppo, John T. and Richard E. Petty (1979), “Effectsof Message
Repetition and Position on Cognitive Response, Recall and
Persuasion,” Journal of Personality and Social Psychology,
37 (1), 97–109.
Calder, Bobby J. and Brian Sternthal (1980), “Television Com-
mercial Wearout: An Information Processing View,” Journal
of Marketing Research, 17 (May), 173–186.
Campbell, Margaret C. (1995), “When Attention-Getting Adver-
tising Tactics Elicit Consumer Inference of Manipulative In-
tent: The Importance of Balancing Benefits and Investments,”
Journal of Consumer Psychology, 4 (3), 225–254.
——— (1999), “Perceptions of Price Unfairness: Antecedents and
Consequences,” Journal of Marketing Research, 36 (May),
Campbell, Margaret C. and Amna Kirmani (2000), “Consumers’
Use of Persuasion Knowledge: The Effects of Accessibility
and Cognitive Capacity on Perceptions of an Influence
Agent,” Journal of Consumer Research, 27 (June), 69–83.
Cox, Dena S. and Anthony D. Cox (1988), “What Does Familiarity
Breed? Complexity as a Moderator of Repetition Effects in
Ad Evaluation,” Journal of Consumer Research, 15 (June),
Edell, Julie A. and Marian C. Burke (1986), “The Relative Impact
of Prior Brand Attitude and Attitude toward the Ad on Brand
Attitude after Ad Exposure,” in Advertising and Consumer
Psychology, Vol. 3, ed. Jerry Olson and Keith Sentis, New
York: Praeger, 93–107.
Friestad, Marian and Peter L. Wright (1994), “The Persuasion
Knowledge Model: How People Cope with Persuasion At-
tempts,” Journal of Consumer Research, 21 (June), 1–31.
Greenwald, Anthony G. (1968), “Cognitive Learning, Cognitive
Response to Persuasion, and Attitude Change,” in Psycho-
logical Foundations of Attitudes, ed. Anthony G. Greenwald
et al., New York: Academic Press, 147–170.
Hilton, James L. and John M. Darley (1991), “The Effects of
Interaction Goals on Person Perception,” in Advances in Ex-
perimental Social Psychology, Vol. 24, ed. Mark P. Zanna,
New York: Academic Press, 236–267.
Jacobson, Robert and Vicki Lane (1995), “StockMarket Reactions
to Brand Extension Announcements: The Effects of Brand
Attitude and Familiarity,” Journal of Marketing, 59 (January),
Kardes, Frank R. (1994), “Consumer Judgment and Decision Pro-
cesses,” in Handbook of Social Cognition, Vol. 2, ed. Robert
S. Wyer, Jr. and Thomas K. Srull, Hillsdale, NJ: Erlbaum,
Keller, Kevin Lane (1991), “Cue Compatibility and Framing in
Advertising,” Journal of Marketing Research, 28 (February),
——— (1998), Strategic Brand Management, Upper Saddle River,
NJ: Prentice-Hall.
Kent, Robert J. and Chris T. Allen (1994), “Competitive Interfer-
ence Effects in Consumer Memory for Advertising: The Role
of Brand Familiarity,” Journal of Marketing, 58 (July),
Kirmani, Amna and Peter Wright (1989), “Money Talks: Perceived
Advertising Expense and Expected Product Quality,” Journal
of Consumer Research, 16 (December), 344–353.
Krugman, Herbert E. (1972), “Why Three Exposures May Be
Enough,” Journal of Advertising Research, 12 (6), 11–14.
Lodish, Leonard M., Magid Abraham, Stuart Kalmenson, Jeanne
Livelsberger, Beth Lubetkin, Bruce Richardson, and Mary
Ellen Stevens (1995), “How T.V. Advertising Works: AMeta-
Analysis of 389 Real World Split Cable T.V. Advertising Ex-
periments,” Journal of Marketing Research, 32 (May),
Machleit, Karen A., Chris T. Allen, and Thomas J. Madden (1993),
“The Mature Brand and Brand Interest: An Alternative Con-
sequence of Ad-Evoked Affect,” Journal of Marketing, 57
(October), 72–82.
Machleit, Karen A. and Robert D. Wilson (1988), “EmotionalFeel-
ings and Attitude toward the Ad: The Roles of Brand Fa-
miliarity and Repetition,” Journal of Advertising, 17 (3),
MacKenzie, Scott B. and Richard A. Spreng (1992), “How Does
Motivation Moderate the Impact of Central and Peripheral
Processing on Brand Attitudes and Intentions?” Journal of
Consumer Research, 18 (March), 519–529.
Messmer, Donald J. (1979), “Repetition and Attitudinal Discrep-
ancy Effects on the Affective Response to Television Adver-
tising,” Journal of Business Research, 7 (1), 75–93.
Mitchell, Andrew A. and Jerry C. Olson (1977), “Cognitive Effects
of Advertising Repetition,” in Advances in Consumer Re-
search, Vol. 4, ed. William D. Perreault, Jr., Atlanta: Asso-
ciation for Consumer Research, 213–220.
Pechmann, Cornelia and David W. Stewart (1989), “Advertising
Repetition: A Critical Review of Wearin and Wearout,” Cur-
rent Issues and Research in Advertising, 11 (1–2), 285–330.
——— (1990), “The Effects of Comparative Advertising on At-
tention, Memory, and Purchase Intentions, Journal of Con-
sumer Research, 17 (September), 180–191.
Ray, Michael L. and Alan G. Sawyer (1971), “Repetition inMedia
Models: A Laboratory Technique,” Journal of Marketing Re-
search, 8 (February), 20–29.
Rethans Arno J., John L. Swasy, and Lawrence J. Marks (1986),
“Effects of Television Commercial Repetition, Receiver
Knowledge, and Commercial Length: A Test of the Two-
Factor Model,” Journal of Marketing Research, 23 (Febru-
ary), 50–56.
Rosenthal, Robert, Ralph L. Rosnow, and Donald B. Rubin (2000),
Contrasts and Effect Sizes in Behavioral Research: A Cor-
relational Approach, New York: Cambridge University Press.
Sagarin, Brad J., Robert B. Cialdini, William E. Rice, and Sherman
B. Serna (2002), “Dispelling the Illusion of Invulnerability:
The Motivations and Mechanisms of Resistance to Persua-
sion,” Journal of Personality and Social Psychology, 83 (3),
Shiv, Baba, Julie A. Edell, and John W. Payne (1997), “Factors
Affecting the Impact of Negatively and Positively Framed Ad
Messages,” Journal of Consumer Research, 24 (December),
Smith, Robert E. (1993), “Integrating Information from Advertis-
ing and Trial: Processes and Effects on Consumer Response
to Product Information,” Journal of Marketing Research, 30
(May), 204–219.
Snyder, Mark and Arthur A. Stukas, Jr. (1999), “Interpersonal Pro-
cesses: The Interplay of Cognitive, Motivational, and Behav-
ioral Activities in Social Interaction,” Annual Review of Psy-
chology, 50, 273–303.
Stewart, David W. (1992), “Speculations on the Future of Adver-
tising Research,” Journal of Advertising, 21 (September),
Stewart, David W. and David H. Furse (1986), Effective Television
Advertising: A Study of 1,000 Commercials, Lexington, MA:
Sujan, Mita (1985), “Consumer Knowledge: Effects on Evaluation
Strategies Mediating Consumer Judgments,” Journal of Con-
sumer Research, 12 (June), 16–31.
Vakratsas, Demetrios and Tim Ambler (1999), “How Advertising
Works: What Do We Really Know?” Journal of Marketing,
63 (January), 26–43.
Wright, Peter (1973), “The Cognitive Processes Mediating Accep-
tance of Advertising,” Journal of Marketing Research, 10
(February), 53–62.
... Still, the repeat exposure strategy has no significant impact on the purchasing behaviour of women consumers. These results (Kaur and Hundal, 2017;Campbell and Keller, 2003;Khan and Munoz, 2015;Majeed and Rezzak, 2011;Liu and Liu, 2019;Trivedi and Teichert, 2020;Öztürk and Tekin, 2020;Dokeroğlu and Gökçearslan, 2020;Meraabi and Selvasundaram, 2020) support works in the literature. ...
... Mizah kullanımı ürünün daha eğlenceli olduğu izlenimi uyandırarak kadın tüketicilerin duygularını harekete geçirmekte ve ürünün satın alınmasını artırmaktadır.Mevcut çalışmadan elde edilen bulgulara göre; reklamlarda ünlü kullanımı, ürün kıyaslama, cinsel çekicilik ve mizah kullanımı stratejilerinin, tüketicilerin satın alma davranışları üzerinde anlamlı ve pozitif bir etkiye sahip olduğu ancak, tekrara maruz kalma stratejisinin kadın tüketicilerin satın alma davranışları üzerinde anlamlı bir etkisi olmadığı belirlenmiştir. Bu sonuçlar(Kaur ve Hundal, 2017;Campbell ve Keller, 2003;Khan ve Munoz, 2015; Majeed ve Rezzak, 2011;Liu ve Liu, 2019; Trivedi ve Teichert, 2020;Öztürk ve Tekin, 2020;Dökeroğlu ve Gökçearslan, 2020; Meraabi ve Selvasundaram, 2020) literatürdeki çalışmaları destekler niteliktedir. ...
Full-text available
Kadın tüketicilerin gün geçtikçe daha bilgili ve finansal açıdan bağımsız hale gelmeleri işletmelerin pazarlama ve reklam stratejileri için önemli bir hedef kitle olmalarına da neden olmaktadır. Reklamların sürekli tekrar etmesi, markaların kendilerini bir ünlüyle özdeşleştirmesi, rakip ürünlerle reklamı yapılan ürünün mukayese edilerek tüketicinin etkilenmeye çalışılması, cinsel çekicilik unsurlarının reklamlarda kullanılması ya da çeşitli mizahi unsurların reklamlara dahil edilerek kadın tüketicilerin satın alma davranışlarına yönlendirilmesi ve tüm bu yöntemlerin etkili olup olmadığının araştırılması hem reklam verenler hem de tüketicilerin satın alma davranışlarının incelenmesi için önem arz etmektedir. Bu çalışma, reklamlarda kullanılan stratejilerin (tekrara maruz kalma, ünlü kullanımı, ürün kıyaslama, cinsel çekicilik, mizah kullanımı) kadın tüketicilerin satın alma davranışları üzerindeki etkisini ortaya çıkarmak amacıyla yapılmıştır. Bu bağlamda veri, kolayda örnekleme yoluyla seçilen 399 kadın tüketiciden nicel araştırma yöntemlerinden biri olan çevrimiçi anket yöntemiyle toplanmıştır ve veriler Yapısal Eşitlik Modeli ile analiz edilmiştir. Analiz sonuçlarında ünlü kullanımı, ürün kıyaslama, cinsel çekicilik, mizah kullanımı stratejilerinin kadın tüketicilerin satın alma davranışları üzerinde etkili olduğu ancak tekrara maruz kalma stratejisinin kadın tüketicilerin satın alma davranışını etkilemediği belirlenmiştir.
... To the researchers' knowledge, most research on repeated exposure tested the effects on recall and attitudes (e.g. Cacioppo & Petty, 1979;Campbell & Keller, 2003). While recall and attitudes are important for brands to know, they do not explain the customerbrand relationship developed by fashion films. ...
... Third, as previously mentioned, most research on repeated exposure has tested consumer attitudes and ad recall (Bornstein, 1989;Cacioppo & Petty, 1979;Campbell & Keller, 2003;Schmidt & Eisend, 2015). The current study evaluated character empathy and brand anthropomorphism, which are rarely tested in the field. ...
... Familiarity captures the direct and the indirect experience with a brand within a consumer's memory. The more the consumer interacts with the online retailer, the more it is familiar to him (Campbell and Keller, 2003). H2b (ß=0.053; ...
Conference Paper
Full-text available
In this paper, we study how the interaction with consumers on social media impacts impulse buying using the data of 396 questionnaires. The results confirm that the e-tailer's reputation, familiarity, and the relevance of his social media communication positively impact trust and impulse buying. We have also found that social distance moderates the effect of the e-tailer’s reputation and the perceived relevance of the e-tailer's social media communication on impulse buying. Knowing how social media communication influences impulse buying enables companies to strengthen synergy between social media presence and the online store.
... Likewise, it has been found that there are negative and positive emotions which impact consumer in an unexpected way (Najmi et al., 2012). It has been noticed that brand familiarity directs the impact of Attitude toward advertisement on Attitude toward the brand, subsequently, consumers familiar with the brand will rely more on their current information about the brand than on Attitude toward advertisement informing their Attitude toward brand (Campbell & Keller, 2003). Buying intentions are used to pretest advertisement and it evaluates proposed promotions for both new and existing products (Morwitz et al., 2007). ...
Full-text available
Spokes character requirement has developed its growth in popularity because spoke characters are not likely to embarrass their sponsors with unacceptable off stage conduct in a manner which contrarily influencing the negative picture of the sponsor brand. Nowadays advertiser has more prominent control over the development of spokes-characters by giving them characteristics that are both powerful and harmonious and with the alluring qualities of the endorsed product. The main purpose of this research is to look at consumer view regarding spokes-characters in the area of advertisement and, how consumer views impact the use of spokes-characters to create a perception of advertisements and brands that ultimately influences their Buying intention. The meta-analysis concluded that appeal and skill of the spokes-character has substantive influence on attitude of the consumer toward the advertisements. The second finding was that the spoke-characters play a crucial role in trust-building towards the brand. Thus, both attitude toward advertisements and attitude toward brand positively influence buying intention.
... However, the relationship between ad repetition and an audience's reception of the ad is not monotonic. Ad effectiveness is believed to increase at low levels of repetition and then decrease as ad repetition increases (Berlyne 1970;Campbell and Keller 2003). Therefore, it is necessary to limit the maximum exposure times of ads to avoid adverse consequences caused by excessive exposure. ...
Full-text available
Bus exterior advertising plays a significant role in outdoor advertising, since it provides frequent exposure to a large number of residents. Traditional route selection methods are generally based on a rough estimation, for example, the number of total passengers of a bus route or the geographical features along the bus route. Targeted bus exterior advertising remains a challenge as little is known about the characteristics of the people along the bus route. In this study, we are aiming at determining a set of bus routes for a given ad category to maximize advertising effectiveness, by mining multiple data sources, including mobile phone data, bus GPS data, smart card data (SCD), and land use data. Specifically, we first estimated the distribution of potential target audiences using mobile phone data and land use data. Two optimization models are proposed considering different advertising requirements. For well-established brands that audiences are familiar with, a wide coverage-oriented bus route selection model is proposed to maximize the coverage of potential target audiences. For new brands that require a high level of exposure before they become recognizable, a deep coverage-oriented bus route selection model is proposed to maximize the total exposure times of the ads. Both models were demonstrated with a case study in Shenzhen, China to explicitly present the outcomes of the models and the differences between them. The calculation results show that the wide coverage-oriented model achieves an average of 84.8% improvement compared with baseline 1 which selects the bus routes with the most passengers, while an average of 9.2% improvement compared with baseline 2 which selects the bus route with the maximum coverage of the target area in reaching more potential target audiences. The exposure intensity of the deep coverage-oriented model is almost 3.7 times of the wide coverage-oriented model. The proposed models provide new options for advertisers to select a suitable advertising strategy according to their needs.
Background Policies that mandate list price disclosure in direct-to-consumer pharmaceutical advertising (DTCPA) cite price transparency among the benefits. The expectation is that price transparency will lead to changes in consumer behavior that will ultimately lower healthcare costs. Objective The objective of this study was to assess the impact of price transparency on perceived level of information and consumer behaviors, specifically intentions to seek treatment and intentions to comparison shop. Methods A nine-arm randomized experiment was conducted to expose respondents to television advertisements for prescription drugs that varied by price disclosure type (no price/control, list price only, or price plus, which disclosed the list price and typical out-of-pocket cost) and indicated condition (deep vein thrombosis/pulmonary embolism [DVT/PE], diabetes, or rheumatoid arthritis [RA]). The sample was recruited from US adult members of the nationally representative Amerispeak online panel. Results The sample included 2138 respondents. For ads featuring prescription drugs for DVT/PE, findings provide no evidence of an impact from price disclosure on perception of sufficient information. For ads for prescription drugs for diabetes, there was no evidence of an impact from list price only, but the price plus group was more likely than the control group to report the ad provided sufficient information (OR = 2.475). For ads for RA prescription drugs, both the list price only group (OR = 3.380) and price plus group (OR = 2.720) were more likely to report sufficient information than the control. Findings provide no evidence of an impact from price disclosure on consumer behaviors (i.e., intention to seek treatment or intention to comparison shop). Conclusions Mandatory DTCPA list price disclosure may not be the most effective tool for improving price transparency and affecting consumer behavior.
This study explores the extent of direct and mediated influence of consumer affinity and perceived value on consumers’ purchase intentions, in the realm of global brands. Using attitude theory and the elaboration likelihood model as conceptual anchors, a theory-driven model is tested in a between-subject design. Findings reveal that consumer affinity has a substantial and direct influence, while perceived value has a substantial mediated influence, with dominating affective component of the attitude. Perceived value has a stronger influence than consumer affinity on purchase intentions, but consumer aspirations make affinities stronger. These findings advance the consumer behavior literature and enhance managerial decision-making in market segmentation, targeting, and positioning contexts.
Purpose Mixed products, while presenting new business opportunities, raise considerable concerns among managers and researchers. However, whether mixed products (functionally vs culturally) trigger positive or negative consumer reactions is controversial. Hereby, the present research seeks to resolve the conflicting effects by examining the moderating role of service provider type (humanoid service robot vs human employee) in the impact of mixed products on consumer reactions. Design/methodology/approach Two studies were conducted to explore the effect of mixed products on consumer reactions. Specifically, study 1 was developed to examine the interplay of mixed products and service provider type in shaping consumers' product attitudes and purchase intentions under an offline shopping scenario; study 2 further provided evidence for the mediating roles of perceived usefulness and perceived enjoyment in the above processes under an online-shopping context. Findings The convergent findings of two studies conclude that, when served by a humanoid service robot (vs human employee), consumers exhibit more positive attitudes and higher purchase intentions toward functionally (vs culturally) mixed products. Furthermore, such effect is driven by the perceived usefulness (vs perceived enjoyment) when served by humanoid robot (vs human employee). Originality/value First, this is one of the first studies to conceptualize mixed products as the two-dimensional construct (i.e. functionally mixed and culturally mixed), and the findings sheds light on the mixed products literature. Second, this paper introduces service provider type as the boundary condition for the impact of mixed products on consumers' product attitudes and purchase intentions, which expands the match-up hypothesis and schema theory in service marketing. Third, the current research explores the mediating roles of perceived usefulness and perceived enjoyment in the above effects, which could make significant contribution to the motivation theory.
Influencers’ follower count, or indegree, is a key criterion that advertisers use when devising influencer marketing campaigns. However, whether influencers with lower or higher follower count are more effective in generating engagement remains an open question. This multimethod research effort—involving an observational field data analysis, based on 802 Instagram marketing campaigns featuring more than 1,700 influencers, together with an eye-tracking study and laboratory experiments—establishes conclusive evidence of an inverted U-shaped relationship between influencers’ follower count and engagement with sponsored content. A higher follower count implies broader reach but also cues a weaker relationship that reduces followers’ engagement likelihood. That is, engagement increases, then decreases, as influencer follower count rises. The authors further test the potential moderating effects of two campaign properties: Campaign content customization and brand familiarity. Higher content customization and lower brand familiarity signal that influencers value their relationships with followers and thereby flatten the inverted U-shaped relationship. Managers can leverage these novel results and the related actionable guidelines to improve their influencer marketing strategies.
Purpose There are two major strategies for short video advertising which are KOL (key opinion leader) endorsement and in-feed advertising. The authors aim to research the effectiveness of these two strategies for heterogeneous sellers. Design/methodology/approach The study employed a data set of users from Douyin. Using an endogenous treatment model, the study empirically examines the two strategies' effectiveness in attracting product traffic for online retailors at a short video app Douyin (TikTok). Findings The results show that the performance of in-feed advertising is higher when the seller's product is of lower price and when the seller has smaller cumulative video exposure. In addition, KOL endorsement is effective regardless of the product price, but performs better when the seller has larger cumulative video exposure. Originality/value To the best of the authors’ knowledge, this study is one of the first to explore the interaction effects of two major advertising strategies, KOL endorsement and in-feed advertising on short video platforms. The findings provide important theoretical contributions and practical implications.
Full-text available
In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators. (46 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The authors review the two-factor elaboration model of message repetition effects and report a study of the model's applicability to new product advertising. The study findings do not support the hypothesized inverted-U relationship between repetition and attitude toward a novel commercial and product. However, the underlying processes of learning, tedium arousal, and elaboration were observed. Viewer knowledge and commercial length did not moderate these processes.
The study suggests that the effect of repeated advertising exposures on brand evaluations is moderated by the ease with which the advertising message is processed. Increasing exposures enhanced the effectiveness of a difficult appeal, increased then decreased the effectiveness of a moderately difficult appeal, and decreased then increased the effectiveness of an easy appeal. These outcomes support the premise that message effectiveness can be affected by the time available for message processing and the time required for that task.
The authors analyze results of 389 BehaviorScan® matched household, consumer panel, split cable, real world T.V. advertising weight, and copy tests. Additionally, study sponsors—packaged goods advertisers, T.V. networks, and advertising agencies—filled out questionnaires on 140 of the tests, which could test common beliefs about how T.V. advertising works, to evaluate strategic, media, and copy variables unavailable from the BehaviorScan® results. Although some of the variables did indeed identify T.V. advertising that positively affected sales, many of the variables did not differentiate among the sales effects of different advertising treatments. For example, increasing advertising budgets in relation to competitors does not increase sales in general. However, changing brand, copy, and media strategy in categories with many purchase occasions in which in-store merchandising is low increases the likelihood of T.V. advertising positively affecting sales. The authors’ data do not show a strong relationship between standard recall and persuasion copy test measures and sales effectiveness. The data also suggest different variable formulations for choice and market response models that include advertising.
The authors propose that for mature brands, ad-evoked affect will not have a strong influence on brand attitude; they formulate brand interest, a new construct, as a more relevant consequence of ad-evoked affect. They present empirical evidence to support their theory regarding the consequences of ad-evoked affect for mature brands.
Recent advertising media models demand estimates of effects of repetitive exposures on consumers in particular advertising situations. A laboratory technique for providing such estimates is suggested, and a study using this technique indicates the need for significantly different repetition functions for different kinds of products, brand positions, advertising formats, and advertising goals. Further development of the technique is also indicated.
Although consumers often encounter ads for familiar brands, previous advertising interference studies have used ads for low-familiarity brands. The authors focus on brand familiarity's role in increasing ad memorability and moderating competitive interference. They conducted a factorial experiment varying the familiarity of brands featured in test and competing ads. With differences in ad executions, prior exposure, processing objectives, and exposure time experimentally controlled, subjects displayed substantially better recall of new product information for familiar brands. Their findings suggest that established brands have important advantages in advertising: Consumers should be more likely to recall ad information, and their memory should be less affected by exposure to competitors’ ads. The authors conclude with implications for the marketing of new and mature brands.
Ten years ago, "An Empirical Investigation of Advertising Wearin and Wearout" (Blair, 1987) presented data which demonstrated not only the ability of pretesting to predict advertising's in-market effect, but also how that advertising's selling power is delivered in market. The past decade has yielded a great deal more evidence on both subjects. Ten separate studies with a total of 500 observations have supported the original findings and provided insight into additional areas such as how advertising works for large brands and how an execution's wearout is affected by the airing of other commercials for the same brand. The practitioners who are applying this learning are achieving revolutionary improvement in advertising's impact on their revenue growth.