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The interactive effects of colors and products on perceptions of brand logo appropriateness

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Abstract

This article explores the role that color can play in building brand meaning with two experiments. Without prior conditioning, we demonstrate how an appropriately chosen color for a brand name (logo) can bring inherent and immediate value to a brand. Experiment 1 explores the notion of congruity, showing that it is more appropriate for functional products to be presented in functional colors, and sensorysocial products in sensory-social colors. Experiment 2 examines the effect of red and blue on brands of products that can be classified as both functional and sensory-social, and the ability of color to enhance a brand's desired image. When people know how brands are attempting to position themselves, people consider colors congruent with those positions to be more appropriate.
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Marketing Theory
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DOI: 10.1177/1470593106061263
2006 6: 63Marketing Theory
Paul A. Bottomley and John R. Doyle
appropriateness
The interactive effects of colors and products on perceptions of brand logo
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The interactive effects of colors and products
on perceptions of brand logo
appropriateness
Paul A. Bottomley
Cardiff Business School, UK
John R. Doyle
Cardiff Business School, UK
Abstract. This article explores the role that color can play in building brand meaning
with two experiments. Without prior conditioning, we demonstrate how an appro-
priately chosen color for a brand name (logo) can bring inherent and immediate value
to a brand. Experiment 1 explores the notion of congruity, showing that it is more
appropriate for functional products to be presented in functional colors, and sensory-
social products in sensory-social colors. Experiment 2 examines the effect of red and
blue on brands of products that can be classified as both functional and
sensory-social, and the ability of color to enhance a brand’s desired image. When
people know how brands are attempting to position themselves, people consider colors
congruent with those positions to be more appropriate. Key Words brand identity
color connotative meaning
Consumers associate certain brands with certain colors, such as Marlboro with
red, Guinness with black, and Cadbury with purple (Grimes and Doole, 1998).
Collectively, color, symbol, shape and lettering contribute to what Lightfoot and
Gerstman (1998) define as visual equity. Visual equity is the value derived from
‘visual form’, that is the ‘look and feel’ of the brand. Visual equity contributes
towards brand recognition, enabling a brand to stand out on the supermarket
shelf (e.g. the iconic shape of the Coca Cola bottle). It also helps to communicate
a brand’s desired image (e.g. Prudential’s Rock of Gibraltar logo with associations
of strength; Keller, 1998). We focus here on the intrinsic meaning of color, that if
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DOI: 10.1177/1470593106061263
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appropriately selected may bring, ‘inherent and immediate value to the brand’
(Kohli and LaBahn, 1997: 67), like a carefully chosen name.
But what makes a color appropriate for a product or conveying a brand iden-
tity, for instance in a logotype? Turning to the marketplace for guidance as to what
constitutes an appropriate color-product combination may prove unhelpful on at
least two counts. First, grocery store audits suggest that a package’s primary color
is often used to denote flavor (Garber and Hyatt, 2003). Second, based on a
survey of 82 product categories, over 50 percent of store brands from two US
supermarkets were found to imitate leading national brands’ visual equity in
terms of color, size and shape (Scott Morton and Zettelmeyer, 2000). While
imitation may be the greatest form of flattery, the color selection decision for these
copycat brands was essentially preordained, hence providing limited guidance
regarding the color selection decision beyond ‘follow the leader’.
This article investigates the role of color in brand image creation with two
experiments. The first study explores the issue of congruity, showing that it is
more appropriate for functional products to be presented in functional colors,
and sensory-social products in sensory-social colors. The second study extends
the first by exploring the ability of color to enhance or dilute brand identity and
considers the interplay of visual (color) and verbal (benefit proposition) informa-
tion. Finally, while prior studies have concentrated on single products, we
use multiple product categories to empirically test, rather than merely speculate
about, the generalizability of our findings.
The background literature
Keller (1998) defines brand elements as those trademarkable devices that help to
identify and differentiate the brand. Color is only one element of a brand’s
projection endowed with inherent meaning, previous studies attesting to the
influence of name (Keller et al., 1998; Klink, 2000), non-alphabetic logos
(Henderson and Cote, 1998), and typeface (Childers and Jass, 2002). Whilst
memory for the color of words is unusual during the normal course of reading
(Light et al., 1975), color provides a valuable retrieval cue for adults (Tavassoli,
2001) and children (Macklin, 1996) when learning brand names. More impor-
tantly, colors evoke a variety of associations that, without prior conditioning, can
be used to communicate a brand’s desired image in the consumer’s mind
(Madden et al., 2000).
The inherent meaning of color has consequences, particularly in marketing
applications. For instance, Bellizzi and Hite’s (1992) work on store atmospherics
suggests that people prefer blue rather than red retail environments, finding them
more relaxing, encouraging longer periods of browsing, and greater purchase
intention. Gorn et al. (2004) show that color influences how quickly a web page is
perceived to download, and feelings of relaxation mediate this relationship.
Similarly, Mandel and Johnson (2002) demonstrate that background colors and
images on a website could act as primes influencing attribute importance and
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product choice. Specifically, the ‘wallpaper’ on a car website featuring green
with dollar signs successfully primed price, whilst red and orange flames primed
safety.
Within branding, the inherent meaning of color has been examined using ad
hoc collections of words describing various emotions, personality traits, and
salient qualities for marketers (Grimes and Doole, 1998). For instance, Jacobs et
al. (1991) found that US students associated black with expensive and powerful,
blue with dependable, trustworthy and high quality, red with love, purple with
progressive and inexpensive, gray with dependable and high quality and yellow
with happy. Within the color psychology literature, more comprehensive frame-
works have been utilized (Valdez and Mehrabian, 1994). For instance, Adams and
Osgood (1973) surveyed people in 23 countries using Osgood et al.’s (1957) three
dimensions of connotative meaning (Evaluation, Potency and Activity). They
found that blue, green, and white were the most highly evaluated colors, whilst red
and black were the most potent. Red was also considered the most active color,
with black and gray the most passive.
Color preference studies suggest that, in general, hues are preferred in decreas-
ing order of liking: blue, green, purple, red and yellow (Whitfield and Wiltshire,
1990), although liking of individual colors may be country specific. For instance,
Madden et al. (2000) surveyed students from eight countries, and reported that
while liking for black, green, red and white was culturally invariant, preferences
for blue, brown, gold, orange, purple, and yellow were not. Just because you like
a color does not necessarily make it appropriate for presenting a product or brand.
However, researchers have found that favored colors are perceived to be favored
across a wider range of situations than unfavored ones (Taft, 1997) thereby sug-
gesting that they are more appropriate.
Color appropriateness: the notion of color-product congruity
We are interested in why people perceive that certain products should be
displayed in certain colors. In an early study, Schiller (1935) had women rank the
appropriateness of 20 color combinations for five products and five associations.
Breakfast foods and soap (functional products) were best received in green-
yellow, the color combination most strongly associated with economical and
cleanliness (functional benefits). Similarly, dignity and luxury (sensory-social
benefits) were most strongly associated with silver-black, the combination ranked
second for perfume (sensory-social product). We contend that both colors and
products have connotative meanings (sets of associations and overtones), and the
greater their similarity, the more appropriate a color will be for a product or
brand. Although the bases for similarity may differ, the notion of congruity has
figured prominently in the advertising and persuasion literatures (e.g. Drolet and
Aaker, 2002). In branding, Roth and Romeo (1992) showed that when country
image is congruent with the benefits desired from product category use, purchase
intention is enhanced. Likewise, Ruth (2001) found that brand evaluation is
Colors and brand logo appropriateness
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enhanced with emotion-category congruity – the extent to which a brand’s emo-
tion benefit proposition matches the emotions associated with product usage.
A forerunner to our own line of enquiry is the work of Walker et al. (1986), who
explored why certain typefaces are appropriate for some professions (products)
and not others. They found that typeface appropriateness was determined by the
extent a typeface shared inherent qualities with the concept it represented. For
instance, Palatino Italic was judged feminine, bright, quiet and light, qualities
associated with doctors and dentists (r= .76 and.77), whilst Braggadocio was con-
sidered masculine, rough and strong, qualities associated with builders (r= .55).
In addition, Lewis and Walker (1989) observed notable behavioral consequences
for conceiving of typeface as generating a second route to meaning, in addition to
the word itself. Based on a pre-test, Palatino Italic was shown to have connota-
tions of fast. In contrast Cooper Black connoted slow. People responded faster in
an experimental task (pressing one of two keys to a simple semantic judgment)
when the connotative meaning of the word matched that of the typeface (e.g.
Cheetah in Palatino Italic; Tortoise in Cooper Black) than when word and type-
face were incongruent.
Perceptual fluency refers to the ease with which a stimulus is processed.
Research suggests that increasing perceptual fluency, for instance by prior ‘mere
exposure’, increases our perceptions of a statement’s truthfulness, a name’s
famousness, the duration of the stimulus, and how much we like it (Jacoby et al.,
1989). Lee and Labroo distinguished between perceptual and conceptual fluency,
which they defined as, ‘the ease with which the target comes to consumers’ minds
and pertains to the processing of meaning’ (2004: 151). Conceptual fluency, like
perceptual fluency, leads to a more positive attitude towards the brand. Therefore,
we infer that congruent color-product combinations will be processed more
fluently (Lewis and Walker, 1989) and thus will be liked more, and rated as more
appropriate, than incongruent combinations.
The framework
The normative framework of Park et al. (1986) provides a powerful means of
classifying brands according to consumers’ underlying purchase motivations.
Brands can convey functional, sensory or social images. While functional brands
fulfill consumers’ utilitarian needs for problem solving or problem prevention,
sensory brands fulfill needs for sensory pleasure and stimulation, including
novelty and variety. Social brands fulfill symbolic needs for self-identity, group
membership and affiliation. Roth (1995) explored the relationship between
global brand image and performance using Park et al.’s framework. He found that
brands were unlikely to emphasize both functional and sensory-social benefits as
functional image ratings were highly negatively correlated with sensory (r= –0.83)
and social (r= –0.75) ratings. In contrast, sensory and social image ratings were
mildly positively correlated (r= 0.25), suggesting that brands may jointly empha-
size such benefits. In addition, Park et al.’s purchase motivation typology broadly
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corresponds to that used by Claeys et al. (1995) to classify products along the
think-feel dimension of the FCB grid (Vaughn, 1980). Therefore, in the interests
of parsimony, we shall aggregate products and brands into two categories: func-
tional and sensory-social combined. Integrating, Park et al.’s (1986) normative
framework with our notion of color-product congruity, we predict that:
H1: It is more appropriate for functional (sensory-social) products/brands to be presented in
functional (sensory-social) colors rather than sensory-social (functional) colors.
Assuming H1 is supported, this color-product interaction could be examined in
many ways. We concentrate on the red-blue comparison because it is well docu-
mented, and the primary focus of previous marketing studies. Reanalysing
Wexner (1954) provides evidence that red and blue have contrasting connotative
meanings. She asked people to identify the most appropriate color, from a set of
eight, to represent 11 mood-tones. Using frequency counts across this set of
mood-tones, we constructed a color-by-color correlation matrix. As anticipated,
blue and green were highly correlated (r= 0.87), while red and yellow were
mildly related (r= 0.18). Most important, red and blue had the largest negative
correlation (r= –0.59, p< 0.05), indicating that when red was judged appropriate
for conveying a specific emotion (mood-tone), blue was judged inappropriate.
We likewise reanalysed Jacobs et al.’s (1991) cross-cultural color comparison
(their Table 2). They asked people which color, from a set of eight, they most asso-
ciated with 13 concepts, including emotions and personality traits, and reported
whether 0–19 percent, 20–29 percent, 30–49 percent, or more than 49 percent of
subjects made the color-concept association. From this information, we con-
structed a Spearman’s rank correlation matrix. Once more, red-blue was the most
negatively correlated pair of colors for American subjects (r= –0.59, p= 0.03).
This finding also generalized, albeit weakly, across Japanese (r= –0.35), Korean (r
= –0.17), and Chinese students (r= –0.17).
Madden et al. (2000) had students from eight countries rate 10 colors on 20
semantic differential scales. For each country a perceptual map was created. In
general, blue, green, and white formed one cluster, black and brown another,
while red was the only color to stand-alone. Madden et al. contend that drawing
a straight line between red and the blue-green-white cluster creates, ‘a spectrum
of meaning (that) is evident across all countries’ (2000: 98) running from active,
hot and vibrant to calm, gentle, and peaceful. The remaining colors were located
equidistantly from these endpoints. To summarize, we conclude that red and blue
have contrasting connotative meanings based on evidence from different coun-
tries, collected at different points in time, and measured using different concepts
and associations.
Evidence regarding the connotative meaning of products is limited, although
many associations of colors appear to be highly germane to product category use.
For instance, the connotations of blue with sincere, dependable and trustworthy
(Jacobs et al., 1991) appear relatively more salient to the fulfillment of functional
(e.g. a bank) rather than sensory-social needs (e.g. a night-club). In contrast, the
connotations of red with exciting/stimulating, powerful/strong, cheerful/jovial
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(Wexner, 1954), adventure and love (Jacobs et al., 1991) appear more relevant to
the fulfillment of sensory-social needs. Thus, we predict:
H2: Blue will be more appropriate than red for functional products, and conversely, red will be
more appropriate than blue for sensory-social products.
Pretest: distinguishing functional from sensory-social products and
colors
A convenience sample of 15 academics and administrators identified functional
and sensory-social products and colors. Participants considered purchasing a
variety of products (40) and stated whether their decisions would be motivated by
the fulfillment of functional or sensory-social needs using a scale with endpoints
‘purely functional’ (1) and ‘purely sensory-social’ (7). This procedure was adapt-
ed from Leclerc et al. (1994). Functional products were defined as, ‘. . . products
that fulfill a need for problem solving or problem prevention’. Sensory-social
products were defined as those ‘that fulfill a need for personal expression, convey
status, attain social approval . . . or sensory pleasure (look, taste or smell nice),
variety or stimulation’. These definitions were adapted from Park et al. (1986).
There was good agreement as to the products’ underlying benefits: median
inter-subject correlation 0.75. To generalize our findings across materials and
adequately sample the product space, the six most functional and six most senso-
ry-social products were selected. The functional products chosen were: car tires
(1.20), anti-freeze (1.27), electrician (1.40), kitchen roll (1.53), solicitors (1.60)
and power tools (1.61). The sensory-social products were: perfume (6.47), expen-
sive restaurant (6.20), nightclub (6.13), amusement park (6.07), chocolates (6.00),
and ice cream (5.93). There was also good separation between the two product
groups: power tools, the least functional of the functional products set, was rated
lower than ice cream, the least sensory-social of the sensory-social products set
(repeated measures t(14) = –6.69, p< .001).
An analogous analysis was conducted for color. People considered the associa-
tions evoked by 16 colors, judging the extent to which each color was ‘purely func-
tional’ (1) or ‘purely sensory-social’ (7). Functional colors were defined as those
that elicit ‘associations that would be relevant for functional products, while
sensory-social colors suggest associations that would be relevant for sensory-social
products’. Not surprisingly, given the slightly unusual task, the inter-subject
correlations were somewhat weaker, although still quite strong (median r= 0.56).
Four functional (gray (1.47), black (2.40), blue (2.47) and green (3.13)) and four
sensory-social (red (3.97), yellow (4.27), pink (5.40), and violet (5.67)) colors
were selected. Again, there was good separation between the two color groups:
green, the least functional of the functional colors set was rated lower than red, the
least sensory-social of the sensory-social colors set (repeated measures t(14) =
–1.57, p= .06, 1-tail test).
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Method: subjects, procedure and materials
Thirty-five teachers and administrative staff (22 women) participated in the
experiment in return for a donation to school funds. Subjects were tested indi-
vidually in a room that was well lit by natural daylight, but out of direct sunlight,
with beige walls and ceiling, and a neutral carpet. All sources of artificial light were
switched off. Each person received a 13-page booklet. Page one introduced the
task directing subjects to, ‘Consider the fictitious company/brand Frampton. Take
each version of what Frampton is or does, and rate the appropriateness of each
color for that version of Frampton’. Ninety-six logos were presented (eight colors
×12 products), 10 on each page. Finally, manipulation checks assessed the needs
satisfied by each product, and associations evoked by each color (1 = highly
functional, 7 = highly sensory-social).
Each logo comprised the brand name set in a distinctive typeface and color, but
devoid of secondary embellishments, an approach used by Sony, Boeing and
Chanel (Carter and Higgins, 1999). Both the name and product (in parenthesis)
were printed in the same color: Frampton’s (night club). The logos were presented
in maximum saturation and medium luminance resulting in a rich color, un-
diluted by black or white, and printed using Microsoft PowerPoint on a Hewlett-
Packard DeskJet. Using the Windows color-definition system, the actual levels of
hue, brightness and saturation were: black (0, 0, 0), gray (0, 128, 0), green (85,
128, 255), blue (170, 128, 255), red (0, 128, 255), yellow (40, 128, 255), dark pink
(213, 128, 255) and purple (213, 66, 255).
Prior research indicates that names and fonts also possess inherent meaning
(Keller et al., 1998; Klink, 2000; Walker et al., 1986). To minimize any font effect
confounding the impact of color, all logos were presented in Broadway (24 point),
and all instructions in Times New Roman (18 point). Doyle and Bottomley (2004)
found, in a pretest of 25 fonts, that Broadway’s average appropriateness ratings
exhibited the least variance across 32 products, suggesting it was neutral.
Similarly, two family names were selected (Frampton and Bamforth) and treated
as a between-subjects factor. The names were relatively uncommon, given the
number of telephone directory entries, and held no strong associations with any
product or color, at least for these authors. Finally, to minimize any ordering
effects, the logos were presented in two random orders. In summary, each subject
rated the appropriateness of 96 logos, each displayed in a fully saturated color and
neutral font, in one of two brand names, and in one of two random orderings.
Color appropriateness was measured on an 11-point scale with end-points
‘highly appropriate’ (10) and ‘highly inappropriate’ (0). Although many possible
response variables could have been explored, including recall and recognition,
most classic studies in color (Schiller, 1935) and typography (Walker et al., 1986)
have used appropriateness, so one reason is simply to make contact with that
literature. But, past studies have focused on appropriateness with good reason: it is
a prime concern of anyone involved in selecting brand elements (color, name,
font). Further, Doyle and Bottomley (2004) have found that people chose products
(chocolate truffles that they actually consumed) more frequently when presented
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in packaging with an appropriate font rather than an inappropriate font. Thus,
there is evidence, albeit in a related domain, of a link between appropriateness and
a response variable of central importance to marketers, namely brand choice.
Results
Manipulation checks
The effectiveness of the manipulations was checked using a single-item scale
with the end-points ‘highly functional’ (1) and ‘highly sensory-social’ (7). There
was good separation between the two product groups: the least functional of the
functional products set was rated lower than the least sensory-social of the
sensory-social products set (M= 2.26 vs. 5.60, repeated measures t(34) = –8.24,
p< .001). Similarly, there was good separation between the two color groups: the
least functional of the functional colors set was rated lower than the least sensory-
social of the sensory-social colors set (M= 4.34 vs. 5.03, repeated measures t(34)
= –2.33, p< .026). As anticipated, the associations evoked by functional colors
were judged more relevant for the fulfillment of functional rather than sensory-
social needs.
Main results
Whilst the principle of generalization to other subjects is well understood,
researchers often neglect generalization to other materials (Clark, 1973). This
provides an accurate description of color research in marketing which has relied
on a few products and colors, but made little effort to combine these findings into
formally justified statements regarding the population from which the samples
were drawn. Our interest lies in generalizing to both subjects and materials. As our
materials consisted of both a sample of colors and a sample of products, we con-
ducted follow up analyses on a color-by-color and product-by-product basis.
H1: congruity between colors and products
According to H1, functional colors will be more appropriate than sensory-social
colors for functional products, the converse being so for sensory-social products.
To test this proposition, each subject’s functional color appropriateness scores
were averaged across the set of functional products and across the set of sensory-
social products. Similar computations were performed for each subject’s sensory-
social color scores. The four new series were entered into a repeated-measures
ANOVA. Product (functional vs. sensory-social), and color (functional vs.
sensory-social) were treated as within-subjects effects, while name (Frampton vs.
Bamforth) and problem order (order 1 vs. order 2) were treated as between-
subjects effects. As the two between-subject factors and their higher order inter-
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actions were not significant, we report results of a simplified analysis having
excluding these factors from further consideration.
The main effects for color and product were not significant (F’s < 1) but, as
anticipated, the color ×product interaction was (F(1, 34) = 132.69, p< .001), indi-
cating that functional and sensory-social colors were not equally appropriate for
functional and sensory-social products. Follow up within-product comparisons
revealed that functional colors were more appropriate than sensory-social colors
for functional products (M= 5.75 vs. 4.28; F(1, 34) = 66.35, p< .001). In contrast,
sensory-social colors were more appropriate than functional colors for sensory-
social products (M= 5.75 vs. 4.22; F(1, 34) = 31.25, p< .001). Similarly, the with-
in-color comparisons revealed that sensory-social colors were relatively more
appropriate for sensory-social products (M= 5.75 vs. 4.28; F(1, 34) = 52.65, p<
.001), while functional colors were relatively more appropriate for functional
products (M= 5.75 vs. 4.22; F(1, 34) = 98.8, p< .001).
Having shown the color-product interaction generalizes to different subjects
(using the same materials), an obvious next question concerns the degree to which
this interaction is true of all products and all colors sampled. This entails ruling
out the following scenarios: (1) there exist a small number of functional (sensory-
social) products for which functional (sensory-social) colors are relatively more
appropriate than sensory-social (functional) colors; (2) there exist a small
number of functional (sensory-social) colors for which functional (sensory-
social) products are relatively more appropriate than sensory-social (functional)
products; however the ‘signal’ from these few products (colors) may be sufficient
to register a statistically significant interaction.
Adopting a product-oriented focus, taking each product in turn, we performed
a repeated measures t-test comparing each subject’s mean appropriateness ratings
for (a) the set of functional colors with (b) the set of sensory-social colors. For
functional products we expect (a) > (b), and for sensory-social products we expect
(b) > (a). In 10 out of 12 cases the differences were significant (p< .05, 1-tail or
better) and in the predicted direction. However, the supposedly functional
kitchen roll was significant (p< .05), but in the wrong direction. While blue is
associated with hygiene, black and gray are often linked with dirt and grime.
When combined, this may have diluted the mean appropriateness rating for this
set of functional colors. For detailed results, see Table 1.
Adopting a color-oriented focus, taking each color in turn, we performed a
repeated measures ttest comparing each subject’s mean appropriateness ratings
for (a) the set of functional products, with their mean ratings for (b) the set of
sensory-social products. For functional colors we expect (a) > (b), whilst for
sensory-social colors we expect (b) > (a). All eight differences were significant
(p< .05, 1-tail or better) and in the predicted direction (see Table 2). Taken
together these two sets of results indicate that colors considered functional are
congruent with products considered functional, and judged to be more appro-
priate in which to display functional products. The same is true for colors and
products considered sensory-social.
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Table 1
Functional colors vs. sensory-social colors: a product-by-product analysis
Functional Sen.-soc. Mean Std. error Paired pvalue
Product colors colors diff. mean t-test (1-tailed)
Functional
Anti-freeze 5.71 4.36 1.34 0.33 4.07 .000
Car tires 6.11 3.59 2.52 0.27 9.20 .000
Electrician 5.87 4.39 1.48 0.27 5.46 .000
Kitchen roll 4.67 5.26 –0.59 0.29 –2.02 .026
Power tools 6.36 4.36 2.00 0.31 6.53 .000
Solicitor 5.77 3.73 2.04 0.32 6.41 .000
Sensory-social
Amusement park 4.41 6.51 –2.10 0.34 –6.14 .000
Chocolates 3.49 5.08 –1.59 0.34 –4.65 .000
Ice cream 3.69 5.61 –1.91 0.32 –6.00 .000
Night club 5.08 6.30 –1.22 0.36 –3.39 .001
Perfume 3.91 5.82 –1.91 0.35 –5.39 .000
Restaurant 4.73 5.16 –0.43 0.38 –1.14 .131
(expensive)
Note: Mean appropriateness ratings for each product averaged across functional (black, gray, green, blue)
and sensory-social colors (red, yellow, pink, purple).
Table 2
Functional products vs. sensory-social products: a color-by-color analysis
Functional Sen.-soc. Mean Std. error Paired pvalue
Colour product product diff. mean t-test (1-tailed)
Functional
Black 6.24 3.95 2.29 0.33 6.97 .000
Gray 5.54 2.74 2.80 0.28 10.19 .000
Green 5.00 4.52 0.49 0.16 2.96 .003
Blue 6.21 5.67 0.54 0.23 2.38 .012
Sensory-social
Red 5.16 6.14 –0.98 0.23 –4.29 .000
Yellow 3.06 3.99 –0.93 0.26 –3.57 .001
Bright Pink 4.34 6.56 –2.23 0.28 –7.76 .000
Purple 4.54 6.30 –1.76 0.23 –7.55 .000
Note: Mean appropriateness ratings for each color averaged across functional (anti-freeze, car tires,
electrician, kitchen roll, power tools, solicitor) and sensory-social products (amusement park, chocolates,
ice cream, night club, perfume, expensive restaurant).
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H2: red vs. blue
Hypothesis 2 predicts red is more appropriate than blue for sensory-social
products, the converse being so for functional products. Each subject’s blue (red)
appropriateness ratings were averaged across the six functional and the six
sensory-social products separately. These four series were entered into a repeated
measures ANOVA treating color and product as within-subjects factors. Whilst
there was no main effect for color (F(1, 34) = 2.13, p> .15) or product (F(1, 34)
= 1.50, p> .23), as anticipated, their interaction was significant (F(1, 34) = 29.30,
p< .001). Follow up within-product comparisons revealed blue was more appro-
priate than red for functional products (M= 6.21 vs. 5.16; F(1, 34) = 22.06, p<
.001), whilst red was marginally more appropriate than blue for sensory-social
products (M= 6.14 vs. 5.67; F(1, 34) = 3.17, p= .08).
To assess the generalizability to other materials, we performed a product-by-
product analysis comparing each subject’s red and blue appropriateness ratings
using a repeated measures ttest. For functional products, we expect blue to be
more appropriate than red, and for sensory-social products, red to be more
appropriate than blue. In nine out of 12 cases these differences were significant
(p< .05) and in the predicted direction. However, the supposedly sensory-social
ice cream approached significance (p< .1), but in the wrong direction. Perhaps,
the specific associations of blue with cold overwhelmed the more general hedo-
nistic connotations of red. A summary of these results is presented in Table 3.
Colors and brand logo appropriateness
Paul A. Bottomley and John R. Doyle
73
Table 3
Red vs. blue: a product-by-product analysis
Mean Std. error Paired pvalue
Product Blue Red diff. mean t-test (1-tailed)
Functional
Anti-freeze 6.91 5.63 1.29 0.66 1.95 .030
Car tires 5.63 4.49 1.14 0.38 3.04 .003
Electrician 6.20 5.54 0.66 0.38 1.71 .048
Kitchen roll 5.63 5.31 0.31 0.37 0.85 .200
Power tools 6.66 5.86 0.80 0.41 1.97 .029
Solicitor 6.23 4.14 2.09 0.43 4.84 .000
Sensory-social
Amusement park 6.23 6.97 –0.74 0.36 –2.05 .024
Chocolates 4.51 5.66 –1.14 0.42 –2.73 .005
Ice cream 5.89 5.11 0.77 0.51 1.52 .069
Night club 6.31 7.17 –0.86 0.48 –1.79 .041
Perfume 5.14 6.17 –1.03 0.38 –2.70 .006
Restaurant 5.94 5.74 0.20 0.41 0.49 .314
(expensive)
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Discussion
Experiment 1 examined the impact of color when presenting a brand/product’s
logo. We offered two hypotheses. H1 predicted that functional colors would be
more appropriate for functional rather than sensory-social products, whilst
sensory-social colors would be more appropriate for sensory-social products. One
specific aspect of this congruity hypothesis was further explored, namely the
red-blue comparison, because it is well documented, and the primary focus of
prior marketing studies. We predicted that blue would be more appropriate than
red for functional products, whilst red would be more appropriate for sensory-
social products. Both predictions were supported, suggesting that colors that are
connotatively congruent with the product will be rated as more appropriate.
Furthermore, the congruity hypothesis generalized to other subjects from the
same population (by significance testing) and to other colors and other products
(by replication) sharing the same selection characteristics as the ones used here.
Experiment 2
This study extends Experiment 1 in a number of important directions. Having
found support for the notion of congruity, we now investigate the effect of color
on products that can be classified as both functional and sensory-social. This
‘bi-valence’ gives these products greater flexibility in terms of brand identity,
image, and positioning, which means they should also be easier to manipulate
experimentally than products that are primarily functional or sensory-social.
Based on H2, if blue is more appropriate than red for functional products, and
vice versa for sensory-social products, then by inference red and blue should be
judged as equally appropriate for these bivalent products. Second, while
Experiment 1 focused on visual information, we examine here the interplay of
visual (color) and verbal (benefit proposition) information. Third, brand logos
will be evaluated holistically rather than explicitly considering color appropriate-
ness per se. Thus, extrapolating H2 from products to brands, we predict:
H3: Blue will be more appropriate than red for brands conveying a functional image, while red
will be more appropriate than blue for brands conveying a sensory-social image.
Our review of the color meaning studies, such as Madden et al. (2000), would
suggest that red and blue are maximally separated, being located at opposite ends
of the color meaning spectrum. In contrast, our empirical results indicate that red
and blue are minimally separated, with blue the least functional of the functional
colors (M= 3.66, manipulation check) and red the least sensory-social of the
sensory-social set of colors (M= 4.76). Acknowledging the different scales, time
periods and countries as contributing factors to these contrary findings, we pro-
ceeded with the red-blue comparison because they met the desirable criterion of
being judged equally appropriate across the set of 12 products considered in
Experiment 1 (M= 5.65 vs. 5.94; see Table 3).
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Pretest: identifying functional and sensory-social benefits
Pretest results from Experiment 1 revealed seven ‘bivalent’ products. Thus, a
second pretest was conducted to identify functional and sensory-social benefits
associated with these products. Twelve administrative personnel and graduate
students evaluated the extent to which various attributes and benefits fulfilled
functional rather than sensory-social needs on a single item scale with endpoints
‘purely functional’ (1) and ‘purely sensory-social’ (7) as previously defined. We
selected the two most functional and two most sensory-social benefits to manipu-
late the desired brand image. For instance, the ability of shampoo to eliminate
dandruff, and remove greasiness were considered highly functional benefits,
whilst being invigorating and producing a radiant shine were considered highly
sensory-social benefits; see Table 4.
Taking each product in turn, we performed a repeated measures ttest compar-
ing each subject’s average score for (a) the pair of functional benefits with (b) the
pair of sensory-social benefits (see Table 4, columns 3 and 5). Results revealed that
each pair of functional benefits was rated lower than each pair of sensory-social
benefits (all p’s < .01). A series of independent measures t-tests also indicated that
each pair of benefits differed from the scale midpoint (p< .01), with the exception
of holidays and fun and spectacular locations that approached significance
(p< .07). Thus, each pair of attributes was perceived as conveying functional or
sensory-social benefits, but not both.
Experimental design: subjects, materials and procedure
Subjects were 126 business studies students. A two-page questionnaire was
administered at the start of a lecture taking 10 minutes to complete. Although par-
ticipation was voluntary, all completed questionnaires were entered into a prize
draw. Materials consisted of seven choice problems. For each problem, subjects
indicated the appropriateness of two logos for conveying a brand’s desired image
by allocating a budget of 100 points (a constant sum) between the two alterna-
tives. As before, each logo comprised the name in a neutral font and a single color.
Presentation order was extensively counter-balanced. First, each product/brand
conveyed a functional or sensory-social image. For example, brands of sofa were
promoted as ‘hardwearing with washable covers’ or ‘stylish with sumptuous
fabrics’. Second, each product was presented in one of two family brand names:
for example, Leighton’s or Denbury’s Sofas. A different pair of names was
randomly allocated to each product. With seven problems, to limit the number of
variants of the questionnaire to a manageable number, we adopted a split-plot
design, creating two ‘product sets’ and two ‘name sets’ which were crossed. In
Product Set A, brands of sofas, shampoo and holidays conveyed functional
images, while brands of luggage, mountain bikes, sports watches, and health and
fitness centers conveyed sensory-social images, and vice versa in Product Set B.
Therefore, subjects evaluated brands with both functional and sensory-social
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Table 4
Pretest results for experiment 2
Mean of Mean of Paired t-test
Product functional sensory-social (1-tailed)
category Functional benefits benefits (a) Sensory-social benefits benefits (b) (a) vs. (b)
Health & fitness Highly qualified instructors 2.58 Beautiful décor 5.96 6.90
centres Scientific programs ** Exclusive membership * (.001)
Holidays Reliable 2.88 Fun 4.79 2.93
Efficient service * Spectacular locations ** (.007)
Luggage Durable 2.08 Fashionable 5.92 6.52
Lightweight ** Color coordinated * (.001)
Mountain bikes Built to last 2.38 Raced by champions 5.63 6.08
Easy to maintain ** Adventurous * (.001)
Shampoo Eliminates dandruff 2.71 Invigorating 4.92 6.61
Removes greasiness * Radiant shine ** (.001)
Sofas Hardwearing 1.92 Stylish 5.67 6.37
Washable covers * Sumptuous fabrics ** (.001)
Sports watches Accurate 2.79 Used by athletes 5.29 3.63
Reliable ** Stylish * (.004)
Note: In the main experiment, pairs of benefits labeled * appeared in Product Set A, while pairs of benefits labeled ** appeared in Product Set B.
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images. Similarly, 14 family names were divided into two groups, Name Set 1 and
Name Set 2, and a pair of names, one from each set, was randomly allocated to
each product. In particular, Leighton, Hoyland, Bamforth, Colgrave, Newberry,
Irving and Kersley (Name Set 1), were paired with Denbury, Montford,
Timperley, Pettifer, Oldroyd, Amstey and Roycroft (Name Set 2), and allocated to
sofas, shampoo, holidays, luggage, mountain bikes, sports watches and health
and fitness centers respectively. Third, subjects judged the appropriateness of the
blue logo relative to the red logo for conveying each brand’s desired image by
allocating a budget of 100 points between the two alternatives (a constant
sum approach). In half the questionnaires, the red logo was always positioned
above the comparable blue logo, and vice versa. Finally, in the interests of
‘good housekeeping’, the seven choice problems were presented in two random
orderings.
To summarize, the experimental design was a 2 (brand image) ×2 (names) ×2
(color ordering) ×2 (problem ordering) mixed design. Subjects were randomly
assigned to the 16 conditions. As in Experiment 1, the logos comprised the family
brand name displayed in (Broadway, 24 point) and printed in a fully saturated
color using PowerPoint. The actual levels of hue, brightness and saturation were:
red (0, 128, 255) and blue (170, 128, 255). Finally, the dependent variable was the
blue logo appropriateness score. (By definition, the red logo’s appropriateness
score is implicitly 100 minus the blue logo’s score).
Results
Hypothesis 3 predicts that blue logos will be more appropriate than red logos
for brands promoting a functional image, and vice versa for brands promoting a
sensory-social image. To assess this proposition, we averaged each subject’s blue
logo appropriateness scores across their functional and sensory-social brands
separately. Recall, Product Set A (B) was composed of three (four) functional and
four (three) sensory-social brands. These two series were entered into a repeated-
measures ANOVA with name (Name Set 1 or Name Set 2), problem order
(watches or sofas first) and color order (blue before red logo or vice versa) as
between-subjects factors.
As anticipated by H3, the within-subject benefit effect was significant (F(1, 118)
= 31.70, p< .001) indicating that blue was more appropriate for brands promoting
a functional rather than a sensory-social image (M= 58.95 vs. 48.29). The benefit
effect was tempered by two marginally significant interactions with problem order
(F(1, 118) = 3.58, p= .061) and color order (F(1, 118) = 3.93, p= .050). These inter-
actions simply revealed that the main effect was not quite parallel, although clearly
consistent with H3 in all cases. The average blue appropriateness scores for
functional and sensory-social brands in problem order 1 were 59.5 vs. 45.49, and in
problem order 2, 58.35 vs. 51.17. Similarly, the average blue appropriateness scores
in color order 1 were 61.36 vs. 46.87, and in color order 2 were 56.61 vs. 49.64. No
other main effects or higher order interactions were significant (p> .15).
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In the interests of generalization, a product-by-product analysis was conducted
to determine whether the ‘benefit effect’ was true of all products sampled. For
each product, an independent measures t-test was performed; see Table 5. In the
case of shampoo, holidays, mountain bikes and luggage, the differences in blue
logo appropriateness scores for functional brands compared to sensory-social
brands were significant (p< .05, 1-tailed) and in the predicted direction, with
sports watches marginally significant (p< .07). No difference was found for sofas.
However, health and fitness centers were significant (p< .05), but contrary to
expectations sensory-social benefits were judged more favorably in blue. It may
be a case of ‘two questions in one’. While health clubs (sensory-social) are associ-
ated with relaxation and pampering, qualities elicited by blue, fitness centers
(relatively functional) are associated with strenuous physical exercise that is both
hot and active, qualities elicited by red. In both cases, the specific associations run
contrary to the general associations of functional products with blue and sensory-
social products with red, and may have overwhelmed them on this occasion.
Nonetheless, taken as an ensemble, these results do confirm H3 even under
the most unfavorable of conditions, namely an independent measures t-test
(assuming unequal variance) of the blue logo appropriateness difference scores,
conducted at the stimulus level (n= 7). The average gain of 10.70 appropriateness
points per product was significantly different from zero (p= .038, 1-tailed). Thus,
a brand’s benefit proposition can make these ‘bivalent’ products as polar in terms
of color choice, as the non-bivalent (functional or sensory-social) products
analysed in Experiment 1.
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Table 5
Blue logo appropriateness scores for brands promoting a functional vs. a
sensory-social image: a product-by-product analysis (independent measures
t-tests)
Sensory- Unequal
Functional social Mean Std. error variance pvalue
Product image image diff. mean t-test (1-tailed)
Health & fitness centres 54.52 65.30 –10.78 3.98 –2.71 .004
Holidays 53.32 29.84 23.68 3.95 5.96 .001
Luggage 58.00 48.95 9.05 3.63 2.49 .007
Mountain bikes 53.63 35.61 18.02 4.06 4.40 .001
Shampoo 64.78 37.74 27.04 3.92 6.90 .001
Sofas 62.73 60.16 2.57 3.85 .67 .253
Sports watches 64.84 59.30 5.54 3.67 1.51 .067
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Discussion and conclusions
Together, these studies respond to Garber and Hyatt’s (2003) call for guidelines to
assist marketing managers with the color selection decision. The initial study
established that colors that are connotatively congruent with products are con-
sidered more appropriate. Specifically, functional colors are more appropriate for
functional products, and sensory-social colors more appropriate for sensory-
social products. Even red, the least sensory-social of our set of sensory-social
colors, and blue, the least functional of our set of functional colors, supported this
notion. The second study addressed within-product category heterogeneity,
acknowledging that brands can adopt a variety of positioning strategies, and thus
products may be more color tolerant than initially observed. Brands promoting a
functional image were better received in blue, while brands promoting a sensory-
social image were better received in red.
We have shown that colors and products have connotative meanings that are
sufficiently shared by people to produce a systematic pattern of results consistent
with our hypothesis, namely that congruent combinations will be judged more
appropriate. However, these observed effects may have been amplified given:
(1) the within-subjects nature of the task (multiple comparisons), (2) explicit
instructions to rate appropriateness, and (3) color being the main distinguishing
feature among a set of nearly identical logos. To assess the actual relevance
and size of the congruity effect requires further study, ideally using downstream
variables, such as brand attitude or brand choice, under conditions of incidental
exposure, with richer stimuli, and a between-subjects design to minimize the
extreme focus on color that characterizes the current tasks. Nevertheless, Doyle
and Bottomley (2004) found that people chose chocolate truffles in a ratio of 3:1
from a box displaying an appropriate font for chocolates, rather than an inappro-
priate font. Thus, we are mildly confident that our results will have practical
implications beyond our ‘sterilized’ world.1
To date, we have examined logos presented in a single color on a white back-
ground, yet many brands are associated with color combinations, such as FedEx
with purple and crimson, BP with yellow and green. Work on the inherent
meaning of color combinations has produced conflicting findings. For instance,
Madden et al. (2000) asked people to select a color to partner a logo that consisted
of a red, blue or green square. Colors with complementary meanings were paired
with red; colors with consistent meanings were paired with blue; while green
exhibited no obvious pattern across cultures. Having identified a color combina-
tion, the impact of foreground and background color might be explored using
theories of color harmony (Morriss and Dunlap, 1987) that focus on issues of
spatial balance and relative area to refine the meaning. While both Shell and
McDonald’s are associated with red and yellow, the colors are combined in
different proportions. Do these differences contribute to subtle variations in con-
notative meaning?
From an international perspective, more research is required on color’s cross-
cultural meaning. For instance, Madden et al. (2000) suggested that blue, green,
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red, white, black, and brown are culturally invariant, while purple, yellow and
orange are not. Hupka et al. (1997) distinguished between primary emotions
(anger, fear) that are genetically based with roots in evolution, and culturally
based compound emotions (envy, jealousy). Colors associated with primary
emotions were held more consistently across countries than colors with com-
pound emotions, suggesting that brand images based on primary emotions offer
more opportunities for standardization across countries. Consequently, we might
expect IBM’s logo (Big Blue) to convey a culturally invariant meaning, while
FedEx’s purple and orange trade-dress to be culturally variant, and requiring
customization to ensure a consistent image in the global marketplace. Further,
Tavassoli (2001) found that Chinese students had better memory for the color of
logographs than American students did for the color of alphabetic words. With
greater reliance placed on visual processing when reading logographs rather than
words, the connotative meaning of color may be more important in communi-
cating a desired brand image in eastern rather than western cultures.
From a methodological perspective, we treated connotative meaning as a
uni-dimensional construct (functional vs. sensory-social), although multi-
dimensional perspectives are popular within color psychology. For instance,
Adams and Osgood (1973) measured color meaning in 23 countries using Osgood
et al.’s (1957) three dimensions of connotative meaning (Evaluation, Potency and
Activity). Extending our notion of congruity, we might infer that potent products
should be displayed in potent colors, active products in active colors, and good
products in good colors. But, color is only one element of a brand’s projection
endowed with inherent meaning (Childers and Jass, 2002; Henderson and Cote,
1998; Keller et al., 1998). Future research should clarify whether the proposed
approach for selecting colors for products and brands can be used in parallel
fashion for selecting non-alphabetic logos (symbols), typefaces and names. We are
confident it can be. While the relative effectiveness of our functional sensory-
social measure compared to Osgood et al.’s (1957) framework remains a moot
point, the latter is known to be robustly portable, having been successfully used to
assess words, simple pictures and other non-verbal communications (Valdez and
Mehrabian, 1994). What is clear is that future studies will need to integrate brand
elements from several domains to advance understanding in this area.
Finally, our hypotheses were grounded in the empirical findings of laboratory
studies on the inherent meaning of color ‘chips’. This replication and extension of
them to a different context suggests that this body of knowledge is not as insular
or ‘incestuous’ as Whitfield and Wiltshire (1990) and others might suspect. As
such, marketing managers wishing to explore the extensive literature on color
psychology for purposes of brand building should take heart.
Acknowledgement
The authors would like to thank Jonathan Clark, Karen Cook, Nigel Cook, and Tim
Wakeley for assisting with the fieldwork.
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Note
1 We would like to acknowledge the reviewers for these useful suggestions.
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Paul Bottomley is a Distinguished Senior Research Fellow at Cardiff University.
Current research interests are in the areas of brand management, brand extensions, and
visual equity, namely the value derived from the visual form, that is the look and feel of
the brand. His previous work has been published in the Journal of Marketing Research,
International Journal of Research in Marketing and Organizational Behavior and Human
Decision Processes. Address: Cardiff Business School, Cardiff University, Aberconway
Building, Colum Drive, Cardiff, CF10 3EU, UK. [email: bottomleypa@cardiff.ac.uk]
John Doyle holds a doctorate in experimental psychology and is a Distinguished Senior
Research Fellow at Cardiff Business School. He has published in the Journal of
Marketing Research, International Journal of Research in Marketing, Management Science,
Journal of Business Research,Organizational Behavior and Human Decision Processes, and
Cognitive Psychology. Research in progress relevant to this issue investigates the con-
notative impact of different aspects of a brand’s visual projection (name, logo, colour,
and font), their fit with purpose, and the psychological processes by which meaning is
derived from them. Address: Cardiff Business School, Cardiff University, Aberconway
Building, Colum Drive, Cardiff, CF10 3EU, UK. [email: DoyleJR@cardiff.ac.uk]
Colors and brand logo appropriateness
Paul A. Bottomley and John R. Doyle
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... colors, shape, font) to a company's target market. Specifically, extant studies in the field focus on logo's color (Bottomley & Doyle, 2006;Labrecque & Milne, 2011), symbols and shape (Henderson & Cote, 1998). ...
... In general, research on color psychology has demonstrated that colors can trigger emotional reactions (Levy, 1984) thanks to their ability to recall past associations and experiences (Bottomley & Doyle, 2006). Clarke & Costall's (2007) qualitative study on the link between colors and emotions presents a comprehensive investigation of colors connotations by allowing participants to provide their own salient examples without restricting them to a limited set of emotions categories. ...
Thesis
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This research aims at expanding our understanding of founder social identity in decision-making processes with regards to the founder’s marketing choices. Specifically, the main research question of this work is: how does founder social identity influence decisions regarding identity anchors in sustainable new ventures? The identity anchor that this work will take into account is the company’s logo, one of most powerful communication tools available to companies and the main synthesizer of what a brand stands for.
... The strategic choice of colour has been exploited in product packaging design and has proven effective in shaping brand impressions (Madden, Hewett and Roth, 2 28 2000), in attracting consumer attention (Grimes and Doole, 1998), as well as in distinguishing brands from competing products at the point-of-purchase (Garber, Burke and Jones, 2000). Because of these different colour associations with objects and emotions, in packaging, consumers will perceive a particular package design to be more appropriate when there is a congruence between the colour used and the product type (Bottomley and Doyle, 2006). More specifically, it was found that blue colours were more appropriate than red for functional products, and that red was more appropriate for sensory-social products (ibid.). ...
... If products are advised to use colours that evoke a strong automatic association with positive attributes (Madden, Hewett and Roth, 2000) or create a congruent experience for consumers with product (Bottomley and Doyle, 2006), then this sets a challenge for new products that do not conform to the norm, though the novel use of colour can become advantageous in attracting some types of consumer, especially those who are not loyal to particular brands (Garber, Burke and Jones, 2000). ...
Thesis
This thesis explores the use and effects of maximisers when included within Health and Nutrition (H&N) claims on food product packaging, with direct relevance for industry practice. Four separate studies were carried out in support of this thesis, one field study and three online experimental studies. The effects of the maximiser language device were investigated through an online field experiment, conducted through the Facebook Ads Manager platform, with the results demonstrating that the use of maximisers has a positive effect on product likeability among Facebook users. The first online experimental study then demonstrated the informality features of maximisers, and highlighted the importance of consumer perceived congruence bet ween the language used in advertising a product and the retail environment in which the product is encountered. Results from this study showed that the used of maximisers in H&N claims has a positive direct effect on product likeability. The second online experimental study extended on the concept of perceived congruence from the first online study, investigating the congruence between the use of language and customer comments and reviews, and its effect on perceptions of and purchase intentions towards a product. The study demonstrated the sincerity and affirmation features of maximisers, and showed the interaction of these features with online reviews, with the presence of maximisers having a moderating influence of product perceptions when bad reviews are present. The third and final online experimental study tested the effect of maximisers in a realistic setting, investigating the effects of cognitive load on evaluations of and purchase intentions towards a product. The findings showed maximisers work effectively when consumers are cognitively available, with a reversed effect apparent when consumers are subjected to a high cognitive load. The findings from the experimental studies have potential for impact in industry practice in the marketing and advertising of food products, and for the design of food packaging, as well as for policy-makers aiming to protect consumers and consumer interests related to food advertising.
... Choosing a color is a complex process, because a color should correctly reflect the visual identity of a brand, provoke the wanted image of a brand in consumers' minds, and contribute to the creation of brand awareness [71,74]. The meaning of colors has been analyzed in detail in the past years [75], e.g., the color blue is associated with trust, the color white with purity, and the color purple implies energy and represents excitement. ...
Article
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The world is changing faster than ever before. Continuous changes are also affecting the higher education sector. The number of programs on offer is growing, attraction strategies are changing, and the branding and positioning of higher education institutions are gaining significance. The growing influence of social networks on personal choice cannot be ignored. Of the world’s population, 57% uses social networks and spends an average of 2.5 h a day on them. The most popular social network, Facebook, has up to 2.9 billion active users every month. Therefore, the questions arise as to which factors influence one or another consumer choice, how social networks contribute to brand awareness, and what impact brand has on the higher education sector. After systematic and comparative analysis of concepts published in the scientific literature, the analysis of brand, brand promotion concepts, and factors that increase brand awareness is performed. This study seeks to determine whether and to what extent individual factors influencing student motivation and social networking influence the distinctiveness of a higher education institution brand and how factors influencing student motivation and social networking affect the distinctiveness of higher education institutions’ brands in general. The results of this study can help higher education institutions to develop their own plans, strategies, and good practices. Research methods: systematic and comparative analysis of concepts and methods published in the scientific literature, mathematical and statistical methods, statistical processing, and expert survey.
... Peters (1999) emphasized the importance of the visual power of a logo (Walsh et al., 2010:76). On the other hand some scholars (Bottomly and Doyle, 2006;Henderson and Cote, 1998;Janiszewski and Meyvis; asserted that logos were prominent features of various direct or indirect communication mediums ranging from packing, promotional materials and advertisements to business cards and letterheads (Walsh et al., 2010:77). In addition, Snyder (1993) discusses the logo as a material bearing company's own signature in literature on corporate identity (Henderson and Cote, 1998:14). ...
Chapter
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Introduction The fact that we live in a consumer society causes us to face more brands. It is precisely at this point that more brands, more visual data and as a consequence more logos get imprinted into our minds. Considering Neuromarketing, those visual elements leave their marks on our brains through communicating with them. People, taking their personality traits and interests into consideration, adopt the objects they see or ignore and just imbed them into their subconscious mind. The goal of a company is to be imprinted into the mind of customers and create loyal customers attached to the company. Companies wishing to build customer loyalty take advantage of symbols expressing their own corporate image and identity. Therefore, companies make use of logos telling who they are and expressing their image. A logo can be defined as a symbol, graphic mark or colour and an important Neuromarketing and awareness tool revealing the character of a company. It appears that logo is an element, which is regarded important and creates "awareness" in the concept of competition. It would also be correct to explain logo as a mental projection because the visual input transferred from eyes to brain is recalled and imprinted into our minds where it is interpreted and perceived. The main issue important here is to answer the question: "What is the process of selecting the right logo?" Every company has its own character, marketing image, products and customer portfolio. It is therefore necessary for a logo to meet those differences. When the logo is considered as the visual face of a brand, it is the first sign customers see before they get acquainted with company's products/services. When we go through existent literature, logo is related to a variety of concepts ranging from creation of corporate identity and raising awareness to impact on brand attitude and changing buying behaviour of customers in different age groups. Although it is not possible to assert that logo is the only factor affecting all those concepts, much research conducted revealed its significant impact on them. The logo speeds up the decision-making process and helps customers to make quicker decisions especially when they feel undecided and have brand loyalty. It is necessary to acknowledge that the symbol which is expected to represent the brand image maybe for centuries should be selected after a right decision making process. A logo is not only a shape but also a symbol, which represents the image of a company, a place where customers and companies come together and make a difference in competition. In brief, this study aims to highlight the importance of logo selection for companies as it would affect company image for years and it is therefore necessary for successful companies to have successful logos.
... Logos cannot stand alone, but must gel with an organisation's visual identity. Visual identity is established through visual components such as (1) the logo shape (Fajardo et al., 2016;Jiang et al., 2016), (2) logo symmetry (Airey, 2009;Bajaj & Bond, 2014van Grinsven & Das, 2016), (3) the colours (Bottomley & Doyle, 2006;Hynes, 2009;Labrecque & Milne, 2012), and (4) typefaces (Foroudi et al., 2017;Grohmann et al., 2013;Henderson et al., 2004). The visual elements can appear on various formats including promotional material, packaging, letterheads, clothing, and stationery (Bajaj & Bond, 2014). ...
Thesis
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This research aimed to establish how two community-based organisations (CBOs) in inner city Johannesburg used communication to build political power in their political networks. As such, I explored theories on building, shaping, and transforming networks of power, especially with reference to Latour, and Deleuze and Guattari’s concept of an assemblage. Assemblages are underpinned by the desire to make connections and therefore Deleuze and Guattari’s concept of desire is helpful in revealing the connections between different elements of political communication. The departure point for this research was to examine how CBOs use political communication in networks of power or to generate networks of power. The research examined flows of communication among CBO members, their communities, and other audiences, using an a political communication machine/assemblage. The machine has five components, which were explored in depth in the chapters of this thesis. They are: desire, framing, aesthetics, communication tools and audiences. Desire is not a lack but the creative, productive impetus for the organisations; using this theory to explore the two CBOs communications led to insights into the not only the material outputs and conditions of communication, but also both the rational and affective qualities of that communication. In terms of the study of communication, the conceptual framework allowed for the study of the different components working together to generate a communication flow, instead of simply relying on a static study of frames, or tools, or aesthetics or audiences. As such, the study reveals the dynamism in CBO political communication. Previous studies of South African CBOs have mentioned that before CBOs protest, they undertake extensive efforts to communicate with government; however, the previous studies did not elucidate what these extensive efforts consisted of, so this study has provided rich detail for further exploring the dynamic. The two CBOs were markedly different in their structure and their efforts to communicate. The Inner City Resource Centre (ICRC), which tackles housing issues in the inner city, was well funded, and had offices. Their communication efforts were highly effective at building and retaining its core membership. However, they were not successful in connecting with the City of Johannesburg, because the city had locked them out of participatory spaces. One Voice of All Hawkers Association (One Voice) was highly fractious, some members exhibited micro-fascisms, and the organisation ran in somewhat of a haphazard pattern in its efforts to protect street traders. However, they were highly successful at micro-local politics, using subterfuge to undermine the city’s trader administration system and preventing traders from being evicted. One Voice also sustained a large membership base over a long period of time, and this was mainly based on one-on-one communication. Their success was not based on a powerful political communication machine, but instead on the way they opportunistically managed micro-local circumstances. The study showed that an effective political communication machine was important for growing solidarity networks. However, large parts of government could not be reached, regardless of what communication strategies the organisations deployed, since participatory governance spaces were either closed off or inaccessible.
... Previous research has investigated consumers' perceptions and evaluations of a brand logo's various design elements, including shape (e.g. the use of circular and angular shapes) and color (Bottomley and Doyle, 2006;Jiang et al., 2016;Labrecque and Milne, 2012;Zhang et al., 2006), a complete typeface (Hagtvedt, 2011), framed or unframed logos (Cutright, 2012;Fajardo et al., 2016) and symmetry (Bajaj and Bond, 2018). In this research, we focused particularly on the complexity of brand logos. ...
Article
Full-text available
Purpose This research aims to examine the role of perceived threat (i.e. COVID-19) on people’s preferences for destination logo designs. In addition, it investigates the influence of childhood socioeconomic status (SES) and sensation seeking on the aforementioned effect. Design/methodology/approach Five experiments are used. Studies 1 A and 1B examine the impact of the threat of COVID-19 on visiting intentions as influenced by different destination logos. Study 2 replicates the previous studies and tests for evidence of mediation by the perceived risk. Studies 3 and 4 investigate the moderating role of childhood SES and sensation seeking. Findings The results show that a salient threat of COVID-19 leads people to display higher visiting intentions when presented with simpler (vs complex) destination logo designs. The perceived risk mediates this effect as well. This preference is evident only for people with low (vs high) childhood SES and only for relatively low sensation seekers. Research limitations/implications This study contributes to the branding literature by investigating how situational factors can influence affective reactions to brand logos and to the tourism literature by further investigating the impact of logos on visiting intentions. Practical implications This study provides actionable insights for tourism marketers and logo designers, allowing them to select or create positively perceived destination logos during a potential global crisis. Originality/value This research offers the first evidence that pandemic-related threat perceptions influence people’s visiting intentions when presented with different destination logos, and that these effects are influenced by individual characteristics such as childhood SES or sensation seeking. In doing so, the current study offers a more sophisticated understanding of the potential boundary conditions driving people’s brand logo evaluation.
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Visual Communication is a strong tool to represent the corporate identity. Logo design is the second important thing in branding. Religion Islam encourages us to mark identity to our belongings, individuals, and goods. In this account Prophet Muhammad (s.a.w) set the examples in his life. Pakistan is the second-largest Islamic country and Islamic history leaves an impression on the branding strategies. This research paper will discuss the logo design of Pakistan. Further will study the strategy of companies in the selection of symbols, icons, typography for the emblem, and wordmark of the logo. To analyze the data Content Analysis methodology has been used for this paper, in which logos of the educational sector and banking sector has been selected. Data was collected from secondary sources like official websites and prior research. The study indicates how Islamic roots of all Islamic countries are connected and
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This study examines the impact of brand logo colorfulness on consumer judgments toward a brand and its products. Four experiments demonstrate that the colorfulness of a brand logo affects consumers' perception of the product variety offered by the brand. When consumers feel that a brand logo is colorful, they tend to infer that the brand offers a high variety of product options to its customers. Driven by the perception of product variety, logo colorfulness has downstream consequences on consumer attitudes, an effect that can be moderated by brand positioning. Together, this study introduces the effects of logo colorfulness on consumer judgments, contributes to the psychological literature on color and variety, and bears important practical implications regarding how designers and marketers can practically determine a brand logo that best serves the brand image.
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We are living in a world where there are ever more products available to us. In such a crowded marketplace, brand owners need to try ever harder to make their products appeal to consumers. In many situations, such as the cluttered and colourful aisles of the supermarket, brand manufacturers have very little time in which to communicate their point of difference. We have seen elsewhere in this book how differentiated brands are able to stand out from the crowd. This chapter concentrates on one particular means of differentiation — brand packaging.
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Current investigators of words, sentences, and other language materials almost never provide statistical evidence that their findings generalize beyond the specific sample of language materials they have chosen. Nevertheless, these same investigators do not hesitate to conclude that their findings are true for language in general. In so doing, it is argued, they are committing the language-as-fixed-effect fallacy, which can lead to serious error. The problem is illustrated for one well-known series of studies in semantic memory. With the appropriate statistics these studies are shown to provide no reliable evidence for most of the main conclusions drawn from them. A review of other experiments in semantic memory shows that many of them are likewise suspect. It is demonstrated how this fallacy can be avoided by doing the right statistics, selecting the appropriate design, and sampling by systematic procedures, or, alternatively, by proceeding according to the so-called method of single cases.
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Word associations or verbal synesthesia between concepts of color and emotions were studied in Gersnany, Mexico, Poland, Russia, and the United States. With emotion words as the between-subjects variable, 661 undergraduates indicated on 6-point scales to what extent anger, envy, fear, and jealousy reminded them of 12 terms of color. In all nations, the colors of anger were black and red, fear was black, and jealousy was red. Cross-cultural differences were (a) Poles connected anger, envy, and jealousy also with purple; (b) Germans associated envy and jealousy with yellow; and (c) Americans associated envy with black, green, and red, but for the Russians it was black, purple, and yellow. The findings suggest that cross-modal associations originate in universal human experiences and in culture-specific variables, such as language, mythology, and literature.