IMPRESSION MANAGEMENT USING TYPEFACE DESIGN · to choose typefaces that impact strategically valued...

Impression Management Using Typeface Design

Pamela W. Henderson

Joan L. Giese

Joseph A. Cote

Conditional Acceptance at the Journal of Marketing Ms 02-168 April 2004

Copyright © 2002-2004 Pamela W. Henderson, Joan L. Giese, and Joseph A. Cote all rights reserved

Pamela W. Henderson is Associate Professor of Marketing, Washington State University, 2710 University Drive, Richland, WA 99352, 509-372-7207, 509-372-7512 (fax), [email protected]. Joan L. Giese is Assistant Professor, Department of Marketing, Washington State University, Pullman, WA 99164-4730, 509-335-6354, 509-335-3865 (fax), [email protected]. Joseph A. Cote is Professor, Department of Marketing, Washington State University, 14204 NE Salmon Creek Avenue, Vancouver, WA 98686 360-546-9753, [email protected]. The authors gratefully acknowledge Donovan Follette, Theresa Grate, Jeff Boettcher, James Hutton, Andrew Eads, numerous professional graphic designers, the editor, and the reviewers for their contribution to this research.

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Abstract

This paper develops empirically-based guidelines to help managers select typefaces that impact

strategically valued impressions. The potential tradeoffs among the impressions created by

typeface – pleasing, engaging, reassuring and prominent – are addressed. Selecting typeface can

be simplified by use of six underlying design dimensions; elaborate, harmony, natural, flourish,

weight, and compressed.

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The visual aspects of a corporation’s marketing materials are receiving increasing attention in

marketing research (Childers and Jass 2002; Henderson and Cote 1998; Shapiro 1999; Tavassoli

2001, 2002; Tavassoli and Han 2001, 2002; Veryzer and Hutchinson 1998). By far, the most

pervasive design element in marketing materials is typestyle. Both academicians and

practitioners recognize that typeface design is an important visual tool for accomplishing

corporate communication objectives (Childers and Jass 2002; Hutton 1987; McCarthy and

Mothersbaugh 2002; Pan and Schmitt 1996; Tantillo, DiLorenzo-Aiss, and Mathisen 1995).

Initial research indicates that typeface design impacts perceptions of advertised brands,

influences the readability and memorability of ads (Childers and Jass 2002; McCarthy and

Mothersbaugh 2002), creates strategically important impressions (e.g., general positive image to

more specific impressions of innovativeness, change, power, or warmth, see Craig 1980; Dolen

1984; Hinrichs and Hirasuna 1990; Hutton 1987, 1997; O'Leary 1987; Solomon 1991; Somerick

2000; Spaeth 1995; Tantillo, DiLorenzo-Aiss, and Mathisen 1995), affects the appropriateness of

the typeface for different products (Pan and Schmitt 1996; Walker, Smith, and Livingston 1986),

and may affect a company’s financial performance (Bloch 1995; Hertenstein and Platt 2001;

Hutton 1997; Wallace 2001).

Despite increasing research on the subject, little guidance is available to assist corporations in

selecting typeface to create strategically important impressions. Research on the impressions

created by typeface has assessed only a few of the many characteristics that differentiate their

design. Characteristics studied include serif versus sans serif (Tannenbaum, Jacobson, and

Norris 1964; Tantillo, DiLorenzo-Aiss, and Mathisen 1995), general use versus novel display,

weight (Rowe 1982), and italics (Tannenbaum, Jacobson, and Norris 1964). In addition, most

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studies have examined only a small set of typefaces (10 or fewer); thus limiting the variance seen

in the extensive pool of fonts from which corporations make their selections. Furthermore,

conflicting results continue to surface (e.g., Rowe 1982; Tantillo, DiLorenzo-Aiss, and Mathisen

1995). The only conclusion researchers generally agree about is that typeface design impacts

responses, yet the nature of its effects are not well known. This lack of guidelines led McCarthy

and Mothersbaugh (2002) to call for research to create a set of principles linking the features of

type with the impressions they create.

In this paper, we develop a set of empirically-based guidelines to improve managers’ ability

to choose typefaces that impact strategically valued impressions. In particular, we address four

questions:

1. What are the strategically relevant impressions created by typeface design? 2. What characteristics are most useful for describing typeface design? 3. What is the impact of design on each type of impression? 4. What guidelines should corporations follow to achieve their communication goals

through the use of typeface design? We conducted an exploratory study of current typeface designs and the impressions they create.

Being exploratory in nature, the study is not based on a specific theoretical perspective.

However, there are a few theories related to the possible dimensions of impressions and design

characteristics that will help direct the analysis. Thus, we briefly review theories and empirical

research related to the dimensionality of design and the impressions they create for other stimuli.

Review of Typeface Design Effects

There are two classes of studies that allow us to anticipate the influence of typeface design

characteristics on consumer responses. First, several empirical studies have directly explored the

relationship between a typeface’s characteristics (e.g., serifs) and a response (e.g.,

innovativeness). For example, Tantillo, DiLorenzo-Aiss, and Mathisen (1995) investigated the

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influence of typestyle on selected affective responses (e.g., happy/sad and young/old) and found

numerous response differences between the sans serif and the serif typefaces while, in a similar

study, Rowe (1982) found very few differences. Although each of these studies was a worthy

initial effort, each study fails to investigate a sample of fonts that have a representative range of

design characteristics. These studies also fail to consider the full array of responses to fonts.

A second class of studies that can offer insight into the influence of typeface design

characteristics on consumer responses is the research on aesthetics. Perception-based theories

(such as Gestalt psychology) suggest that simple and harmonious designs will be liked more than

complex and disharmonious designs (Bornstein and D’Agostino 1992; Klinger and Greenwald

1994; Van den Bergh and Vrana 1998; Veryzer and Hutchinson 1998; Whitfield and Slater 1979;

Whittlesea 1993). Motivation-based theories suggest more elaborate designs will increase

arousal and lead to liking (∩-shape relationship, see Berlyne 1971; Hirschman 1980). Other

theories, such as prototypicality and conditioning, attempt to explain why some stimuli are more

pleasing than others, but develop no clear link between the design characteristics and responses

(Martindale 1988; Martindale and Moore 1988; Veryzer 1999; Veryzer and Hutchinson 1998;

Whitfield and Slater 1979, 1983). Purely empirical work on logo design indicates a linear

positive relationship between a harmonious design and a pleasingness response and an ∩-shape

relationship between an elaborate design and a pleasingness response (Henderson and Cote

1998). Henderson and Cote (1998) also found a positive relationship between natural designs

and liking, but they present no theory to explain this link nor do they address dimensions of

response other than pleasingness and liking. In summary, theory and prior research provide

insufficient guidance for managing the range of impressions influenced by typeface design.

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Responses to Typeface Characteristics

In determining impressions created by typeface design, we first consider what constitutes a

response. From a purely empirical standpoint, the design literature has documented a wide

variety of responses to art and design (e.g., honest, distinctive, happy, warm, graceful, beautiful,

masculine, powerful, interesting, intense, emotional, etc., see Craig 1980; Ernst 1977; Rowe

1982; Solomon 1991; Tantillo, DiLorenzo-Aiss, and Mathisen 1995). More broadly, we

consider what might drive response. First, design adds meaning to the stimulus (beyond simply

the depiction of letters). In their seminal research on rating the meaning of concepts, Osgood,

Suci, and Tannenbaum (1957) conclude that responses could be accounted for by three

underlying dimensions: evaluation (e.g., good, pleasant, beautiful); activation (e.g., hot, active,

fast); and potency (e.g., strong, brave, rugged). Design also conveys emotion. Mehrabian and

Russell (1974) have shown that basic emotions or affective responses are captured by three

dimensions: pleasingness (e.g., pleased, contented, relaxed); arousal (e.g., excited, aroused,

jittery); and dominance (e.g., important, influential, controlling). Finally, in the context of a

corporation, design communicates something about the company. As such, we turn to the

spokesperson literature. Much as a spokesperson “dresses-up” the advertiser’s spoken words, so

typeface design “dresses-up” the written word. Spokesperson research has involved

conceptualizing and measuring responses to celebrity endorsers as three underlying dimensions:

attractiveness (e.g., elegant, beautiful, attractive); trustworthiness (e.g., honest, sincere,

dependable); and expertise (e.g., skilled, qualified, experienced, see Ohanian 1990).

There are noticeable similarities to the responses studied by Osgood, Suci, and Tannenbaum

(1957), Mehrabian and Russell (1974), and Ohanian (1990). Similarities are evident in the

evaluation/pleasingness/attractiveness dimensions, the activation/arousal dimensions, and the

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potency/dominance dimensions. In addition, the trustworthiness dimension is discussed in the

typology literature and is critical to spokesperson response and to businesses in general.

Expertise, on the other hand, seems irrelevant to typeface design.

Design Characteristics of Typeface

Typeface design can be distinguished by universal and typeface-specific characteristics.

Universal design characteristics are subjective descriptions of the typeface and include

characteristics such as symmetry, activity, and complexity. As such, universal design

characteristics are holistic descriptions that rely on perception and could be used to describe a

wide variety of stimuli. Typeface-specific design characteristics are graphemic descriptions of

the fonts and include characteristics such as short/tall, serif/sans serif, and condensed/extended.

Typeface-specific characteristics are not as subjective and provide an opportunity to explain

additional variance in responses specific to typeface design. In effect, examining universal

characteristics allows for greater generalizability of findings, whereas examining typeface-

specific characteristics provides an opportunity to hypothesize about additional design factors

and/or engineer a typeface to meet specific goals.

Although there is no direct research on the universal characteristics of typeface design,

research on logo design has proposed three universal dimensions; elaborateness (complex,

active, and depth), naturalness (representative and organic), and harmony (balance & symmetry,

see Henderson and Cote 1998; Henderson et al. 2003). These dimensions may or may not hold

for typeface. There is no research that indicates the dimensionality of typeface-specific

characteristics. It is also difficult to anticipate whether typeface-specific dimensions will, or will

not, be independent of universal design dimensions. On the one hand, typeface-specific

characteristics, such as serifs and ascenders, appear to be so specific to type since they do not

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clearly relate to one of the universal dimensions. On the other hand, some typeface-specific

characteristics, such as handwritten versus typed, appear to relate to universal dimensions found

for logos, such as the naturalness dimension. Unfortunately, neither empirical nor theoretical

information regarding typeface characteristics is sufficient to provide much guidance on

dimensionality.

Goal of Research

Our review of the design literature suggests that there are no meaningful guidelines for typeface

design. The lack of guidelines may lead to designs that do not achieve corporate objectives. For

example, reports on corporations changing their logotypes typically discuss the image

management hopes to communicate through the new typeface (Spaeth 1994; 1999; 1995). Yet,

the implicit assumption of a single response to a logotype is probably incorrect. It is more likely

that there are multiple responses to a logotype and that the corporation must consider tradeoffs

among responses when developing its communication goals. Thus, guidelines are needed to

assist corporations in managing the range of impressions created through their choices. In order

to develop meaningful guidelines for selecting fonts, we conducted an empirical investigation to

determine the design dimensions that best capture differences among typefaces, the response

dimensions typefaces generate, and how typeface design dimensions relate to response

dimensions. Based on the empirical findings, we then provide guidelines for corporations when

selecting typeface.

Research Method

Data collection required four stages. First, appropriate typeface design characteristics were

identified and a sample of representative typefaces selected. Next, typefaces were rated on the

selected design characteristics by professional graphic designers and advertisers. A list of

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strategically relevant impressions was then identified. Lastly, consumers responded to the

typefaces on those impression measures.

Phase 1: Selection of Design Characteristics and Typefaces

As noted earlier, universal design dimensions, such as natural, harmony, and elaborate, should be

relevant for all types of stimuli. These universal dimensions may be captured by either universal

design variables (e.g., the symmetry variable loads onto the harmony dimension for brand logos)

or typeface-specific variables (e.g., handwritten is more organic than machine-made type). In

addition, there are also likely to be design dimensions that are unique to the specific stimulus.

These typeface-specific dimensions can only be captured by typeface-specific variables.

In Phase 1, a list of universal and typeface-specific design characteristics was developed.

Design characteristics included in publications on typology were used to construct an initial list.

Next, five professional graphic designers from different firms that work with a wide range of

corporations were asked to list the primary characteristics that differentiate typeface design. The

final list consisted of 16 universal and eight typeface-specific design characteristics. Table 1

lists the typeface design characteristics and provides illustrative fonts.

------------------------------ Insert Table 1 about here ------------------------------

The five professional designers each provided an extensive list (40-150) of commercially

available typefaces representative of variation on the design characteristics they had identified.

To further broaden the range of typefaces, additional typeface software was purchased. Based on

this input, the researchers selected 210 typefaces. Typefaces were selected that represented the

full range for each of the 24 design characteristics (e.g., extremely complex typefaces to

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extremely simple typefaces) and had both an upper and lower case (some specialty typefaces

only have upper case). See Table 1 for examples of the design characteristics.

Phase 2: Ratings of Design Characteristics

Eighty-two professional graphic designers, working in agencies and corporations, rated the 210

typefaces on seven-point semantic differential scales for each of the 24 characteristics. To

minimize fatigue, each designer rated between 10 and 30 typefaces on 12 of the 24

characteristics. Typefaces were presented on white paper in 16-point font size in full alphabetic

(upper and lower case) and numeric forms. A paper-and-pencil method was used to ensure that

typefaces appeared true to form since computer and software differences across design agencies

pose difficulties in maintaining consistent typeface appearances for research purposes. In all,

17,683 individual ratings were obtained from professional designers.

Phase 3: Selection of Impression Responses

Because our goal is to provide guidance to corporations, we researched impressions that

corporations and designers seek to create through typeface. Managerially-oriented design

literature and input from five professional graphic designers revealed the responses thought to

result from typeface design and that are relevant to the general communication goals of

corporations. These impressions include innovative, calm, liking, interesting, formal, strong,

warm, honest, familiar, emotional, masculine/feminine, and attractive. To confirm the relevance

of these impressions, 35 additional professional designers rated their perceived ability to select

typefaces that elicited these responses. Results indicated that these designers believed that they

could select typefaces to create these impressions and that these impressions were meaningful to

them and their corporate clients.

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We purposely did not refer to scales found in the meaning (Osgood, Suci, and Tannenbaum

1957), emotion (Mehrabian and Russell 1974), or spokesperson (Ohanian 1990) literatures, as

we wanted the results of this study to address specific corporate goals. This approach provides a

stronger test of these dimensions of response in the context of type than if we had used scales

from these studies. Still, there is enough similarity in the evaluations that meaningful

comparisons should be possible.

Phase 4: Ratings of Impressions Created by Typefaces

The next phase involved obtaining responses to the typefaces. Because of the enormity of

gathering a large sample of evaluations of 210 typefaces on each of the 12 response variables, a

laboratory-based computer task was used. The computer display of each typeface was visually

examined and measured to guarantee that the appearance, size, and resolution was the same on

the monitor as on the printed pages to which graphic designers responded. One typeface was

dropped because its appearance on the computer was slightly different than its appearance in

print. Software was written to randomly select 20 typefaces to present to the respondents. Each

typeface was presented individually as a complete alphabet and number set accompanied by six

of the 12 seven-point semantic differential scales (e.g., like/dislike; strong/delicate; etc.). The

participants controlled the speed of typeface viewing and responding. Over 60,000 response

ratings from 336 upper-division students at a large university were obtained with an average of

24.3 responses per typeface. The use of students in design research has been repeatedly justified

by findings that show a surprising consistency in aesthetic response across age groups (Berlyne

1971; Eysenck 1988).

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Analysis and Results

The data were analyzed with the approach used in experimental aesthetics as well as in research

on language processing [e.g., \Berlyne, 1974 #409;Bradshaw, 1984 #472]. Analyses were

conducted at the stimulus- rather than the individual-level. This requires averaging across

individual ratings of a stimulus (typeface) on a particular characteristic or impression response to

obtain a score for that stimulus on that variable. All remaining analyses were conducted using

these stimulus scores. Thus, the unit of analysis is the typeface, and the sample size for each

analysis is the number of typefaces (209). This approach is particularly appropriate for

marketing management because it recognizes that stimuli are designed for, managed for, and

responded to by groups of people rather than individuals.

The variables used in the analyses were 23 averaged design characteristics and the 12

averaged responses. We dropped one of the original 24 design characteristics (frequency of use)

because we concluded that it did not reflect design, but instead reflected designers’ behavior.

What are the Strategically Relevant Response Dimensions?

Consistent with Henderson and Cote (1998), we started by conducting an exploratory factor

analysis (EFA) of the impressions data. The analysis produced three factors. However, one

factor included positive loadings for interesting, emotional, and innovative; and negative

loadings for calm, formal, honest, and familiar. This factor was cumbersome to interpret since it

combined the activation/arousal dimension (Mehrabian and Russell 1974; Osgood, Suci, and

Tannenbaum 1957) with a variant of the trustworthy response dimension suggested by the

spokesperson literature. An attempt to replicate the exploratory factor results using confirmatory

factor analysis (CFA) indicated the problems with the EFA factor structure (CFI = .658, and low

loadings for emotional and interesting). The CFA was respecified to include four factors, which

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roughly corresponded to the evaluation/pleasingness/attractiveness, activation/arousal,

potency/dominance, and trustworthiness dimensions found in previous research on emotions,

evaluations of objects, and spokesperson perceptions (see Table 2). The model fit the data

reasonably well (CFI = .806) and all the loadings were quite high (λ > .7, with the exception of

strong/delicate). The correlations among the impression factors were modest but significant (see

Table 3). In addition, half the correlations were negative, indicating an implicit tradeoff between

impression responses.

Based on these results, four dimensions were used to describe the impression variables.

Pleasing/Displeasing was comprised of liked, warm and attractive. Engaging/Boring was

comprised of interesting and emotional. Reassuring/Unsettling consisted of calm, formal,

honest, familiar and a negative loading for innovative (whose opposite endpoint was

mainstream). Finally, Prominent/Subtle included strong (whose opposite endpoint was delicate)

and masculine. Summated scores were used to capture each of the dimensions.


What Dimensions Best Capture Typeface Design?

As described earlier, the design characteristics consisted of universal and typeface-specific

characteristics. Universal characteristics included distinctive, ornate, special use, conveys

meaning, depth, uniform, balanced, smooth, symmetric, curved, organic, slanted, active, readable

(which is known to capture simplicity in type) and handwritten/typed (which indicates natural

versus man-made in type). Typeface specific characteristics included serif, ascenders,

descenders, heavy, repeat, fat, condense, and x-height. These two groups of characteristics were

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analyzed separately to ensure that generalizable dimensions were identified and linked to

responses so as to better advance design research across stimuli.

Exploratory factor analyses were performed using principal component analysis with

varimax rotation. The factor analysis of the universal characteristics revealed three design

dimensions, which explained 69.7 % of the variance (see Table 3). The first factor,

Elaborateness, included ornate, depth, distinctive, meaningful, and negative loadings for

readable and common (versus special purpose) use. The second factor, Harmony, included

balance, smoothness, symmetry, and uniformity. The third factor, Naturalness, included active,

curved, organic, slant, and a negative loading for looks-typed (as opposed to handwritten). These

results are very similar to Henderson and Cote’s (1998) findings, albeit using different design

characteristics specified by practitioners. A CFA confirmed the appropriateness of this factor

structure (CFI = .858). However, subsequent analyses used the EFA results since orthogonal

factor scores could be created for examining the relationship between design and response.

Factor analysis of the typeface-specific variables also uncovered three dimensions which

explained 60.4% of the variance (see Table 3). Flourish is comprised of serif, ascenders, and

descenders. It might appear that flourish and elaborate would tap the same dimension.

However, they were only correlated at .183. Weight is comprised of heavy, fat, and repeated

elements. Finally, Compressed is comprised of condensed and x-height. Again, a CFA

confirmed the appropriateness of the factor structure (CFI = .862), and the EFA factor scores

were used for the regression analyses.


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How do Design Characteristics Influence Responses to Fonts?

Four separate regression analyses were conducted using pleasing, engaging, reassuring, and

prominent as the dependent variables. The three universal design dimensions (elaborateness,

naturalness, and harmony) and the three font-specific design dimensions (flourish, weight, and

compressed) were used as predictors. First, all the design dimensions were included in the

model. We then added non-linear relationships using stepwise regression. We also tested for

interactions amongst the design dimensions, but none were significant. Overall, the design

dimensions were strongly related to the impressions created by typeface. Explained variance

was particularly high (adjusted R2 from .514 to .734). In addition, both universal and typeface-

specific design dimensions influenced response; however, the universal dimensions consistently

explained more variance. A summary of the regression results is presented in Table 4.


Pleasing/Displeasing. The design dimensions explained 51.4% of the variance in the

pleasing/displeasing response factor. Elaborate, harmony, natural, flourish and compressed all

had significant impacts. Natural had the largest impact (∆R2 = .320) creating more pleasing

fonts, with the effect leveling off at high values. Elaborateness explained 7.9% of the variance

and had a negative impact on pleasingness. Harmony, flourish, and compressed all had modest

effects (∆R2 = .045, .039, and .031 respectively). Harmony and flourish both increased

pleasingness (harmony had slight non-linearity in the nature of the positive relationship). A

curvilinear relationship indicated that moderate values of compressed created the most pleasing

fonts.

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Engaging/Boring. Design explained a large portion of the variance (68.0%) in the

engaging/boring dimension of response. Natural and elaborate had the largest effects (∆R2 =

.268 and .211 respectively) with higher levels of natural and elaborate creating more engaging

typefaces. Harmony was also important and created less engaging fonts (∆R2 = .170), with this

effect diminishing at higher levels of harmony. Compressed and flourish had nominal effects

(∆R2 = .018 and .013 respectively); and both increased the engagingness of the font.

Reassuring/Unsettling. The design elements explained 73.4% of the variance in the

reassuring/unsettling response dimension. Harmony and elaborate had the most influence

explaining 38.5% and 33.0% of the variance respectively. Harmony made fonts more reassuring

while elaborateness made them more unsettling. Flourish explained a nominal amount of

variance (∆R2 = .018) and made fonts more reassuring.

Prominent/Subtle. Natural, weight, flourish and harmony explained 52.8% of the variance in

the prominent/subtle response factor. Natural explained the most variance (∆R2 = .291) with

more natural fonts being perceived as less prominent and more subtle. Weight increased

perceptions of prominence and explained 17.1% of the variance. Flourish and harmony created

less prominent designs, explaining 4.3% and 2.4% of the variance respectively.

Developing Guidelines

In addition to conducting regression analyses to assist in developing guidelines for corporations’

use of typefaces, we conducted a cluster analysis to assess tradeoffs. The focus of the cluster

analysis was on identifying response profiles that could be achieved through a range of

commercially available fonts. The response clusters were built using the 12 raw response

variables, rather than the factors, so as to not lose any richness in the data. The number of

clusters was determined by looking at the average distance between clusters and comparing this

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to the within-cluster distances. In addition, we avoided creating clusters with too few fonts. Six

clusters appeared to best describe the data. While creating additional clusters reduced the

distance values within clusters, cluster sizes became very small. The results and discussion of

the cluster analysis, as well as an extended discussion of guidelines for impression management

through typeface usage, are presented in the next section.

Guidelines for Impression Management

Before examining specific guidelines for selecting typeface, a number of general conclusions are

supported by our analysis. The results provide broad empirical support for the contention by

CEOs, corporate identity analysts, and creative agencies that typefaces convey a variety of

strategically important impressions (Dolen 1984; Hutton 1997; Somerick 2000; Spaeth 1995).

Just as a spokesperson projects an image of the company, typeface appears to have the potential

to influence the impressions created by corporate communications. In addition, the strength of

the relationship between typeface design and the resulting impressions (adjusted R2 from .514 to

.734) suggests that corporations can have significant control over the resulting impressions (all

content issues being equal). Since type is inherent to most corporate communications,

companies can cost effectively leverage the benefits of an appropriately designed typeface.

Our findings further reveal that corporations should take into consideration all four responses

that their typefaces create. Thus, typeface should be carefully selected to ensure consistency

with other elements of the corporate identity strategy. For example, Hilton’s original logomark

was redesigned using a “script look” to make it more friendly (Spaeth 1999).

from to

Our results show that natural, “scripted” typefaces produce more reassuring and pleasing

fonts. However, Hilton’s new font is only average on elaborateness and harmony. The

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combined result is a font that is less prominent, (more subtle), and only moderately engaging.

Simply changing to a “script look” in an attempt to make a friendlier impression had a more

complex effect in that a combination of responses (pleasing, less prominent, and only moderately

engaging) resulted. Focusing only on a single response may lead to unintended consequences in

the other types of response. Firms must recognize the implications of design for all responses,

since multiple responses may be elicited.

Not only must firms attend to the breadth of impressions resulting from their font selections,

they will, in many cases, need to make some tradeoffs with respect to the responses sought.

Ideally, corporations would be able to create any combination of the above impressions.

However, since the design factors have different effects on impressions, a practitioner’s ability to

create high values on all four response dimensions is limited. Specifically, elaborate designs

increase how engaging the design is, but decrease how pleasing and reassuring it is. Harmony

increases pleasing and reassuring responses, but decreases engaging and prominence responses.

Lastly, natural designs are pleasing and engaging, but less prominent. As such, some tradeoff

between responses appears to be necessary. To illustrate, the change in the Citibank logo might

achieve their goal of being “. . .softer, less aggressive, and cozier (Spaeth 1999)" but may also be

too uninteresting (i.e., too low on the engaging dimension) and less pleasing.

from to

A similar font used in our study, corporate mono, is reassuring, but below average in

pleasing, low in engaging, and average in prominence.

Common Response Combinations

We draw on the cluster analysis results to illustrate the tradeoffs. Among the wide range of

commercially available fonts in this study, we found six general profiles (see Table 5).

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The first cluster comprises pleasing, subtle (not prominent), and engaging fonts that were

average on the reassuring dimension. These are liked, warm, attractive, interesting, emotional,

feminine, and delicate (Scheherezade). The means on design dimensions for this cluster

confirm predictions from the regression results. Namely, fonts that evoke these responses will be

high in harmony and flourish and low in weight. A good example is Anglewizard Films (see

Table 5).

The second group is comprised of unsettling but engaging fonts. These fonts are interesting,

emotional, exciting, informal, dishonest, unfamiliar, and innovative (Paintbrush). While most

companies would not want to be referred to as unsettling (not reassuring), these fonts

communicate an edginess that is of value in many communication efforts. For example,

Terrwear.com (see Table 5) produced clothing for mountain biking. Again the design dimension

means for this cluster confirm the regression analysis predictions that fonts that evoke these

responses are natural, somewhat elaborate and lack harmony.

The next cluster of fonts is unlikely to be used heavily by corporations. These fonts are

displeasing and unengaging (i.e., boring) but are average on the reassuring and prominence

dimensions. They are disliked, cold, unattractive, uninteresting and unemotional (Chainlink).

The cluster means confirmed regression analysis predictions that these fonts would be unnatural,

low on compressed, and have little flourish. Even the tradeoffs predicted by the regression

(elaborate designs are displeasing but engaging, and harmony creates boring but pleasing fonts)

were consistent with the cluster results. Although their use in marketing will be limited, there

may be some communication situations where a font such as this would be used; for example, to

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display the characteristics or claims of a competing brand or in non-profit advertising to describe

undesirable behaviors (e.g., antismoking advertisements). However, some companies may want

to produce this type of displeasing image. For example, Cleopatra Records (see Table 5)

produces albums such as Zeromancer’s “Clone Your Lover,” and “This is Neo–Goth.”

The fourth profile of fonts is prominent while being average on pleasing, engaging, and

reassuring. These fonts are masculine and strong and are characterized by designs with weighty

lines (NewYorkDeco). They may also have some elaborateness. It appears that any font

can be made to fit this category simply by making it thicker. For example, Canon (see Table 5)

uses a fairly simple font with thick lines. Again the regression results would predict fonts are

made more prominent by increasing weight (although the regression results suggest these fonts

should be less natural and have less flourish than was found with the cluster analysis).

The fifth cluster of fonts is low in reassuring (i.e., unsettling), displeasing, and yet engaging

while average on the prominent dimension. These fonts will be interesting, emotional, exciting,

informal, dishonest, unfamiliar, innovative, cold, disliked and unattractive (AluminumShred).

Consistent with the regression results, these responses are created by designs low in harmony,

below average in naturalness, and above average in elaborateness. Like cluster three, these are

fonts that are unlikely to be used heavily by corporations unless they want to convey negative

information (e.g., fear appeal ad) or are targeting a niche market. For example, Abominable

Records (see Table 5) carries bands like Helicopterejectionseat which plays, "an eclectic species

of mathematical rock and/or roll.”

The final profile is highly reassuring, but low in engaging (i.e., boring). It comprises fonts

that are average on pleasing and prominent. This cluster contains many common, highly

readable fonts (Georgia). Consistent with regression results, they are low on elaborateness and

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high on harmony. Such fonts are commonly used in the content of print ads as well as by

“stalwarts of the community.” Just looking at the logotype of Mark Rushing & Associates (see

Table 5) conveys this reassuring impression.

The cluster analysis results provide evidence of the tradeoffs necessary when selecting fonts

commercially available fonts. Yet, further examination of the regression results reveals that new

fonts can be created to achieve additional arrays of response profiles. The regression results

provide guidance to corporations for enlisting graphic designers to modify existing fonts or

create new, corporation-specific fonts, rather than using commercially available fonts that may

limit the combination of impressions created. Following are guidelines for creating response

arrays beyond those described above.

Designing Corporation-Specific Fonts

Several strategically attractive response profile options emerge from examining the regression

analyses.

Pleasing, Engaging and Prominent Fonts (average on reassuring) - This combination is very

similar to Cluster 1 except it is prominent rather than subtle. As noted earlier, simply making the

lines thicker can make any font more prominent. For example, Fluf is a much more prominent

font than the similar Kidstuff. Disney (see Table 5) uses this strategy to create a more prominent

looking logotype than is common for cluster 1 designs.

Pleasing, Reassuring and Prominent Fonts (average on engaging) - Creating pleasing and

reassuring fonts should be fairly easy since no tradeoff is required. Pleasing fonts are natural and

simple while reassuring fonts are harmonious and simple. In addition, while harmony does not

have a large effect on pleasingness, it tends to be positive. The same is true for the effect of

naturalness on reassuringness. Thus, pleasing, reassuring fonts can be created through with

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natural, simple, harmonious designs. These fonts can be made more prominent simply by

making the lines thicker (which does not affect evaluations of pleasing or reassuring).

Surprisingly, none of the fonts in our sample had the design characteristics needed to create

pleasing and reassuring fonts. All the fonts that were high in both naturalness and harmony were

also very elaborate. The closest example to the desired font was Hamburger which was high in

naturalness but only average in harmony and was slightly below average in elaborateness.

Hallmark (see Table 5) is a good example of this type of design.

Pleasing, Reassuring and Subtle Fonts (average on the engaging) - As noted above,

creating pleasing and reassuring fonts is fairly easy. To also make them subtle, lines should be

thin and natural. There was no example of this type of font in our sample, and it was extremely

difficult to find a corporate example. However, Imagination Web Design (see Table 5) provides

a good example.

Combining Fonts - A final option is to combine fonts with different response profiles to

create a hybrid response. For example, first initials and delimiters might be used to create a

sense of pleasingness and subtlety. This could be followed by generic fonts to create a

reassuring impression. Elkins and Associates1 provides a good example of just this strategy.

Similar approaches might be used to grab attention, through engaging first initials, without

making the typeface overly unpleasant.

Creating Differentiation through Typeface Design

The nine design profiles of typefaces, along with the added possibility of combining fonts from

different profiles, provide corporations with great flexibility in achieving communication goals

and creating differentiated marketing materials. Even greater flexibility and creativity is

1

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afforded corporations in that they may achieve the described design dimensions by manipulating

any of the design characteristics underlying those dimensions. For example, if a corporation

chooses to use a natural design in order to communicate a pleasing, subtle image; a typeface may

be chosen or created that emphasizes any one of several aspects of naturalness, such as it looks-

handwritten, exhibits curvature, or is slanted. The typeface need not have all characteristics of

naturalness to be high on this dimension.

Thus, rather than constrain a corporation in its use of typeface, the guidelines serve to direct

the already extensive work that goes into selecting, modifying, and using typefaces towards

accomplishing the goals corporations state they desire. In addition, by simplifying the myriad of

characteristics graphic designers consider into six design dimensions, by simplifying the

numerous impressions corporations desire into four response dimensions, and by combining

these into nine broad typeface profiles, these guidelines should serve to improve the

communication of corporate and brand image goals between executives and their creative

partners.

Finally, the guidelines should improve a corporation’s ability to distinguish themselves in

meaningful ways from the communications of their competitors. Without guidance on the design

dimensions and profiles that distinguish typefaces, it would be difficult to determine whether a

selected font differentiates the firm from competitors or conveys an identical response profile.

These guidelines should provide greater insight to both designers and corporations in the audits

they regularly conduct of their competition’s communication materials.

Creating Integrated Communication Campaigns

The guidelines are useful in creating any type of marketing communication that uses print. In

addition, these guidelines should assist corporations in creating and integrating their entire

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portfolio of communications that use the written word. Corporations are increasingly sensitive to

integrating communications across a wide variety of media. Our findings suggest that typeface

is a medium with its own message. This makes it critical that the font’s message/impression be

chosen carefully and held consistent across the wide variety of communications in which a

corporation engages. In some cases, the firm’s preferred font may not be appropriate for a

particular medium, e.g., a billboard, or a web page. By following the guidelines provided,

corporations can choose alternative fonts that still have the same response profile. This will

increase their flexibility while simultaneously increasing the consistency in the messages they

are communicating. While this would not be appropriate for a brand logo which must appear the

same in all communications, it is appropriate for other forms of written communication a

corporation generates.

Future Research

While this study has sought to provide corporations with guidelines for managing impressions

created by their designed materials, more research is needed in the area of design, in general, and

typeface, in particular. Fundamentally, research is needed to determine if people have an innate,

“hardwired” inclination to respond to design based on daily interactions with the natural world

(Colarelli and Dettmann 2003). This research should focus on the consistency with which

people respond to design elements across a range of stimuli and purposes. Another productive

area for future research is in examining design characteristics and their influence on perception

and information processing; e.g., Do elaborate fonts attract greater attention?; Do elaborate fonts

increase cognitive load and require greater processing time?. In addition, future research should

establish baseline or control responses in order to assess whether typeface design enhances or

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undermines impressions, as well as to determine the degree to which design can hurt or help

achieve desired responses.

It is important to determine the impact of the impressions created by typeface on other

responses of interest to corporations such as brand attitudes, customer retention, click-through

behaviors on web sites, purchase behavior, and corporate identity. Initial research indicates that

typeface affects important responses to advertising (e.g., Childers and Jass 2002; McCarthy and

Mothersbaugh 2002). More research is needed to determine the extent of impression transfer

from typeface to the brand and company itself, as well as its impact on the variety of responses

and behaviors studied in marketing.

Another avenue of research will be to explore the extent to which responses to typeface and

other designed stimuli vary across individuals. The approach taken in the current paper was a

stimulus-level analysis which is particularly appropriate in marketing where efforts are directed

at entire segments of consumers. Still, research indicates that individual differences can impact

attentiveness to aesthetics (Bloch, Brunel, and Arnold 2003). In addition, there may be

differences across nations as some countries write using symbols or characters opposed to an

alphabet, which may impact perceptions of letters in alphabetic name brands (Pan and Schmitt

1996). Interestingly, research indicates that perceptions of logos are fairly similar between the

U.S. and Asia (Henderson et al. 2003) , but it is unclear if this will hold with typeface.

Research is also needed to determine the public policy implications of typeface selection.

For example, typeface selection is of special concern in providing information to the elderly.

While the focus is typically on readability for the elderly, variables such as engagingness may

weigh heavily in the extent to which warning labels are read.

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More generally, research is needed on the relationship between design and response for other

design objects. Empirically-based guidelines are needed to help corporations manage, in a more

informed and strategic fashion, their entire design portfolio including products, advertisements,

packaging, websites, signage and physical design such as retail outlets. The present research and

previous research on logos (Henderson and Cote 1998) suggests there may be universal design

dimensions that are generalizable across stimuli. In addition, the responses to these designs may

also be relatively universal and generalizable. As such, the beginning elements of examining

design impact for other classes of design stimuli and assessing the further impact of design on a

wider variety of responses, may be identified. Such research can only help to improve the

profitability of design for corporations while providing the basis for a more universal theory of

design.

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TABLE 1 Examples of Design Characteristics

Design Characteristic High Low Universal - Specifc

Design Factor

Ornate vs. Plain ABCYabcy ABCYabcy Univeral Elaborate Special Use vs Common Use ABCYabcy ABCYabcy Specific Elaborate Depth vs. Flat ABCYabcy ABCYabcy Univeral Elaborate Distinctive vs. Not Distinctive ABCYabcy ABCYabcy Univeral Elaborate Conveys Meaning-Does Not Convey Meaning ABCYabcy ABCYabcy Univeral Elaborate

Readable vs. Not Readable ABCYabcy ABCYabcy Specific Elaborate Balanced vs. Unbalanced ABCYabcy ABCYabcy Univeral Harmony Smooth vs. Rough TUVltuvç ABCYabcy Univeral Harmony Symmetric vs. Asymmetric ABCYabcy ABCYabcy Univeral Harmony Uniform vs. Not Uniform ABCYabcy ABCYabcy Univeral Harmony Organic vs. Geometric2 ABCYabcy ABCYabcy Univeral Natural Looks Typed vs. Looks Handwritten ABCYabcy ABCYabcy Specific Natural

Active vs. Passive ABCYabcy ABCYabcy Univeral Natural Slanted vs. Straight ABCYabcy ABCYabcy Univeral Natural Curved vs. Angular ABCYabcy ABCYabcy Univeral Natural Heavy vs. Light ABCYabcy ABCYabcy Specific Weight Short and Fat vs. Tall and Thin ABCYabcy ABCYabcy Specific Weight Repeated vs. no Repeated Elements ABCYabcy ABCYabcy Specific Weight

Serif vs. Sans Serif ABCYabcy ABCYabcy Specific Flourish Ascenders – Pronounced vs. Not Pronounced3 ABCYabcy ABCYyabcy Specific Flourish

Descenders – Pronounced vs. Not Pronounced ABCYabcy ABCYabcy Specific Flourish

Condensed vs. Extended4 ABCYabcy ABCYabcy Specific Compressed x height Tall vs Short5 ABCYabcyx ABCYabcyx Specific Compressed

The authors can provide a more complete set of examples including examples for the response variables.

2 Organic looks more irregular, unplanned or natural while geometric looks more like objects that are man-made,

planned, or measured. 3 Ascenders (descenders) are the parts of the letter that go above (below) the main body e.g., the top of a lower case

h (the tail of the lower case y). Pronounced ascenders (descenders) appear to go significantly above (below) the body of the letter or stand out in their influence on the appearance of the letter.

4 Condensed refers only to the width of the letter. Condensed letters are narrow while extended letters have a wider base.

5 x-height refers to the height of the lower-case x. Tall letters are letters whose tops are far above the height of the x. Short letters do not rise above the height of the x very far.

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TABLE 2 Confirmatory Factor Analysis of the Response Dimensions

Pleasing Engaging Reassuring ProminentLike-Dislike .834 Warm-Cold .838 Attractive-Unattractive .855 Interesting-Uninteresting .892 Emotional-Unemotional .886 Calm-Not Calm .919 Formal-Informal .880 Honest-Dishonest .921 Familiar-Unfamiliar .916 Innovative-Mainstream -.826 Strong-Delicate .591 Masculine-Feminine 1.000

Correlations among Response Dimensions

Pleasing Engaging Reassuring Prominent Pleasing 1 Engaging .341 1 Reassuring .607 -.589 1 Prominent -.543 -.578 .044 1

chi-square = 536.540 based on 48 degrees of freedom probability value for the chi-square statistic is less than .001 the normal theory rls chi-square for this ml solution is 447.318.

Bentler-Bonett normed fit index = .806 Bentler-Bonett nonnormed fit index = .751 comparative fit index (CFI) = .819

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TABLE 3 Exploratory Factor Analysis of the Design Dimensions

Elaborate Harmony Natural Flourish Weight CompressedDistinctive- Not Distinctive

.787 -.247 .132

Ornate-Plain .780 -.334 .244 Special Use- Common Use

-.720 .449 -.180

Readable-Not Readable -.711 .475 -.076 Conveys Meaning-Does Not Convey Meaning

.687 -.081 .296

Depth:Flat-Multidimensional .659 -.101 .208 Uniform-Not Uniform -.213 .816 -.257 Balanced-Unbalanced -.218 .759 -.277 Smooth-Rough -.371 .693 .135 Symmetric-Asymmetric -.406 .600 -.353 Curved-Angular .180 .313 .804 Organic-Geometric .243 -.373 .742 Slanted-Straight .116 -.215 .720 Looks Handwritten-Looks Typed

-.307 .431 -.718

Active-Passive .380 -.503 .615 Serif-Sans Serif .754 .158 .008 Ascenders :Pronounced-Not Pronounced

.720 -.226 .137

Descenders :Pronounced-Not Pronounced

.639 -.197 .156

Heavy-Light -.333 .771 .033 Repeated Elements- No Repeated Elements

.307 .705 -.180

Short and Fat-Tall and Thin -.382 .677 .397 Condensed-Extended .001 -.024 -.817 x-Height:Tall-Short .281 -.017 .583

Principal Component Analysis with Varimax Rotation Elaborate, Harmony, and Natural explained 69.7% of the variance in the perception design characteristics Flourish, Weight, and Compressed explained 60.4% of the variance in the quantifiable design characteristics

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TABLE 4 Summary of Regression Results

Design Elements

Direction of Effect Beta Coefficient

Size of Effect

(∆adjR2)

Total Adj R2

Natural positive, plateaus at high values .428 - .138N2 .320

Elaborate negative, linear -.275 .079

Harmony

.029 + .208H3 .045

Flourish positive, linear .209 .039

Pleasing

Compressed ∩ .118 – .128S2 .031

.514

Natural positive, linear .412 .268 Elaborate positive, linear .403 .211

Harmony negative at a decreasing rate -.361 + .0645H2 .170

Compressed positive, linear .153 .018

Engaging

Flourish positive, linear .126 .013

.680

Harmony positive, linear .586 .385 Elaborate negative, linear -.600 .330 Reassuring Flourish positive, linear .168 .018

.734

Natural increasingly negative -.436 – .150N2 .291 Weight positive, linear .329 .171 Flourish negative, linear -.220 .043 Prominent Harmony

.258 – .229H3 .024 .528

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TABLE 5 Cluster Analysis Results

Cluster Size Responses Level Design Level Fonts Examples

1 37

Pleasing Engaging Reassuring Prominent

High High Average Low

Elaborate Natural Harmony Flourish Compressed Weight

Average High Average High Average Low

Scheherezade Informal Roman AncientScript Enviro Pepita MT

2 37


Average High Low Average


Above Average High Low Average High Average

Baphomet Edda Chiller Stonehenge Paintbrush

3 21


Low Low Average Average


Above Average Low Average Below Average Low Above Average

Playbill Logan Onyx Industria Inline StencilSet

4 41


Average Average Average High


Above Average Average Average Average Average High

NewYorkDeco Bandstand

SunSplash Middle Ages Fisherman

5 19


Low High Low Average


Above Average Below Average Low Below Average Average Average

AluminumShred BigDaddy Integrity Ransom Amazon

6 54


Average Low High Average


Low Average High Average Average Average

Georgia Verdana Janson Text Century Gothic Times New Roman Century Schoolbook


High High Average High


Average High Average High Average High

Maiden Word Author 6 Viner Hand ITC


High Average High High


Low High High Average Average High

Hamburger


High Average High Low


Low High High Average Average Low

None in Dataset

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6 Author and Viner Hand ITC are presented in bold to make them more consistent with the design characteristics needed to create a prominence response.

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