Marketing Language: A Conceptual Framework and Examination of How Brand
Name Linguistics Influence Brand Loyalty
A dissertation submitted to the
Graduate School
of the University of Cincinnati
in partial fulfillment of the
requirements for the degree of
Doctor of Philosophy
in the Department of Marketing of the College of Business by
Ruth Pogacar
MBA University of Montana
May 2018
Committee Chair: Frank R. Kardes, Ph.D. 2
Abstract
People—be they politicians, marketers, job candidates, product reviewers, or romantic interests—often use linguistic devices to persuade others, and there is a sizeable literature that has documented the effects of numerous linguistic devices. However, understanding the implications of these effects is difficult without an organizing framework. To this end, I introduce a Language Complexity × Processing Mode Framework for classifying linguistic devices based on two continuous dimensions: language complexity, ranging from simple to complex, and processing mode, ranging from automatic to controlled. I then use the framework as a basis for reviewing and synthesizing extant research on the effects of the linguistic devices on persuasion, determining the conditions under which the effectiveness of the linguistic devices can be maximized, and reconciling inconsistencies in prior research.
Brand names can communicate brand gender, and feminine brand gender increases perceived warmth, which in turn increases brand loyalty. Therefore, longer names that end in a vowel (e.g.,
Burberry) sound both more feminine and more warm than shorter names that end in a consonant
(e.g., Ford). Using both experimental manipulation of hypothetical brands and observational analysis of real brands, this research shows that people feel more loyal toward brands with feminine names, predict that feminine sounding brands are more likely to be top performers than parallel masculine sounding names, and this expectation bears out in the marketplace, where top brands have more feminine names than less successful brands. A feminine brand name is even more beneficial for hedonic, relative to utilitarian, products. However, the advantage for feminine names is neutralized when the typical user of a product is male, and masculine brand names are preferred when warmth is not a desirable product attribute.
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Acknowledgements
I would like to thank my husband, Michal, whose encouragement, support, and occasional consultations make everything possible. I am very grateful to my chair, Frank Kardes, and my committee: Tina Lowrey, L. J. Shrum, James Kellaris, and Chung-Yiu (Peter) Chiu for their invaluable feedback. Thank you to Jakki Mohr and Mary Steffel for being generous and inspiring mentors. I am also fortunate to have met Emily Plant and Laura Felton Rosulek who introduced me to academic research (it was a lot of fun!), and Nora Williams and Tom Carpenter who model best practices and follow the highest standards for scientific inquiry. My experience in the
University of Cincinnati doctoral program was enriched in so many ways by the brilliant and witty faculty, including Karen Machleit, Dave Curry, and Chris Allen, and by Suzanne
Masterson’s dedication to training future scholars. This research, in particular, was improved by feedback from Justin Angle, Ryan Rahinel, Tony Salerno, Jorge Pena Marin, Esta Denton Shah,
Noah VanBergen, and Elliott Manzon. In drafting my dissertation, Laura Micciche’s writing workshop and expertise on the topic of acknowledgements were instrumental. I'm grateful to the editors of the Journal of Consumer Psychology for publishing a version of essay one, and the anonymous reviewers for their helpful suggestions. I would like to acknowledge the support of the University of Cincinnati Graduate School Dean’s Fellowship. Finally, I would like to thank my parents, Anesa and Tim, my sister Antonia, and most of all JoJo.
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Table of Contents
Essay 1: The Effects of Linguistic Devices on Consumer Information Processing and Persuasion:
A Language Complexity × Processing Mode Framework ------5
Essay 2: Is Nestle a Lady? Brand Name Linguistics Influence Perceived Gender, Warmth, and
Brand Loyalty ------67
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Essay 1
The Effects of Linguistic Devices on Consumer Information Processing and Persuasion:
A Language Complexity × Processing Mode Framework
Abstract
People—be they politicians, marketers, job candidates, product reviewers, or romantic interests—often use linguistic devices to persuade others, and there is a sizeable literature that has documented the effects of numerous linguistic devices. However, understanding the implications of these effects is difficult without an organizing framework. To this end, we introduce a Language Complexity × Processing Mode Framework for classifying linguistic devices based on two continuous dimensions: language complexity, ranging from simple to complex, and processing mode, ranging from automatic to controlled. We then use the framework as a basis for reviewing and synthesizing extant research on the effects of the linguistic devices on persuasion, determining the conditions under which the effectiveness of the linguistic devices can be maximized, and reconciling inconsistencies in prior research.
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Introduction
People use language to not only express ideas, but also to sell them. Communicators—be they marketers, politicians, job candidates, product reviewers, or romantic interests—carefully choose arguments that they believe will maximize the persuasive impact of their messages.
However, along with what is said (the content of the appeals), how it is said also makes a difference. In particular, communicators may use linguistic devices to make their claims more persuasive. For example, metaphors may be used to position a benefit in relation to something else, rhymes and alliteration may be used to enhance memory and ease of processing, rhetorical questions may be used to stimulate greater depth of processing, and phonetic symbolism may be used to frame expectations.
In fact, there is a sizeable and growing literature that attests to the effects of linguistic devices on persuasion (Lowrey, 2007). However, comprehending the implications of this research is difficult without an organizing framework. Not only are there many different types of linguistic devices that have been investigated, they often differ dramatically on a number of dimensions that have critical implications for their effectiveness, including underlying cognitive processes (automatic, controlled; depth of processing), type of response elicited (cognitive, affective), and effort.
The purpose of this review is to provide such a framework. We begin by developing a framework for classifying linguistic devices based on two continuous dimensions: language complexity, ranging from simple to complex, and processing mode, ranging from automatic to controlled. We then map the linguistic devices onto the four quadrants of the 2 × 2 matrix, and use the framework as a basis to review research on the effects of the linguistic devices, with a particular emphasis on the processes underlying the effects. Next, we discuss implications of the
8 framework for understanding the conditions that will maximize the persuasive effects of the devices. Following that, we use the model to account for seemingly contradictory findings regarding the effects of congruence between marketing or message elements and propose avenues for future research.
Language Complexity × Processing Mode Framework
Although there are undoubtedly many ways that linguistic devices might be categorized
(cf. Carnevale, Luna, & Lerman, 2017; McQuarrie & Mick, 1996), we focus on two dimensions: language complexity and processing mode. We chose these two dimensions because they relate directly to—and therefore facilitate understanding of—persuasion and its underlying processes, one of our primary objectives. Both language complexity and processing mode have critical implications for processes underlying persuasion, including typical components of hierarchy-of- effects models (attention, comprehension, attitudes, etc.; see McGuire, 1978), affective or cognitive processing, memory, and ease of processing, among others.
We conceptualize language complexity as a continuum from simple (e.g., individual sounds or words) to complex (e.g., phrases, sentences, paragraphs). For our purposes, the primary determinant of language complexity is the unit of language (e.g., phonemes, words, sentences). All else equal, the larger the language unit, the more complex the language. Further, language complexity has two components. The primary component is the linguistic device itself, and its unit of language. For example, brand names are for the most part simple, as they typically consist of only one or two words. However, brand names can nevertheless vary in complexity, within the simple category, as a function of such things as word length and number of syllables.
Some devices, such as alliteration, rhyme, and metaphors, may appear in multiple word brand names (simple), or in slogans and tag lines (moderately complex). Other devices, such as
9 syntactic complexity, necessarily appear in sentences or paragraphs, and thus are more complex.
A second component of language complexity is the marketing communication in which the linguistic device is typically embedded. For example, although speech rate and voice pitch are themselves simple devices that are independent of the unit of language (to some degree), they are invariably embedded in marketing communications that represent complex units of language
(multiple sentences). Thus, even though the marketing communication is not a characteristic of the linguistic device per se, for our purposes such devices are classified as complex.
We view processing mode in terms of the extent to which the processes are automatic or controlled. Automatic processing occurs when the presentation of a stimulus automatically activates related concepts stored in memory. More specifically, we adopt recent conceptualizations of automaticity as existing along a continuum (Moors, 2016), and automatic processes are ones that meet one or more of the following criteria: They are uncontrollable, occur outside of conscious awareness, occur at the earliest stages of information processing (e.g., perception), are effortless, and thus not affected by restrictions on cognitive capacity or motivation (i.e., load-independent; for reviews, see Bargh, 1989; Moors, 2016). The more criteria met, the more automatic the process. Controlled processes are typically viewed as the opposite of automatic processes: They are intentional, require attention, and are effortful, and thus are subject to cognitive capacity and motivational constraints. Unlike automatic processes, people are generally aware of the consequences or application of the controlled processing (although they may not always be accurate about them).
The next step in developing our framework is to identify a focal set of linguistic devices, and then categorize them based on the extent to which the language is simple or complex, and the extent to which the processing is automatic or controlled. Identifying the set of linguistic
10 devices to include in this review required some arbitrary choices in order to keep the size of the set manageable. First, we restricted the choice of linguistic devices to those that have received sufficient research attention to allow us to address both their effects and their underlying processes. Thus, some well-known linguistic devices that have been included in other reviews and frameworks (e.g., puns, irony, sarcasm; see McQuarrie & Mick, 1996), but have received relatively little if any empirical attention, are omitted. Second, we considered only devices that pertain to word or phrases themselves (i.e., phonetics, orthography, semantics, etc.), and omitted broader, message-based devices or strategies (e.g., one- vs. two-sided messages, message framing, humor, etc.).
We believe it is important to emphasize that the categorization of the devices as a function of complexity and processing mode is best viewed in terms of heuristic value, and is necessarily imprecise. We have categorized devices in terms of complexity and processing based on which categorization is most dominant. As noted, we view both dimensions as continuous.
Treating the dimensions as continuous allows us to map each linguistic device onto a two- dimensional space in which complexity is aligned along one (x-) axis and processing mode along the other (y-) axis. Each linguistic device is then placed in the two-dimensional space to reflect its relative degree of complexity or processing mode. This representation can be seen in Figure 1.
------Figure 1 about here------
The mapping of linguistic devices as a function of language complexity and processing mode allows for inferences regarding the amount of cognitive effort required. As Figure 1 shows, cognitive effort increases as a function of increases in both language complexity and controlled processing, and is represented by the diagonal arrow moving from bottom left to top right. The level of cognitive effort can be estimated by plotting a line from the linguistic device
11 perpendicular to the diagonal arrow indicating cognitive effort. The amount of cognitive effort has direct implications for the conditions under which the different linguistic devices will be effective in persuasion.
In the next sections, we review representative research for each linguistic device, organized by quadrant. The first sections begin with simple language devices, subcategorized by dominant processing mode, followed by complex language devices, also subcategorized by dominant processing mode.
Simple Language
Automatic Processing
Four linguistic devices fit the classification of simple language that is automatically processed: phonetic symbolism, numbers, sound repetition, and pronunciation. Although these devices share commonalities in terms of language complexity and processing mode, the actual underlying processes differ, as do the nature of the effects they produce. Table 1 provides a summary of the general findings for each device along with relevant citations.
------Table 1 about here------
Phonetic symbolism. Phonetic symbolism refers to a non-arbitrary relation between sound and meaning, and suggests that the sound of a word can convey meaning apart from its definition. The sounds of words derive from phonemes, which are the smallest units of sound
(e.g., the sound of the letter b in bat or the sound of the letter a in cat). Both vowel and consonant sounds are associated with a large array of sensory perceptions, including size, speed, weight, and color. For example, relative to back vowel sounds (lower pitch), front vowel sounds
(higher pitch) are associated with concepts such as harder, sharper, faster, smaller, lighter, psychologically closer, and more feminine. Back vowel sounds are correspondingly associated
12 with softer, duller, slower, larger, heavier, psychologically farther, and more masculine concepts.
Similarly, consonants such as fricatives (sounds formed via air friction through open articulators; e.g., s, f) are associated with the same perceptions as front vowel sounds. Conversely, plosives
(sounds formed via air stoppage by closed articulators; e.g., p, b) are associated with the same perceptions as back vowel sounds (French, 1977; Shrum & Lowrey, 2007; Spence, 2012).
Consumer research has applied these basic findings to marketing communications. For example, the sounds of brand names have been shown to relate to product perceptions (Klink,
2000), brand name preferences (Lowrey & Shrum, 2007; Shrum, Lowrey, Luna, Lerman, & Liu,
2011), product attitudes (Yorkston & Menon, 2004), product recommendations (Guèvremont &
Grohmann, 2015), and willingness to pay (Maglio, Rabaglia, Feder, Krehm, & Trope, 2014).
More specifically, across all of the research just noted, the effects on persuasion are more positive when the fit (congruence) between the sound-symbolic perceptions and expected or preferred attributes of the products is maximized.
Finally, although not precisely a phonetic effect, motor movements involved in word pronunciation also influence judgements (Topolinksi, Zürn, & Schneider, 2015). For example, consonant sequences can be structured such that the consonant sounds proceed from front to back (e.g., PADAK) or back to front (e.g., KADAP). The motor movements of a front-to-back
(inward) sequence mimic those of ingestion (which produces a positive feeling), whereas motor movements of a back-to-front (outward) sequence mimic those of expectoration (which produces a negative feeling; Kronrod, Lowrey, & Ackerman, 2014). Generally, consumers prefer inward brand names more than outward brand names, but like phonetic symbolism effects, preferences are more positive when there is a fit (congruence) between the oral motor movements and type of product (Topolinski, Boecker, Erie, Bakhtiari, & Pecher, 2017).
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Numbers. Numbers are similar to sounds in that they are fundamental building blocks that can evoke conceptual associations independent of their numerical meaning. For example, whereas numerical components of a brand name often convey objective information (V8, iPhone
6), in other cases the letter and number combinations may have no apparent meaning to consumers (WD-40). In such instances, consumers may use implicit or naïve theories about what the numbers imply to form judgements about the product. For example, alphanumeric brand names tend to automatically evoke associations with technology, and thus may be employed or avoided depending on the attributes to be emphasized (e.g., a car positioned on performance vs. comfort; Pavia & Costa, 1993). Similar attributions are made based on whether the number is in digital or written form or expressed as round numbers. Numbers in digital form are perceived to be more technological (Pavia & Costa, 1993), and round numbers are associated with greater product completeness (Gunasti & Ozcan, 2016; Yan & Pena-Marin, 2017) and femininity (Yan,
2016).
Similar to the associations that round numbers invoke, consumers may also make inferences based on the granularity of the number’s expression. Because finer-grained numbers are considered more precise, and message recipients infer that communicators use granularity to communicate precision, such things as repair estimates and durations are considered more accurate (and thus more preferred) when the granularity is higher (e.g., 30 days) than when it is lower (e.g., 1 mo.; Zhang & Schwarz, 2012). Granularity effects have also been observed in the use of integers (3) versus finer-grain decimals (2.4). Not only does the granularity of the number provide objective information, but changes from decimals to integers (and vice versa) also affect consumer perceptions. For example, changes from decimals to an integer are perceived as crossing a threshold, and thus a product’s ratings, attribute values, or version number that
14 changes from a decimal to an integer (e.g., 3.2 to 4) is evaluated more favorably than when the change is between two integers (e.g., 3 to 4), despite the fact that the latter difference is larger
(Shoham, Steinhart, & Moldovan, 2017).
Sound repetition. Sound repetition is multiple occurrences of the same sound in a word or phrase. One type of sound repetition is alliteration—the repetition of the first (or sometimes second) sound of a stressed syllable, usually a consonant, in a series of successive syllables or words. Alliteration can occur in brand names (e.g., PayPal), or longer word passages such as slogans and sentences (“Britain’s Best Business Bank”).
Alliteration has a number of beneficial effects. First, alliteration acts as a mnemonic and memory cue, and tends to be more effective than other memory cues such as imagery (Rubin,
1995). Second, alliteration also affects other consumer-related judgments. For example, products were evaluated more favorably when their brand names were alliterative than when they were not (e.g., Sepsop vs. Sepfut; Argo, Popa, & Smith, 2010), and this effect was mediated by affect, with alliteration producing more positive affect. Similarly, price promotions were evaluated more favorably when they were alliterative than when they were not (e.g., “3 Theybles $30” vs. “3
Theybles $29”; Davis, Bagchi, & Block, 2016), even though the non-alliterative promotion was objectively better. This effect was mediated by processing fluency. Alliterative promotions were easier to process, which presumably led to more positive evaluations.
Another example of sound repetition is rhyme, which is a repetition of the same or similar sounds in multiple words, usually in the final syllable. Like alliteration, rhyme can be found in brand names (7-Eleven) and slogans (“Don’t just book it. Thomas Cook it.”), and acts as a memory cue that can increase recall (Carr & Miles, 1997) and influence product evaluations, choice, and affect (Argo et al., 2010). Rhyme also influences perceptions of truthfulness. For
15 example, aphorisms that rhyme (e.g., “woes unite foes”) are judged to be more truthful than the semantically equivalent non-rhyming aphorism (e.g., “woes unite enemies;” McGlone &
Tofighbakhsh, 2000), and rhyming slogans are liked better, easier to remember, and more persuasive, and are also considered more original and more trustworthy, than equivalent non- rhyming slogans (Filkuková & Klempe, 2013).
Pronunciation. Ease of pronunciation can be manipulated by making words (brand names) easier or harder to pronounce, and ease of pronunciation is positively related to processing fluency (Schwarz, 2004). Research suggests that ease of processing influences perceptions of familiarity. Because things that are familiar are usually easier to process, people assume, often erroneously, that things that are easier to process are more familiar (Schwarz,
2004). In turn, familiarity influences other judgments, including perceptions of risk, novelty, and liking. For example, food additives and carnival rides whose names were difficult to pronounce were judged more harmful or risky than when the names were easy to pronounce (Song &
Schwarz, 2009). However, disfluency can also lead to favorable outcomes, depending on the attributions that arise from processing fluency. Because familiarity is also related to novelty (less familiar is more novel), the same carnival rides that were judged to be more harmful when the names were harder to pronounce were also considered more exciting.
Familiarity (via processing fluency) also affects liking. Things that are more familiar are generally liked better (Zajonc, 1968). Consequently, people with easier-to-pronounce names are better-liked than those with difficult-to-pronounce names (Laham, Koval, & Alter, 2012).
Complexity and processing mode. We have classified the preceding four linguistic devices in the categories of simple and automatic. In terms of complexity, the devices are confined primarily to one or two words (e.g., brand names, names of ingredients) or short
16 phrases (e.g., slogans), and thus fall at the more extreme simple end of the complexity continuum. However, as noted earlier, even though each of the devices themselves are low in complexity, their complexity also depends on the context in which they are used. For example, alphanumeric brand names are at the very simple end of the continuum. However, in some situations numbers may be used in more complex communications (e.g., terms of a warranty, repair time, negotiations, etc.). Thus, complexity is also a function of the mode of communication. Given this range, we have classified numbers as more complex than the other three devices, but still within the simple language category.
In terms of processing mode, although we have placed the four devices in the category of automatic processing, they differ in terms of where they fall along the continuum. For example, research clearly indicates that the effects of phonetic symbolism occur automatically: they occur very rapidly, outside of conscious awareness, are uncontrollable, and load-independent (cf.
Baxter, Kulczynski, & Ilicic, 2014; Coulter & Coulter, 2010; Parise & Spence, 2012; Yorkston &
Menon, 2004). Thus, phonetic symbolism meets all of the criteria for automaticity. Sound repetition and ease of pronunciation effects also occur relatively automatically. Even though people are aware of the prime (they are aware of the rhyme, alliteration, or pronunciation ease), they are usually unaware of the influence of these phenomena on their judgments.
Numbers also tend to be processed relatively automatically, but the degree of automaticity may vary across situations. For example, consumers may not be aware that they associate round numbers with completeness, or that this perception influences judgments such as likelihood to close a deal in negotiations (Yan & Pena-Marin, 2017). In such cases, the level of automaticity may be similar to levels for phonetic symbolism, sound repetition, and pronunciation. However, in other instances, the process of using numerical associations to make
17 judgments may be more controlled. For example, consumers are generally aware of the connotations of alphanumeric brand names with respect to technology (Pavia & Costa, 1993), and also likely aware of the possible influence of alphanumerics on judgments such as attitudes and preferences, which suggests that the process may be a conscious one. Thus, the extent to which the associations are applied to judgments depends on the conditions under which they are processed. Higher levels of involvement may result in a more elaborative, controlled process
(Petty & Cacioppo, 1986), and thus consumers may be more likely to consider the implications of the numeric component, such as the relation between the brand and the implied attributes. In contrast, when involvement is low, consumers may use a heuristic decision process (“higher number is better” heuristic) that automatically associates the number with expected associations
(Gunasti & Ross, 2010).
Effects of numerical granularity also result from slightly more controlled processes
(Zhang & Schwarz, 2012). The effects of granularity described earlier are couched in terms of
Grice’s (1975) logic of conversation, in which recipients expect information to be truthful, relevant, understandable, and provide only the amount of detail that is needed. Thus, message recipients infer that a higher-grained numerical expression is intended to convey more precision than a lower-grained one. However, this effect is attenuated if the source is not considered trustworthy (violating one of Grice’s maxims). In this case, consumers presumably make inferences based on granularity and make conscious decisions to use the implications as a basis for judgment.
In sum, across various situations, numbers tend to be processed relatively automatically, but meet fewer of the criteria for automaticity than the other three linguistic devices. Thus, we have classified them as less automatic (more controlled) along the processing mode continuum
18
(see Figure 1).
Controlled Processing
Three linguistic devices fit the classification of simple language that is processed in a more controlled manner: semantic appositeness, word familiarity, and unusual spelling (see Table
2). These devices are typically used in the context of brand names, but evoke different types of cognitions, which has implications for the ways in which the effects are applied.
------Table 2 about here------
Semantic appositeness. In marketing contexts, semantic appositeness refers to the extent to which a brand name conveys meaningful information about a product’s functions or attributes
(Anandan, 2009), such as Lean Cuisine or Land Rover, and is considered one criteria for a good brand name (Keller, Aperia, & Georgson, 2012). Semantic appositeness conveys an advantage primarily through recall and recognition. Words that are more meaningful are more memorable
(Leahey & Harris, 1996), and this recall advantage is due at least in part to semantic associability in memory (Paivio, 1971) and depth of processing (Craik & Tulving, 1975). For example, brand names that are more integratively related to the product via interactive imagery are better recalled than brand names that are unrelated to the product’s attributes or functions (Lutz & Lutz,
1977). Similarly, recall of advertising claims is greater when the claim is related to the brand name meaning, although brand name meaningfulness can also inhibit recall of claims unrelated to the brand name meaning (Keller, Heckler, & Houston, 1998). This memory advantage also diminishes as brand names become more familiar, with semantic appositeness positively correlated with brand name memorability for familiar but not unfamiliar brands (Lowrey, Shrum,
& Dubitsky, 2003).
Word familiarity. Familiar words may increase memorability, which is another key
19 criterion for a good brand name (Keller et al., 2012). Some words occur more often than others in everyday language, and those that occur or are encountered more frequently are usually more memorable (Hulme, Maughan, & Brown, 1991). The enhanced memorability for familiar words can be explained in terms of spreading activation theories of memory (Collins & Loftus, 1975).
Repeated activation of a word (or concept) increases its accessibility, which in turn increases the probability that it will be used as a basis for judgment. Thus, more familiar brand names might be expected to have an advantage in memorability over less familiar brand names.
However, there are at least two competing processes that may actually reduce the memorability advantage of familiar words. The first is distinctiveness. Distinctiveness refers to the extent to which a word is novel or unique, and things that are more distinctive are more likely to be noticed (McArthur, 1981) and processed more deeply (Berlyne, 1971). Consistent with this reasoning, research on memory for non-words vs. real words finds that non-words produce greater brain activation (Price, Wise, & Frackowiak, 1996). Thus, the distinctiveness of a word may increase memorability, and less familiar words are usually more distinctive (Lockhart,
Craik, & Jacoby, 1976). Marketers seem to be at least implicitly aware of the advantages of distinctiveness. For example, the proportion of brand names beginning with the letter K is much greater than the proportion of occurrence of all such words in the English language, which has been attributed to the distinctiveness of words beginning with K (Vanden Bergh, 1990).
A second consideration, raised by Meyers-Levy (1989), is that although familiar words should be more accessible from memory based on frequency of activation, they may also have more competing associations with other concepts. A large number of associations (large association set size) linked to a brand name may decrease the strength of each link, or retrieval path, thus inhibiting recall. Consequently, high-frequency brand names, and their associated
20 attributes, are better recalled than low-frequency names when the association set size is small, but the reverse is true when the set size is large.
Lerman and Garbarino (2002) also addressed the issue of word familiarity by measuring both recall, which is a multi-step process involving retrieval of a particular item from memory
(Lynch & Srull, 1982), and recognition, which bypasses the retrieval stage (Nedungadi, Mitchell,
& Berger, 1993). They found that recall is better for real-word than non-word brand names, but the reverse is true for recognition.
Unusual spelling. Unusual spellings are a common convention in constructing brand names. Examples include misspellings that replace certain letters in a correctly spelled word
(e.g., Froot Loops), substitute a letter for a word (e.g., U-Haul), drop a letter that does not affect the desired pronunciation (e.g., Flickr), or use a single letter as a phonetic substitute for a word
(e.g., Shop n’ Save, Toys R Us; for a review, see Wong, 2013). Unusual spellings presumably work through the same distinctiveness process we noted for unfamiliar words. The deviations from conventional spelling may attract attention because they are unexpected, different, and new
(Wong, 2013), thus increasing the memorability of unusually spelled brand names (Lowrey et al.,
2003).
Apart from increasing attention and memory, unusual spellings can also provide meaning.
For example, the type of unusual or unconventional spellings may contribute to brand meaning and brand identity. The use of a single letter as a phonetic substitute for a word (e.g., Shop n’
Save) may connote casualness, and certain types of misspellings may be common to particular demographic groups (e.g., children, sub-cultures such as gaming, skateboarding, etc.). Thus, unusual spellings can provide a signal to the target market (Wong, 2013).
Although unusual spellings appear to be beneficial for brand name recall, they may be
21 problematic for other marketing outcomes. For example, like pronunciation difficulty, unusual spellings may inhibit processing fluency, which can adversely affect crossmodal correspondences
(McNeel, 2017).
Complexity and processing mode. Semantic appositeness, word familiarity, and unusual spellings pertain almost exclusively to their use in brand names. Thus, they are necessarily very simple in terms of complexity. However, even though one- or two-word brand names are easy to process, the processing mode is more controlled, and the extent to which the process is controlled varies somewhat across the three linguistic devices. For example, the advantage of semantic appositeness is primarily through enhanced recall. Even though the brand name itself is easy to comprehend, when consumers encounter a suggestively meaningful brand name, they must consciously map the implications of the name onto the product category or attributes, and this conscious mapping increases depth of processing, which makes the semantic associations in memory stronger (Craik & Lockhart, 1972), and thus makes the brand names more memorable.
This is clearly a controlled process, in that consumers are aware of the semantic connotations of the brand name, but the process is not particularly effortful. Thus, we classify semantic appositeness in the controlled portion of Figure 1, but at the lowest level.
Similar considerations apply to word familiarity and unusual spellings. The implications of word familiarity and unusual spellings operate through more controlled processes, and the extent of the processing may vary as a function of familiarity. For example, familiar words or brand names may require relatively little processing, and in many ways may fall closer to an automatic process. However, unfamiliar or unusually spelled brand names attract attention and increase depth of processing, both of which are conscious processes (although they may occur very quickly, depending on how unusual or unfamiliar the brand names are). Although unusual
22 spellings or unfamiliar words may reduce ease of processing (fluency), they stimulate more thought about the brand name. In addition, unusual spellings (more so than unfamiliar words) can provide meaning and link to consumer identities and target markets. In such cases, the processes are even more elaborate, and thus more controlled, than the simple process of comprehending the unusual spelling. Thus, we classify unusual spellings as more controlled than word familiarity.
Complex Language
Automatic Processing
Five linguistic devices fit the classification of complex language that is automatically processed: pronouns, assertive language, politeness, language intensity, and voice (pitch and speech rate). Table 3 summarizes the effects for these linguistic devices. Although these devices share commonalities in terms of language complexity and processing mode, they also vary, relative to each other, along both the complexity and processing continua.
------Table 3 about here------
Pronouns. Pronouns are a subcategory of particles (along with articles, prepositions, and auxiliary verbs) that are often referred to as function words (Campbell & Pennebaker, 2003;
Pennebaker, 2011), that take the place of other words but have little meaning themselves.
Pronouns are often used in persuasive communications to induce self-referencing (processing information in relation to the self). For example, a spokesperson in an ad may speak directly to the consumer by including the pronoun “you” (“you may remember” vs. “one may remember;”
Burnkrant & Unnava, 1989, 1995). Self-referencing generally increases message elaboration, and thus enhances persuasion, but only when motivation to process information is high. However, excessive self-referencing can lead to too much elaboration, which can cause critical or irrelevant
23 thoughts, and thus reduce persuasion (cf. Burnkrant & Unnava, 1995; Meyers-Levy & Peracchio,
1996; Sujan, Bettman, & Baumgartner, 1993).
Pronouns are also used to reflect or imply relationships. The use of the word “we,” as opposed to “you and I,” suggests a closer relationship, and this relation has implications for how speakers are perceived by listeners (Fitzsimons & Kay, 2004). For example, in the context of ads, closeness-implying pronouns (e.g. “we”) can enhance persuasion, but only when the closeness implications are considered appropriate (e.g., current customers). In such cases, the closeness implying pronouns increase brand trust (Sela, Wheeler, & Sarial-Abi, 2012).
Pronouns can also signal emphasis on the self (vs. other) in interpersonal interactions
(Fahnestock, 2011). However, research suggests that the effects can be counterintuitive. The use of the self-referencing “you” fits with a customer-centric approach in company-consumer interactions. Indeed, marketers seem to have a naïve theory that more customer-referencing pronoun use is better, but this may not always be the case. For instance, Packard, Moore, and
McFerran (2018) found that sales and service agents’ use of pronouns to emphasize how “we”
(the firm) can serve “you” (the customer) has no effect on attitudes or purchase behavior. In contrast, when sales and service providers use the pronoun “I” to refer to how they can help the customer, customers perceive that the agent has more empathy and agency, resulting in more positive attitudes and purchase behavior.
Assertive language. Assertive language refers to statements that are confident, forceful, or bold. Assertive language can be seen in slogans and tag lines, such as “Think small”
(Volkswagen), and “Live in your world. Play in ours” (PlayStation), or advertising appeals (“Buy now!”). Although being confident, forceful, or bold may be useful at times, perhaps not surprisingly, these traits are not always well-received. In fact, the effectiveness of assertive
24 language depends on a number of factors. One factor that influences the effectiveness of assertive language is type of product. Assertive language enhances persuasion for hedonic products, but the reverse is true for utilitarian products (Kronrod, Grinstein, & Wathieu, 2012a).
These differential effects of product type can be explained in terms of communication expectations: Consumers expect assertive language for hedonic (but not utilitarian), and the congruence between expectations and outcomes increases liking and persuasion (Kim, Rao, &
Lee, 2009). Another factor that influences effectiveness of assertive language is mood. Message recipients who are in a more positive mood may expect greater levels of assertiveness because the positive mood loosens perceptions of social norms, and hedonic products are associated with more positive moods than utilitarian products (Kronrod et al., 2012a).
One potential pitfall for the effectiveness of assertive language is its propensity to induce reactance in message recipients. Reactance occurs when message recipients feel they are being ordered or commanded, which threatens their feelings of autonomy and freedom (Brehm, 1966).
Reactance effects are often observed in persuasive communications that use fear appeals, which can have negative rather than positive effects on persuasion. Similar processes have been found to underlie the effects of assertive language. For example, the use of assertive language has been shown to be effective in environmental message appeals, but only for those who already view environmental issues as important. For those who do not think environmental issues are important, assertive language is perceived as more threatening, and in line with reactance theory, produces negative effects (Kronrod, Grinstein, & Wathieu, 2012b). Similar effects were reported by Zemack-Rugar, Moore, & Fitzsimons (2017), who found that assertive ads reduced compliance (e.g., purchase frequency) for those who were committed to a brand (i.e., had a strong consumer—brand connection), and this effect was serially mediated by anticipated guilt
25 for ignoring the message and pressure to comply.
Politeness. This linguistic factor refers to the use of words and phrases that are normatively considered to be polite. In some instances, language politeness might be viewed as less assertive. The use of the word “please” in “Please recycle” adds politeness to an assertive statement, and thus politeness can potentially serve to soften the perceived pushiness of a strongly assertive slogan or appeal. However, in the only research of which we are aware that tested this possibility, the addition of a politeness marker to an assertive ad appeal (“Buy now” vs “Please buy now”) had no effect (Zemack-Rugar et al., 2017).
In other instances, polite words or phrases can be used at the beginning of a communication to lessen the negative impact of the remainder of the communication. For example, dispreferred markers, such as "I'll be honest," or “I don’t mean to be rude, but,” function as a form of social etiquette by allowing speakers to downplay the negativity of statements and soften the delivery of criticism. This use of politeness may ease the social costs of negative, face-threatening pronouncements for both speakers and listeners (Brown & Levinson,
1987; Holtgraves, 1997). Such politeness can in turn increase persuasion. For example, across various word-of-mouth situations (reviews, conversation), communicators were rated as more credible, likable, and more likely to be sought out for advice when they used dispreferred markers than when they did not. The use of dispreferred markers also influenced perceptions of brand personality (more sincere) and increased willingness to pay for the product (Hamilton,
Vohs, & McGill, 2014).
Intensity. Language intensity refers to the extent to which a message deviates from neutrality (Bowers, 1963). Deviations from neutrality can be accomplished by the addition of
26 adjectives (intensifiers) such as “very,” “really,” or “extremely,” or the use of stronger adjectives
(e.g., “detested” vs. “didn’t like”). Some studies have documented the positive effects of language intensity on message persuasiveness and its components (e.g., source credibility, trustworthiness, etc.). For example, e-mail solicitations to college alumni featuring more intense language yielded higher response rates than emails featuring less intense language (Andersen &
Blackburn, 2004), and health intervention brochures sent to parents were more effective when the language was more intensive compared to when it was less intensive (Buller et al., 2000).
However, the effects of language intensity also depend on individual differences of message recipients. One individual difference is the tendency for message recipients themselves to use intensive language in their everyday communications: The greater the tendency for message recipients to use intensive language, the more positive are the effects of intensive language use on source credibility and message agreement (Aune & Kikuchi, 1993). The effects of language intensity may also depend on pre-existing attitudes toward the source. For communicators who lack trustworthiness (e.g., politicians), the use of intensive language can backfire. For example, in a study that manipulated language intensity for a hypothetical presidential candidate, candidates using more intensive language were rated lower on character than candidates using less intensive language (Clementson, Pascual-Ferrá & Beatty, 2016).
Finally, some research suggests that the underlying mechanism for language intensity effects relates to message processing. Craig & Blankenship (2011) demonstrated that the use of more intensive language led to greater intentions to comply with a request, and this effect was mediated by message elaboration. Intensive language increased message elaboration and compliance when the message arguments were strong, suggesting that sufficient motivation and ability to process message arguments may be needed for intensive language to be effective.
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Voice: Pitch and speech rate. Voice pitch is the perceptual representation of fundamental frequency, which is the rate at which the vocal folds in the throat vibrate during speech (Dahl, 2010).1 Numerous studies in psychology and linguistics suggest that voice pitch influences a variety of judgments (for a review, see Dahl, 2010). For example, lower-pitched voices are generally evaluated more favorably than higher-pitched voices (Bond, Welkowitz,
Goldschmidt, & Wattenberg, 1987), and speakers with lower-pitched voices are considered more potent, calm, emphatic, and truthful than speakers with higher-pitched voices (Apple, Streeter, &
Krauss, 1979).
In marketing contexts, voice pitch typically applies to the speech of spokespersons in ads, and research shows that acceptance of an advertising message is greater when the spokesperson’s voice is lower-pitched than when it is higher-pitched, at least in low-involvement conditions
(Gelinas-Chebat & Chebat, 1992), and attitudes toward the ad and the product are more favorable when the spokesperson’s voice pitch is lower than when it is higher (Chattopadhyay,
Dahl, Ritchie, & Shahin, 2003). However, some research also suggests that gender may moderate these voice pitch effects. For example, in studies of marketing research telephone interviewers, those with higher-pitched voices had lower refusal rates and were generally more successful than those with lower-pitched voices (Oksenberg, Coleman, & Cannell, 1986; Sharf & Lehman,
1984). However, unlike the research just noted showing positive effects of lower voice pitch, in which the spokespersons were men, the marketing telephone interviewers were women.
Speech rate refers to how fast information is transmitted by a speaker. Research suggests that faster speech rates are more persuasive than slower speech rates and have similar effects as
1 Pitch was also discussed in the context of phonetic symbolism effects. However, we classify voice pitch as a separate linguistic device because the units of analysis are different (individual words vs. general speech).
28 lower voice pitch. The rationale is that people have a generally preferred rate of speech that is slightly faster than normal speed (Chattopadhyay et al., 2003), and people who speak within this slightly faster range are considered more credible, intelligent, knowledgeable, truthful, and persuasive (Miller, Maruyama, Beaber, & Valone, 1976; for a review, see Dahl, 2010). However, not all of the effects of speech rate are positive. Because faster speech rates necessarily occur over shorter amounts of time (time compression), listeners have less time to process the information, which can impair attention and recall (Chattopadhyay et al., 2003). Moreover, listeners may use speech rate to make inferences about the difficulty of the task, and thus elect not to devote sufficient cognitive processing resources in evaluating an ad (Moore, Hausknecht,
& Thamodaran, 1986). Indeed, some research suggests that voice and speech rate may interact.
For example, in the research that showed more favorable attitudes when speech rates were faster than when they were slower, this relation held only when voice pitch was low. Thus, the faster speech rates may have led to more peripheral processing (Petty & Cacioppo, 1986), and message recipients used peripheral cues such as voice pitch as a basis for their attitude judgments.
Complexity and processing mode. Classifying assertive, polite, and intense language in terms of complexity presents some challenges. Although the words used to convey assertiveness, politeness, and intensity are themselves very simple, their use in persuasive communications varies greatly. These devices can easily be employed in short slogans that are relatively simple
(e.g., “Go green,” “Please go green,” etc.), or in more complex persuasive communications such as email solicitations, brochures, or ad copy. We have classified assertive, polite, and intense language toward the more complex end of the continuum because most of the research that has investigated their effects has used more complex language. The same attributions pertain to voice pitch, speech rate, and pronouns, as their use is typically in more complex communications.
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However, we also recognize that the complexity will differ across contexts.
Even though the context may typically be within complex language, we have classified the processing mode as more toward the automatic end of the continuum, but close to the mid- point (see Figure 1). Generally, the effects of these devices appear to occur relatively spontaneously, and people seem to be unaware of the effects of the linguistic devices. For example, voice pitch and speech rate are automatically processed, and message recipients are usually unaware of either increases or decreases in speech rate or the effects of speech rates on their judgments (assuming that the speech rate changes do not surpass the threshold of a just- noticeable-difference). Moreover, speech rate and voice pitch are generally effective only under peripheral processing conditions (Chattopadhyay et al., 2003; Gelinas-Chebat & Chebat, 1992).
For assertive, intensive, and polite language, message recipients may be aware of their use, but they are effortlessly processed, although disfluency between their use and expectations may induce somewhat more elaborative processing. In addition, the devices exhibit the same congruency effects noted for other automatically processed linguistic devices. Congruency between a person’s tendency to use intensive language in everyday communications and the intensity of the language used in an appeal is positively correlated with source credibility and message agreement. Similarly, the positive effects of assertive language are observed when there is a fit (congruence) between the use of assertive language and expectations regarding product category (hedonic vs. utilitarian).
The effects of pronoun use also occur relatively automatically, but their use tends to prompt less automatic (more controlled) processing relative to the other four linguistic devices.
The self-referencing effects of pronoun use can induce more elaboration, which can be beneficial for persuasion. In addition, when self-referencing is in a narrative form, it increases narrative
30 transportation (Green & Brock, 2000), which increases elaboration but results in less critical evaluation of the arguments, thereby enhancing persuasion. Thus, the processing mode is automatic, but toward the mid-point of the continuum. In addition, the same congruency effects noted for other linguistic devices hold for certain types of pronoun use. The positive effects of closeness-implying pronouns are maximized when the pronoun use is consistent with message recipients’ expectations (e.g., for current customers).
Controlled Processing
Four linguistic devices fit the classification of complex language that is processed in a more controlled manner: metaphor, analogy, questions, and syntax (Table 4). These devices vary in terms of their complexity and their underlying processes, depending on the types of communications in which they are embedded.
------Table 4 about here------
Metaphor. Metaphor is a figure of speech in which a word or phrase regarding one thing is used to suggest a comparison to another thing. Metaphors can be used for brand names (e.g.,
Arrid, to imply dryness), as well as slogans and other appeals (e.g., “Budweiser, the king of beers”). Numerous studies have investigated the effects of metaphors on persuasion across disciplines (e.g., linguistics, psychology, communication, business; for a review, see Landau,
Zhong, & Swanson, 2018). The general conclusion is that metaphors produce an assimilation effect (positive effects for positive metaphors, negative effects for negative metaphors), and thus enhance persuasion, but these effects are dependent on a number of moderating conditions. In particular, metaphors are more persuasive when the comparison is novel, they appear at the beginning of related arguments (Ottati & Renstrom, 2010; Sopory & Dillard, 2002), and the message recipient is familiar with the topic or an expert in the domain (Johnson & Taylor, 1981;
31
Sopory & Dillard, 2002). However, metaphors can also have a negative effect on persuasion, particularly if there is not a sufficiently clear semantic link with literal arguments in the persuasive communication (Krumdick, Ottati, & Deiger, 2004).
In marketing contexts, metaphors have been shown to have positive effects on ad and brand attitudes and purchase intentions (Ang & Lim, 2006; McQuarrie & Mick, 1999).
Metaphors can also influence expectations and predictions. For example, using agent metaphors
(those that describe action or movement) to describe a current day stock price trend increased expectations and predictions of a continuation of the trend in the future compared to descriptions that did not use metaphor (Morris, Sheldon, Ames, & Young, 2007). In the context of consumer reviews, the use of metaphors has been shown to be more persuasive than literal language, but only for product categories (hedonic) in which the use of metaphors and other figurative language is consistent with communication norms (Kronrod & Danziger, 2013).
The underlying mechanisms of metaphor effects have also been investigated. Metaphors affect perceptions of source credibility (Bowers & Osborn, 1966), source attractiveness (Sopory
& Dillard, 2002), and source personality (Ang & Lim, 2006), although these effects are not always consistent (Ottati & Renstrom, 2010). Metaphors also influence message processing, for example by increasing attention to argument strength. However, these effects depend on message recipients’ attitudes toward the metaphor topic (Ottati, Rhoads, & Graesser, 1999).
Analogy. Analogy refers to a comparison of one thing to another to show similarities between the two. In this regard, it has a similar function as metaphor, but differs in how the comparison is made. Whereas a metaphor involves a figure of speech to make a comparison, analogy is more of a logical argument, and thus is typically more complex.
Analogies can be persuasive because they provide an effective means of comparing a
32 known base referent to an unknown referent, which quickly links properties of the base referent that are stored in memory to the target referent (e.g., a new product; Landau et al., 2018). Some research suggests that analogies have a positive influence on persuasion (McCroskey & Combs,
1969). However, the effectiveness of analogies depends on certain factors. Analogy that is used in the context of rebuttals results in decreased liking for the communicator (Whaley & Wagner,
2000), and in some cases more negative attitudes (Whaley & Holloway, 1996). Research has also demonstrated the beneficial use of analogies in marketing contexts. Analogies can increase the persuasiveness of an ad, but only when motivation and ability to process the communication is high (Roehm & Sternthal, 2001).
Questions. In the context of linguistic devices, there are primarily three types of questions: rhetorical questions, tag questions, and hypothetical questions. Rhetorical questions refer to questions in which the answer is implicit (Ahluwalia & Burnkrant, 2004), such as “Isn’t this coffee great?” As an example of figurative language, rhetorical questions are an artful deviation from message recipient expectations (McQuarrie & Mick, 1996), and thus are expected to increase elaboration. However, the effects of questions on persuasion depend on the nature of the increased elaborations, and in particular whether they are message-based or source-based.
For message-based elaborations, the basic finding is that under conditions of low involvement, rhetorical questions increase message attention and elaboration, and thus enhance persuasion
(Burnkrant & Howard, 1984; Petty, Cacioppo, & Heesacker, 1981). However, under high- involvement situations, rhetorical questions can distract message recipients from processing the arguments, which can decrease persuasion, and can also lead to perceptions of being pressured by the source, which can further decrease persuasion (Swasy & Munch, 1985). Still other research suggests that the pattern of effects may depend on where the rhetorical questions are
33 positioned in a (lengthy) persuasive communication. For example, the positive effects of rhetorical questions may hold only when the questions occur at the beginning of a persuasive communication (Howard, 1990).
Research has also documented the effects of rhetorical questions on source evaluation and elaboration, but again the effects on persuasion depend on particular factors. When message recipients have high persuasion knowledge (Friestad & Wright, 1994), rhetorical questions may cause them to attempt to infer why the communicator asked the question. Consequently, rhetorical questions posed by positively perceived sources are considered less pressuring and more persuasive, whereas the opposite is true for negatively perceived sources (Ahluwalia &
Burnkrant, 2004).
Tag questions—short rhetorical question phrases at the end of a statement (e.g., “don’t you think?”)—may also increase or decrease persuasion, depending on source credibility
(Blankenship & Craig, 2007). Tag questions can soften the impact of assertions (Lakoff, 1972), and can affect message processing, but like rhetorical questions, the effects depend on perceptions of the communication source. Tag questions increase message processing but decrease persuasiveness when source credibility is low, whereas they increase both message processing and persuasiveness when source credibility is high (Blankenship & Craig, 2007).
A third category—a hypothetical question—present a hypothetical situation (e.g., “If you knew Candidate A voted against Proposition 1, would you vote for her?”). Even though such questions are purely hypothetical, they can serve as a prime that makes the implications of the question more accessible, and thus enhance persuasion in a variety of contexts (e.g., voting, legal decisions, food choice; cf. Fitzsimons & Shiv, 2001; Moore, Neal, Fitzsimons, & Shiv, 2012).
Moreover, people are generally aware of these accessibility effects, making it difficult to debias
34 the effects of the hypothetical questions.
Syntax. Syntax refers to sentence structure (how words are arranged to create sentences).
Syntax can be used to manipulate ad copy complexity. For example, sentences using negations, passive constructions, and left-branching structures are more difficult to process than sentences that are affirmative and use active constructions and right-branching structures (Mehler, 1963;
Miller, 1962). Although the usual rule of thumb for advertising copy is KISS (Keep It Simple,
Stupid), research suggests that simple may not always be best. In fact, the research findings are mixed in terms of whether complexity reduces or enhances advertising effectiveness (for a review, see Lowrey, 2008).
One factor that may explain these conflicting findings is motivation to process information (involvement). Although ad copy complexity is generally not viewed favorably, complex syntax leads to more favorable attitudes than simple syntax when involvement with the message is high (Lowrey, 1998, 2006). The findings across these and other studies may be explained by considering advertising copy along a complexity continuum (Lowrey, 2008).
Although studies often manipulate (and label) level of complexity as high or low, in reality the more complex conditions are actually fairly moderate, which mimic more complex real-world ads. The general conclusion is that when motivation to process ad information is higher, moderately complex copy enhances attitudes toward products and improves memorability relative to low-complexity ads because it increases message elaboration (Lowrey, 1998).
Complexity and processing mode. The level of complexity for metaphor, analogy, questions, and syntax can vary substantially, depending on the type of communication in which they are embedded. For example, metaphor complexity will vary depending on whether the metaphor is in a brand name, a slogan, or a more lengthy advertising copy. The same is true for
35 analogies and questions. Most instances will involve at least a series of words to form a question or state the analogy, and thus may be moderate to highly complex. In contrast, the use of either complex or simple syntax necessarily requires multiple words or sentences. Thus, syntax falls at the extreme complex end of the language complexity continuum.
In terms of processing mode, these four devices are clearly controlled, but the underlying processes vary and are dependent upon at least two factors. The first factor is comprehension and understanding of the linguistic device itself. For example, there is evidence that metaphors are processed automatically (Gildea & Glucksberg, 1983). This may be true of simple metaphors
(e.g., “king of beers”), whereas others may require more thought (e.g., “a dream is a wish your heart makes”). Similarly, the addition of a tag question or phrasing a claim as a question rather than an assertion is easily comprehended as long as the questions are straightforward.
In contrast, analogies can be more complex and difficult to comprehend. An analogy compares a presumably known base referent to an unknown target referent. For example, consider the examples used by Roehm and Sternthal (2001). They used an analogy to Quicken (a financial management software) to explain a new nutritional management software.
Comprehending the analogy requires both prior knowledge of the base referent (Quicken) and sufficient processing resources to map that knowledge onto inferences about the target.
Consequently, analogies (compared to literal comparison conditions) are more persuasive for experts but less persuasive for novices.
The second factor that effects processing mode is how the information derived from the linguistic device is applied to subsequent judgments. For example, even when analogies are relatively easy to comprehend because knowledge of the base referent is high, using those inferences to make judgments (e.g., person perceptions, attitudes, etc.) is a controlled process.
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Thus, aspects of the situation or person (e.g., motivation or ability to process information) will dictate the extent to which analogies are beneficial, with positive effects occurring through central route processing when both motivation and ability to process the persuasive communication is high (Roehm & Sternthal, 2001).
Effects of metaphor, questions, and syntactic complexity also require substantial processing resources. The effects of these devices are observed primarily under higher involvement conditions. Moreover, for both rhetorical questions and metaphor, placement position in the persuasive communication affects persuasion, but sometimes in opposite ways, and the differential effects are a function of how the linguistic device works. Metaphors stimulate message processing, and consequently they are most effective at the beginning of a communication, assuming that the persuasive arguments are strong ones, because they increase the scrutiny of the messages. Rhetorical questions that appear at the beginning of a communication can also stimulate online message processing, whereas questions that appear at the end serve to increase elaborative, memory-based processing of the message that has just been received (Howard, 1990).
Framework Application
Maximizing the Effectiveness of Linguistic Devices
We have reviewed research on the persuasive effects of linguistic devices in marketing and have categorized the devices in terms of their language complexity and the extent to which the related processing is automatic or controlled. Both of these factors govern the conditions under which the effectiveness of the linguistic devices can be maximized.
As Figure 1 shows, the classification framework allows for a direct mapping of the linguistic devices onto the cognitive effort required to process the persuasive communication.
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The Language Complexity × Processing Mode framework facilitates unique predictions regarding cognitive effort. For example, it may seem logical that cognitive effort should be predominantly—if not completely—a function of language complexity. This reasoning is consistent with most dual process models of persuasion. Presumably, the more complex the communication, the higher the level of motivation and ability needed to process the persuasive elements of the communication. But consider the case of voice pitch and speech rate. These devices most frequently occur in very complex communications. However, because the effects of voice are more automatic, higher involvement does not enhance the persuasiveness of the communication, but in fact reduces it. Because the effects of voice on source attributions are more automatic, the positive effects on persuasion occur primarily under low involvement conditions and message recipients use voice effects in a heuristic manner.
Similar considerations apply to linguistic devices that are simple in terms of language but operate through controlled processes. For example, semantic appositeness is a characteristic of a brand name, the least complex of the devices, and its effects are predominantly related to enhanced memory. However, the effect of semantic appositeness (meaningfulness) operates through increased depth of processing. This process is effortful, and thus requires the motivation and ability to elaborate on the implications of the brand name (e.g., what it suggests about what the product is, what it does, how good it is, etc.). Alphanumeric brand names provide another example. Although we have classified them in the automatic portion of processing mode, and they are one of the least complex devices, the attributions about what the combination of numbers and letters mean requires a reasonable level of cognitive effort. When consumers are willing to expend the effort, then the desired effects on persuasion are observed. However, when consumers are unwilling or unable to devote sufficient cognitive resources, the numbers may be
38 used in a heuristic fashion that can be counterproductive (Gunasti & Ross, 2010). For these reasons, we argue that the dual consideration of both language complexity and processing mode provides a more accurate estimate of cognitive effort than does language complexity alone.
The research we have reviewed also details the particular effects that linguistic devices have on different aspects (or stages) of persuasion. Some devices primarily affect memory, some devices affect downstream variables such as attitudes and intentions, and some devices affect intermediary (mediating) variables. Thus, whether the effects of linguistic devices enhance persuasion may depend on the objective (e.g., memory, attitudes, behavior). For example, consider the case of word familiarity, whose effects can operate through different (competing) processes. On the one hand, more familiar words are generally easier to recall initially, but they also have more associations in memory, which can inhibit recall in certain situations. On the other hand, unfamiliar words are more distinctive, which can increase depth of processing, but only if consumers are willing and able to elaborate on the distinctiveness. Unusual spellings operate in ways similar to those of word familiarity. The nature of the unusualness itself can convey meaning (e.g., casualness, target markets), and thus have effects on persuasion-related outcomes such as attitudes and perceptions.
We have categorized the linguistic devices in terms of a single point in the two- dimensional Language Complexity × Processing Mode space (Figure 1). However, as we have noted throughout, the single-point categorization is for heuristic purposes, and both complexity and automaticity can vary depending on a variety of factors. In this regard, the framework is flexible, and the placement of any linguistic device can be adjusted based on these factors to arrive at an approximation of the required cognitive effort needed to maximize persuasion.
Theoretically, such adjustments could place a particular linguistic device into a different
39 quadrant entirely, but practically we expect that adjustments would move primarily within the same quadrant.
Resolving Conflicting Findings: The Relative Benefits of Congruence vs. Incongruence
We use the term congruence to refer to the degree of similarity between marketing or message elements. Congruence effects are generally explained in terms of schema congruity theory, which pertains to the relation between activated concepts and expectations, and people generally prefer things that conform to their expectations (Mandler, 1982). Consistent with this reasoning, we have reviewed a number of instances in which the effects of linguistic devices are stronger when congruence is maximized (high congruity). For example, the effects of phonetic symbolism on brand name preference are maximized when the sound symbolic (Guèvremont &
Grohmann, 2015; Lowrey & Shrum, 2007; Yorkston & Menon, 2004) or motor movement
(Topolinski et al., 2015) connotations of the brand name are congruent with expected or preferred attributes of the product. Similarly, the positive effects of assertive language are greater when the use of assertive language is congruent with expectations regarding product category
(Kronrod et al., 2012a). Congruency effects are also observed in the use of intensive language, which is most effective for message recipients who themselves use intensive language in everyday communications (Aune & Kikuchi, 1993). In addition, congruence between the linguistic style (e.g., politeness) of the request and the receiver’s expectations increases persuasion (e.g., Brown & Levinson, 1987; Forgas, 1998; Hamilton et al. 2014), and congruency between closeness-implying pronouns and message recipients’ perceptions of conversation norms enhances persuasion (Sela et al., 2012).
Despite these very consistent findings, a sizeable literature also suggests that high congruence is not optimal, but instead, moderate levels of incongruence tend to produce the most
40 positive persuasion-related outcomes (e.g., product evaluations). For example, Meyers-Levy,
Louie, and Curren (1994) found that extensions whose brand names were congruent with the product category of the parent brand were evaluated more favorably than brand names that were extremely incongruent, consistent with a congruency effect. However, they found that brand names that were moderately incongruent were actually the most preferred, and this enhancement for moderate incongruity was mediated by positive cognitive elaboration. This inverted-U- shaped relation has been demonstrated in numerous studies, typically ones that relate to preferences for new products or extensions (cf. Jhang, Grant, & Campbell, 2012; Kronrod &
Lowrey, 2016; Maoz & Tybout, 2002; Meyers-Levy & Tybout, 1989; Noseworthy, Cotte, &
Lee, 2011).
Mandler (1982) explained this U-shaped relation in terms of the comprehension and resolution processes. Congruent links are easy to comprehend, and no resolution of incongruency is required, making them predictable but also not overly stimulating. Extremely incongruent links are more difficult to process, and the incongruency is unlikely to be resolved, which creates negative affect because the inability to resolve the incongruency is frustrating. In contrast, moderately incongruent links increase elaboration in an effort to resolve the incongruence, and if successful, the resolution can be rewarding and pleasantly arousing (Maoz & Tybout, 2002;
Noseworthy, Di Muro, & Murray, 2014). Consistent with this reasoning, a number of moderators have been identified that relate to arousal, such as perceived risk (Campbell & Goodstein, 2001), experiential processing (Noseworthy et al., 2011), and involvement (Maoz & Tybout, 2002).
The positive effects of other linguistic devices are also based on incongruence with expectations. Unusual spellings are remembered better precisely because they are unusual
(unexpected), and thus stimulate greater depth of processing. Rhetorical devices such as
41 metaphor are unexpected artful deviations and are processed more deeply, and they increase elaboration and generate pleasure because their initial ambiguity stimulates interest, and resolving the ambiguity can feel rewarding (Berlyne, 1971; McQuarrie & Mick, 1992).
The framework we have presented provides a potential explanation for the apparent conflicting findings with respect to congruence. As Figure 1 shows, of the examples we just provided, all of the linguistic devices that show positive effects of congruence (phonetic symbolism, assertive, intensive, and polite language) fall in the automatic processing quadrants
(bottom half of Figure 1, independent of complexity). Because of the automatic nature of the effects, perceptions that are related to congruence do not rely upon extensive processing, but instead are more sensory in nature. Message recipients rely upon general perceptions of fit, but they are typically unaware of either the reasons for the perceptions or how they are applied to judgments. Thus, positive congruence effects appear to occur when message recipients do not overly elaborate on the messages.
In contrast, the linguistic devices that show positive effects of incongruence (unusual spelling, metaphor) fall in the controlled processing quadrants (top half of Figure 1, independent of complexity). These linguistic devices benefit from message elaboration, which is a controlled process. Assuming cognitive processing resources are available and a person is willing to use them, moderate incongruency stimulates elaboration, which is often pleasurable, and enhances persuasion. Although the effects reported by Meyers-Levy et al. (1994) and others are based on stimuli that are not easily categorized as linguistic devices, the positive effects of moderate incongruence generally occur through more elaborative, controlled processing (e.g., high involvement; Maoz & Tybout, 2002).
The same reasoning applies to the finding that moderate levels of syntactic complexity
42 are more persuasive than low and high levels (Lowrey, 1998). Although not concerned with congruence per se, moderate levels of complexity, like the moderate levels of congruence investigated by Meyers-Levy et al. (1994), increase positive message elaboration. However, in this case, because language complexity is high, the results hold only for those with sufficient motivation and ability to process the persuasive communication.
Research Opportunities
Although the review and framework we have proposed document the robustness of the use and effectiveness of linguistic devices in persuasion, they also reveal a number of potential research opportunities. First, one of the more glaring research gaps is the lack of work demonstrating the generalizability of linguistic devices across cultures. This issue is particularly important given recent reviews that suggest that what are considered fundamental psychological processes and effects often are not observed (and in fact may be reversed) in other cultures (cf.,
Henrich, Heine, & Norenzayan, 2010; Oyserman, Coon, & Kemmelmeier, 2002) or even subcultures (Carey & Markus, 2016). For example, although phonetic preferences (Pogacar,
Peterlin, Pokorn, & Pogačar, 2017), the front/back vowel effect (Ultan, 1978), and phonetic congruence (Shrum et al., 2012) have been documented across languages, there is relatively less systematic evidence of the cross-linguistic persuasiveness of other phonetic effects, such as consonant symbolism (but see Blasi, Wichmann, Hammarström, Stadler, & Christiansen, 2016 for recent evidence of consonant effects more generally).
Although the lack of research documenting cross-cultural effects for certain types of phonetic symbolism clearly limits the extent to which current findings can be generalized, there is also a more fundamental theoretical issue that represents a research opportunity: the origins of the effects. For example, are phonetic effects innate, or are they learned over time (for a review,
43 see Spence, 2012)? If innate, then relatively universal effects would be expected, and the effects should also be observed at the advent of language acquisition (e.g., young children). However, if they are learned over time, then shared meanings that frequently differ across cultures suggest that the effects may not be cross-culturally robust and are unlikely to be observed at the earliest stages of language development (cf. Baxter & Lowrey, 2011, 2014).
Similar considerations apply to other automatic effects, such as speech rate. For example, faster speech rates are believed to be more persuasive because research shows that people have a generally preferred rate of speech that is slightly faster than normal speed. However, the extent to which these effects may generalize to other languages likely depends on the origin of the effects.
If the effects are for the most part innate (e.g., slightly higher levels of arousal that may be induced by faster speech rates are universally preferred), then the effects are more likely to generalize (although the precise preferred rate may still differ across languages and cultures). In contrast, if the effects occur over time through a socialization process, then the meanings assigned to faster versus slower speech may differ across cultures, depending on cultural conversational norms.
For other linguistic devices, such as polite, assertive, and intense language, the effects relate directly to communication norms and expectations. Communication norms differ across cultures (Hall, 1976; Richardson & Smith, 2007), and have important consequences for how individuals respond to communications independent of the content of what is communicated
(Lee, Shrum, & Yi, 2017). Consequently, to the extent that concepts such as politeness and assertiveness differ across cultures, it is likely that the effects of these linguistic devices may also vary. Given the role that communication norms and expectations play in these effects, as well as
44 others (e.g., number granularity), research that addresses the role of culture and communication norms in the context of linguistic devices would be useful.
Another potentially useful avenue of research pertains to the role of individual differences in the effects of linguistic devices. For example, we noted earlier that the effects of communicator voice pitch are essentially opposite for male and female communicators.
However, the evidence for such gender differences in spokesperson voice pitch effects is very limited, and no research to our knowledge has systematically investigated these differences.
Perhaps more important, apart from simple individual difference effects, future research would benefit from a better understanding of the underlying processes. For example, the effects of voice pitch on persuasion appear to be mediated by the effects of voice pitch on source attributions
(credibility, attractiveness, trustworthiness, etc.). If so, do the effects of voice pitch in such situations function similarly to phonetic symbolism effects (e.g., higher pitch associated with particular qualities, such as size, masculinity, power)? Additionally, is congruence important, such as the congruence between attributions of voice pitch, expectations of gender, and characteristics of the brand or product (e.g., perceived masculinity or femininity of the product, apart from actual gender use)? For both spokesperson voice pitch and phonetic symbolism effects for brand names, pitch may be related to important attributes of the brand (e.g., competence, warmth, etc.) that have important implications for persuasion.
Another way in which individual differences may be integrated into research on linguistic effects pertains to the relation between individual differences in language use. To take one example, pronoun use (e.g., “I” vs. “we”) is associated with a variety of individual difference variables (e.g., age, gender, personality, emotion, need states; Pennebaker, Mehl, & Niederhoffer,
2003). One possible avenue for future research is to address the question of whether these
45 individual difference relations affect perceptions of the communicator. For example, do message recipients infer particular characteristics of the source based on how they use language, similar to the effects of voice pitch? The same considerations apply to other linguistic devices such as polite, assertive, and intensive language. Put differently, can the mediating role of expectations that has been noted for several devices be explained in part by inferences about the communicator based on what types of words they use and how they use them? If so, then persuasion may be enhanced by maximizing the congruence between these expectations and elements of the message.
Finally, we have confined our review to research that pertains to the effects of linguistic devices on message recipients. However, emerging research suggests that the language communicators use also affects communicators themselves. For example, the use of explaining language (“because”) in online reviews can affect the communicators’ own evaluations of an experience they are reporting, because the explaining language increases their understanding of the experience, which ironically can have detrimental effects, depending on whether the experiences are hedonic or utilitarian (Moore, 2012). Based on these findings, research that expands the focus to other linguistic devices may be fruitful. For example, what effects do the use of devices such as polite, assertive, or intense language have on the communicator?
Correlations between individual difference variables and language use noted previously appear to assume that individual differences influence language use (Pennebaker et al., 2003). However, in instances in which the particular individual difference may be situational (e.g., mood, emotion, social constraints), does language use influence these variables? If so, then the words chosen to communicate product or experience information may have effects on the communicator as well
46 as the recipient. Thus, research that goes beyond traditional communicator-recipient models may provide additional insight into how language affects thinking.
In conclusion, the review we have provided documents the extensive research on the persuasive effects of linguistic devices, and the framework we have proposed provides an organizing tool for understanding how the linguistic devices exert their effects. However, despite the relative maturity of this research area, we believe there are important research questions yet to be answered, and the goal of this framework is to help structure and inform future inquiries.
47
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Table 1 Summary of Simple-Automatic Device Effects
Linguistic Effects Representative Citations
Device
Phonetic • sounds based on vowels and consonants influence Klink (2000); Lowrey and
Symbolism consumer perceptions, expectations Shrum (2007); Maglio et
• positive effects on preferences maximized when al. (2014); Topolinksi et
symbolism is congruent with expectations al. (2015); Yorkston and
Menon (2004)
Numbers • associated with perceptions of technology Gunasti and Ozcan (2016);
• granularity influences inferences and expectations Pavia and Costa (1993);
• roundedness associated with perceptions of completeness Yan and Pena-Marin
(2017); Zhang and
Schwarz (2012)
Sound • alliteration and rhyme aid memory Argo et al. (2010); Davis
Repetition: • rhymes increase processing fluency et al. (2016); Filkuková
Alliteration • influence liking, perceptions of truthfulness and Klempe (2013); and Rhyme McGlone Tofighbakhsh
(2000)
Pronunciati • easier to pronounce words are easier to process (greater Laham et al. (2012); Song on (Ease) fluency) and Schwarz (2009)
• associated fluency influences perceptions of familiarity
64
• associated familiarity influences perceptions of risk,
novelty, liking
65
Table 2 Summary of Simple-Controlled Device Effects
Linguistic Marketing Outcomes Citations
Device
Semantic • aids recall and recognition Keller et al. (1998);
Appositenes • increases depth of processing Lowrey et al. (2003); Lutz s and Lutz (1977)
Word • familiar words usually easier to recall, but can also have Hulme et al. (1991);
Familiarity more competing associations, reducing memorability Lerman and Garbarino
• unfamiliar words more distinctive, which increases depth (2002); Meyers-Levy
of processing, which has positive effects on memory (1989)
Unusual • attracts attention, which enhances memory Lowrey et al. (2003);
Spelling • affects perceptions of casualness McNeel (2017); Wong
• can be associated with consumer identities (2013)
• but can inhibit processing fluency
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Table 3 Summary of Complex-Automatic Device Effects
Linguistic Marketing Outcomes Citations
Device
Pronouns • induces self-referencing Burnkrant and Unnava
• enhances persuasion when sufficient motivation and (1989, 1995); Fitzsimons
ability to process information and Kay (2004); Packard
• can increase message elaboration, which can enhance et al. (2018); Sela et al.
persuasion, but too much elaboration can be distracting (2012)
• can imply relationships, which enhances persuasion if
the implied relationships considered appropriate
Assertive • more effective for hedonic than for utilitarian products Kronrod et al. (2012a,
Language • can induce reactance, and thus have negative effects on 2012b); Zemack-Rugar et
persuasion al. (2017)
Politeness • can temper assertive language (reduce reactance) Brown and Levinson
• lessens impact of negative information (1987); Hamilton et al.
• influences perceptions of brand personality (2014); Zemack-Rugar et
al. (2017)
Intensity • can increase message elaboration Anderson and Blackburn
• effective if message recipients themselves are prone to (2004); Aune and Kakuchi
using intensive language (1993); Buller et al.
(2000); Clementson et al.
67
• effective if attitudes toward source are positive, backfires (2016); Craig and
if negative Blankenship (2011)
• influences perceptions of source credibility and
trustworthiness
Voice: • lower pitch liked better, but primarily when Apple et al. (1979); Bond
Pitch, communicator is male et al. (1987);
Speech Rate • pitch affects perceptions of source (potency, truthfulness) Chattopadhyay et al.
• slightly faster (than normal) speech rates evaluated more (2003); Gelinas-Chebat
favorably and Chebat (1992); Sharf
• rate affects perceptions of source (credibility, and Lehman (1984)
trustworthiness)
• but may impair attention and recall
Table 4 Summary of Complex-Controlled Device Effects
Linguistic Marketing Outcomes Citations
Device
Metaphor • effective when comparison is novel, appears at Ang and Lim (2006);
beginning, and recipients familiar with topic Kronrod and Danziger
• influences expectations (2013); Landau et al.
• influences source credibility, attitudes, perceptions (2018); McQuarrie and
• problematic when metaphor is not fully understood Mick (1999); Ottati et al.
68
(1999); Sopory and Dillard
(2002)
Analogy • enhances persuasion under high involvement conditions McCroskey and Combs
• enhances persuasion if comparison is well-understood (1969); Roehm and
• less effective when used in rebuttals Sternthal (2001); Whaley
and Holloway (1996);
Whaley and Wagner
(2000)
Questions • increases elaboration because often unexpected Ahluwalia and Burnkrant
• excessive use can be distracting and reduce persuasion (2004); Burnkrant and
• more effective at beginning than end of communication Howard (1984);
Fitzsimons and Shiv
(2001); Moore et al.
(2012)
Syntax • affects copy complexity and ease of processing Lowrey (1998, 2006);
• moderately complex copy more persuasive under high- Miller (1962)
involvement conditions
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Figure 1 Language Complexity × Processing Mode Framework
Syntax Analogy • Unusual Spelling Controlled • Word Familiarity High • Semantic Appositeness Questions
Metaphor
Cognitive Effort Pronouns
Low • Numbers Politeness Intensity Processing Mode Processing Assertive Language
Pronunciation Voice: Pitch, Speech Rate Sound Repetition Phonetic Symbolism Automatic
Simple Language Complexity Complex
70
Essay 2
Is Nestle a Lady? Brand Name Linguistics Influence Perceived Gender, Warmth, and
Brand Loyalty
Abstract
Brand names can communicate brand gender, and feminine brand gender increases perceived warmth, which in turn increases brand loyalty. Therefore, longer names that end in a vowel (e.g.,
Burberry) sound both more feminine and more warm than shorter names that end in a consonant
(e.g., Ford). Using both experimental manipulation of hypothetical brands and observational analysis of real brands, this research shows that people feel more loyal toward brands with feminine names, predict that feminine sounding brands are more likely to be top performers than parallel masculine sounding names, and this expectation bears out in the marketplace, where top brands have more feminine names than less successful brands. A feminine brand name is even more beneficial for hedonic, relative to utilitarian, products. However, the advantage for feminine names is neutralized when the typical user of a product is male, and masculine brand names are preferred when warmth is not a desirable product attribute.
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Brands succeed or fail for many reasons - product quality, managerial decisions, service quality, etc. One perhaps under-appreciated factor is the linguistic characteristics of a brand’s name. A well-crafted name may enhance awareness and attitudes (e.g., Aaker and Keller 1990), whereas a bad name can be a product’s demise (e.g., the Ford Edsel; Hartley 1992; Klink 2000).
The brands Coca-Cola, Burberry, and Nestlé are successful for many different reasons, but one thing these brands have in common is names with feminine linguistic characteristics.
Specifically, all three names are longer than one syllable and end in vowels. In this research we demonstrate that brand names with feminine linguistic characteristics are perceived to be warm and therefore inspire greater customer loyalty.
Prior research suggests that top brands feature distinct sound patterns relative to less successful brands because certain sounds are more pleasing to consumers and therefore contribute to brand performance (Pogacar et al., 2015). Linguistic features such as brand name sounds that convey desirable attributes can enhance product preference. For instance, participants report that an ice cream called “Frosh” tastes better than the same ice cream called
“Frish.” Moreover, these effects are automatic and nonconscious (Yorkston and Menon 2004); thus, if carefully crafted, qualities of a name may provide an extra source of affinity for the brand that consumers respond to instinctively. This may provide a performance boost over competitors with comparable managerial and strategic competence. Notably, whereas brand name sounds have been well researched, research on brand name length and stress is surprisingly scant.
Names are composed of many linguistic features, including sounds, syllables, and stress.
These form a set of distinct characteristics associated with traditionally masculine and feminine names that has persisted across generations. In general, men’s names are more likely to end in a consonant whereas women’s names are more likely to end in a vowel, particularly the ‘a’ sound
72 as in the name “Donna” (Cassidy, Kelly, and Sharoni 1999; Lieberson and Bell 1992). Men’s names also tend to be shorter, and if they have more than one syllable, the stress is often on the first syllable (e.g., RO-bert), whereas women’s names more often have stress on the second or later syllable (e.g., Ro-BER-ta) (Lieberson and Bell 1992; Slater and Feinman 1985). However, analysis of the most common baby names given during a thirty-year period from 1960 to 1990 found a trend toward giving both male and female babies more feminine names (Barry and
Harper 1995). The authors interpreted this change as signaling an increase in preference for attributes such as warmth, which is commonly associated with femininity.
The degree to which a brand name sounds masculine or feminine is relevant because gender perceptions can lead to inferences about brand personality (Aaker 1997; Grohmann
2009). Specifically, femininity is associated with warmth (Eagly and Mladinic, 1994; Fiske,
1998; Fiske et al., 1999; Glick et al., 2000), a desirable brand attribute in most product categories. Warm brands inspire positive consumers’ attitudes and repurchase behaviors (Dick and Basu 1994; Chaudhuri and Holbrook 2001), and greater brand loyalty (Biel 1993; Brakus
Schmitt and Zarantonello 2009; Fournier 1998),which should ultimately lead to better brand performance (Park et al., 2010). However, warmth alone may be insufficient to generate brand loyalty. For consumers to become loyal, however, a brand will likely also need to possess some degree of competence. Research suggests that when both warmth and competence are present, consumers should be brand loyal because warmth combined with competence leads to affiliation
(Fiske, Xu, Cuddy and Glick 1999; Fiske et al 2002; Glick and Fiske 1999).
The present research examines the effect of brand name on brand loyalty, as a function of warmth and competence, and the downstream implications for brand performance. We find that feminine brand names are perceived to be warm, which increases brand loyalty, and that this
73 effect is moderated by perceived competence (Study 1). Moreover, brand name gender leads to perceived warmth and brand loyalty, which increases predicted brand performance in a serial mediation model (Study 2). This effect is stronger for hedonic than utilitarian products because warmth is a greater consideration for hedonic products (Study 3). Finally, the advantage for feminine names is neutralized when the typical user of a product is male (Study 4) and masculine brand names are preferred when warmth is not a desirable product attribute (Study 5).
CONCEPTUAL DEVELOPMENT
Brand Name Linguistics
Names may vary on three key dimensions: sounds, number of syllables, and stress. The sounds, or ‘phonemes,’ in a name include the specific sound attributes of the various consonants and vowels comprising the name. Length, as measured by the number of syllables, can vary from one syllable (e.g., Fred) to four (e.g., Angelica), and, rarely, even five (e.g., Evangelina). Thus, the names John and Joan differ only in their sound properties, whereas John and Josephina differ in terms of sounds, syllable length, and stress. Stress refers to the relative emphasis placed on each syllable. Names with only one syllable by definition consist of a single stressed syllable, whereas in names with more than one syllable the position of stress may vary from the first position (e.g., DAN-iel) to the second (e.g., dan-IELLE), or later (e.g., don-a-TELL-a).
Sound symbolism refers to the way sounds convey meaning, and the study of sound symbolism in brand names has produced a rich literature (e.g., Klink 2000; Lowrey and Shrum
2007; Yorkston and Menon 2004). One key finding is that names with front vowels, such as those in “Intel,” which are produced in the front of the mouth, sound smaller, lighter, faster, and
74 more feminine than names with back vowels, such as “Ford” (Klink 2000). This suggests that the phonetic qualities of a brand name may be tailored to match the desired brand image.
Whereas brand name sounds have been a frequent topic of research, length and stress have received surprisingly little attention in the marketing literature. The two published studies on brand name length that do exist present conflicting results. In terms of memorability – a key concern for brand names – Vaden Bergh and colleagues found that single syllable names elicit greater recall than three syllable names (1984). Alternatively, in terms of general appeal, Crystal
(1995) demonstrated that appealing sounding words in English tend to have three or more syllables (e.g., from the poet John Kitching’s list of beautiful words: “flamingo,” “chinchilla,”
“enigma,” and “akimbo”). Perhaps relevant to the current research is the finding that, in the
United States, women’s names tend to be longer than men’s (Cutler, Norris, and Williams 1987).
Though the relation between name length and liking remains unclear, it appears that longer names tend to be more feminine.
Whereas past research has examined brand name phonetics and sound symbolism, no prior research in marketing has investigated the interplay of phonetics, syllables, and stress patterns. Furthermore, most prior research has focused on the use of brand name linguistics to convey desirable attributes, rather than abstract personified qualities such as warmth and competence. Finally, prior work has looked at the short-term or point-of-purchase effects of brand names rather than the long-term effects on consumer attitudes and behavior. In other words, research has not previously examined the interaction of brand name elements on perceptions of warmth or competence, or consumer behaviors such as loyalty.
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Warmth, Competence, and Brand Loyalty
Warmth represents the degree to which a target seems warm, tolerant, good-natured, and sincere, whereas competence represents the degree to which a target seems competent, confident, independent, competitive, and intelligent (Fiske et al., 2002). These two fundamental dimensions are critical to the way people categorize and understand the social world because they address two issues relevant to our ancestors’ survival. That is, warmth (or lack thereof) indicates whether another has benign or hostile intentions, and competence indicates whether they have the capacity to carry out such intentions. Of the two, warmth is considered primary because it distinguishes friend from foe, a distinction that for primitive humans had to be answered swiftly to determine whether a fight or flight decision was at hand. The competence of a potential threat might be considered secondarily if it became necessary to determine whether fight or flight was more strategically advisable (Cuddy, Glick, and Beninger 2011).
Studies examining morality and competence, where morality is operationalized as warmth (Cuddy, Glick, and Beninger 2011) show that warmth and competence are ubiquitous in the way we judge and perceive other people, accounting for more than 75% of the variance in evaluations of individuals, with warmth being the leading component (Wojciszke 1994). For instance, when asked to indicate the traits they considered important in forming a general opinion of another person, participants indicated that traits related to warmth were significantly more important than traits related to competence (Wojciszke, Dowhyluk, and Jaworski, 1998).
Furthermore, warmth judgments are made more rapidly than competence judgments and have more influence on global attitudes (e.g., Wojciszke, Bazinska, and Jaworski,1998; Wojciszke and Abele, 2008) as demonstrated in the context of lexical decision tasks (Ybarra, Chan, and
Park, 2001), split second judgments of faces (Willis and Todorov, 2006), and even the way
76 children as young as three make decisions based on warmth about newly-encountered people before making decisions based on competence (Mascaro and Sperber, 2009).
The various responses elicited by the four possible combinations of high versus low warmth and competence have been discussed extensively in the literature (e.g., Cuddy, Glick, and Beninger 2011). Of primary importance for the present research, the stereotype content model posits that warmth combined with competence leads to affiliation (Fiske et al., 1999;
Fiske et al., 2002; Glick and Fiske 1999), prompting association behaviors (Becker and Asbrock,
2011; Cuddy, Fiske, and Glick 2007). We predict that this associative impulse will manifest as loyalty in the context of brands.
Brand loyalty refers to consumers’ attitudes and behaviors toward a brand, including continued purchasing and positive word-of-mouth (Swan and Oliver, 1989). Loyalty is a strong positive predictor of firm profitability and growth (Reichheld and Teal, 2001; Rust and Zahorik,
1993), and contributes to overall brand equity (Biel 1993). Brand loyalty is driven by two primary factors: trust and positive affect, i.e., the extent to which a brand makes customers feel
“good” and “happy” (Chaudhury and Holbrook 2001).
If brand names convey gender associations that lead to inferences of warmth this may enhance brand loyalty because warmth, in combination with competence, leads to perceptions of ingroup status and affiliation behaviors (Becker and Asbrock, 2011; Cuddy et al., 2007; Fiske et al., 2002b).
In the following sections, we present five studies showing that brand name linguistics – specifically, sounds, syllable length, and stress – signal brand name gender, which influences perceived brand warmth. Warmth, in combination with competence, enhances brand loyalty, and contributes to predicted brand performance.
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PILOT STUDY
We conducted an exploratory analysis of Interbrand top brand names compared with less successful brands, using datasets taken from the literature (Pogacar et al., 2015). The Interbrand top brand names consist of an unduplicated composite list of the 144 ‘global top brands’ for a ten-year period from 2001 to 2010. The comparison dataset consists of 144 business names derived from a random sample of the Corpus of Contemporary American English (Davies 2009).
(Duplicate Interbrand names were removed from the comparison dataset prior to analysis).
Names from both the top brand and less successful brand lists were coded according to the Phonetic Gender Scoring system. The Phonetic Gender Score (henceforth the “name gender score”) is a normative scale that quantifies the degree to which a name is masculine or feminine by assigning a value between -2 (very masculine) and +2 (very feminine) for each name characteristic (Barry and Harper 1995). The scale is based on the documented characteristics of generations of men’s and women’s names in the United States, such that characteristics most common to women’s names, such as ending in a schwa (e.g., Amanda), are assigned a positive value, whereas characteristics most common to men’s names, such as ending in “d” (e.g., Brad), are assigned a negative value, and characteristics that are equally common to both genders, such as ending in “n” (e.g., Joan or John) carry a neutral score of 0 (Appendix B). Since many brands consist of two or more names, in the present research we average the scales for all words in the name to calculate the mean name gender score for each brand. This method represents an important new perspective and measurement tool for marketing.
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Analysis of Interbrand top brand names compared with less successful brands shows that top brand names have significantly higher phonetic gender scores (M = .16, SD = 1.06) than less successful brands (M = -.20, SD = 1.09; t(286) = 2.83, p = .005, d = .34). Further analysis shows that for all product categories represented by at least five names on the Interbrand list (i.e., alcohol, automotive, electronics, financial services, fast-moving consumer packaged goods, and luxury products) the average name gender scores is positive, indicating femininity, in all but one case (fast-moving consumer packaged goods, e.g., Kraft).
This finding is noteworthy because it suggests that the most successful brand names are more likely to have feminine linguistic characteristics. Next, we will report on three studies that examine this phenomenon in the context of both real-world and hypothetical brand names.
STUDY 1
In Study 1, we seek to better understand the prevalence of feminine name characteristics among top brands relative to less successful brands. To this end, we asked participants to evaluate a sample of real brands, and indicate how warm and competent each seemed, and how loyal they felt toward each. We then test whether feminine (versus masculine) brand name gender predicts warmth and loyalty. We predict that warmth will mediate the effect of brand name gender on brand loyalty. Further, we propose that, although warmth is a key driver of brand loyalty, competence will moderate the indirect effect. Formally:
H1a: Feminine brand name gender will predict perceived warmth, which will predict
brand loyalty.
79
H1b: Competence will moderate the indirect effect of brand name on loyalty through
warmth such that loyalty will be greatest when both warmth and competence are high.
Selection of Stimulus Brands
To identify brands with a high degree of variability in terms of loyalty that are relevant to the participant population, we asked a separate sample of one hundred mTurk workers (60% male, Mage = 34.66) to list ten brands they thought were “really cool” and ten brands they
“would never use,” following the procedures outlined by Escalas and Bettman (2003). We then selected the twenty-five most frequently listed brands in each category (Appendix B). The name gender score was calculated for each brand. Notably, an independent sample t-test indicated that the well-liked brands had significantly higher (more feminine) name gender scores than the disliked brands (M = .20, SD = .90 vs. M = -.54, SD = 1.1; t(48) = 2.64, p = .01, d = .75). In other words, well-liked brands have more feminine names. These results suggest that the prevalence of feminine name characteristics among Interbrand top brand names is not merely spurious.
Method
Participants. Five hundred and seventeen mTurk workers (52% male, Mage = 36.85) participated in the main study.
Procedure. Each participant was presented with a randomly selected subset of ten of the fifty brands, and for each brand was asked to evaluate warmth, competence, and brand loyalty measures in random order. Warmth was measured by asking participants to indicate the extent to which each brand sounded tolerant, warm, good-natured, and sincere (Fiske et al. 1999) on a
80 seven-point scale anchored at 1 (Not at all) and 7 (Very much; α = .96). Competence was measured by asking to what extent each brand sounded competent (Cuddy, Fiske and Glick
2007) on the same seven-point scale. Brand loyalty was assessed with five measures based on
Chaudhuri and Holbrook (2001) and Brakus, Schmitt, and Zarantonello (2009): “I will / would be loyal to [brand],” “I’ll buy [brand] in the future,” “I would choose [brand] over other options,” “I would recommend [brand] to others,” and “I am committed to [brand],” on seven- point scales anchored at 1 (Not at all) and 7 (Very much; α = .95). Finally, participants were asked to indicate how familiar they were with each of the brands they had evaluated on seven- point scales anchored at 1 (Not at all) and 7 (Very much) before completing standard demographic information.
Results
Direct Effects and Interactions. As hypothesized, brand name gender predicts perceived warmth (t(5136) = 3.14, p = .002, d = .09), which predicts brand loyalty (t(5137) = 64.98, p
< .001, d = 1.81), and this indirect effect is qualified by an interaction between warmth and competence (t(5136) = 9.26, p < .001, d = .12) such that loyalty is highest when both warmth and competence are high. However, the indirect effect through warmth is smaller when competence is low (β = .02, CI [.002, .04]) and greater when competence is high (β = .03, [.002, .06]).
Mediation and Moderated Mediation. we hypothesized that feminine brand name gender would be positively related to warmth perceptions, which would in turn be positively related to brand loyalty, resulting in an indirect effect of brand name gender on brand loyalty through warmth. Mediation analysis using PROCESS Model 4 (Hayes 2013) with 5,000 bootstrapped resamples confirmed this (95% CI = [.001, .06]), supporting H1a. we also predicted that
81 competence would moderate this indirect effect, and moderated mediation analysis using
PROCESS Model 14 (Hayes 2013) with 5,000 bootstrapped resamples confirmed this (95% CI =
[.0003, .005]), supporting H1b (Figure 1).
------Figure 1 about here------
Familiarity. Mean familiarity was significantly above average, indicating that participants were familiar with the brands they evaluated (M = 5.36, SD = 1.83), and including familiarity as a covariate does not alter the direction or significance of results.
Warmth and Competence. Notably, although both warmth and competence predict brand loyalty, the effect of warmth is larger (d = .81, 95% CI [.79, .84]) than the effect of competence
(d = .68, 95% CI [.65, .71]), and the confidence intervals around these effect sizes do not overlap, indicating that the effect of warmth is significantly larger than the effect of competence
(Fritz, Morris, and Richler 2012).
Rater Effects. To examine possible rater effects, we followed the protocols established by
Bates (2005), using the linear model function and the linear mixed model functions in lme4 package (Bates 2005; Bates and Maechler 2009) in the statistical software R (version 3.2.3; R
Development Core Team 2009). A multiple linear regression model with brand name gender, warmth, and competence as predictors of brand loyalty reproduced the results in the PROCESS model. Next, to account for participant level variability, we ran a linear mixed effect model with brand name gender, warmth, and competence (including interaction term) as fixed effects, and separate intercepts for each participant as random effects. The pattern of results remained the same, but this produced lower Akaike information criterion (AIC) and Bayesian information criterion (BIC) scores (17,452 versus 16,507 and 17,498 versus 16,560, respectively), indicating that the model with participant as a random effect better represents the data than the model
82 without. The p value from the likelihood ratio test comparing the two models is significant, indicating that the model with participant as a random effect is significantly different from the model without (χ2 (7) = 946.70, p < .001). The pattern of results remains the same in both models, however, indicating that rater effects do not alter the findings.
Discussion
Study 1 demonstrates that the linguistic characteristics of brand names – specifically, the combination of sounds, name length, and stress that convey name gender – predict perceived warmth and loyalty toward real-world brands. Feminine brand name gender predicts warmth which predicts brand loyalty. However, competence qualifies this effect such that loyalty is highest when both warmth and competence are high. This suggests that the prevalence of names with feminine name gender scores among Interbrand top brands observed in the pilot study may be due to the association between femininity and warmth, an attribute strongly predictive of brand loyalty.
Warmth and competence were positively correlated (d = .74, p < .001) consistent with prior research (Cuddy and Fiske 2004), and both were positively correlated with the feminine brand name gender, which is also consistent with recent findings that feminine stereotypes (e.g., housewives) score high in both warmth and competence (Cuddy, Fiske, and Glick 2007). This represents a shift from earlier work, which found that warm feminine stereotypes were low in competence (e.g., Fiske et al. 2002; Fiske et al., 1999), possibly parallel to the cultural shift toward valuing feminine qualities (Barry and Harper 1995).
In this study we measured competence with a single item, which is consistent with prior research (Cuddy, Fiske and Glick 2007), but prevents us from conducting analysis of
83 discriminant validity between warmth and competence. Therefore, in Study 2 we assess both warmth and competence using the extended scales. Additionally, although the results from study
1 point to warmth and competence as explanatory variables for the prevalence of feminine linguistic attributes among Interbrand top brand names, brand name gender was not manipulated in this study, so we cannot draw causal conclusions. Furthermore, participants’ prior experience with brands may have influenced the results. Therefore, in Study 2, we seek to replicate and extend these results in a controlled experiment using hypothetical brand names. This allows us to experimentally manipulate the linguistic characteristics of interest and eliminate noise related to prior brand experience.
STUDY 2
In Study 2 we asked participants to evaluate two hypothetical brand names that are carefully constructed to vary only on brand name gender. Participants also indicated how loyal they were inclined to be toward each brand, and how likely each brand is to be a ‘top’ brand. we predict that the feminine brand name will seem warmer than the masculine brand name, and warmth will increase the extent to which people feel inclined to be loyal to the brand, which in turn will increase the predicted likelihood that it is a ‘top’ brand. Thus, warmth may be a critical component of ‘top brand’ status, as reflected in the Interbrand top brand pilot results, because feelings of warmth lead to brand loyalty, which contributes to brand success (Park et al., 2010;
Watson et al., 2015). Formally:
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H2: Perceived warmth and brand loyalty will serially mediate the effect of brand name
gender on predicted likelihood of ‘top’ brand status.
Pretest
We conducted a pretest to identify hypothetical brand names that vary on name gender score while being equally and generally devoid of meaning and unfamiliar to participants. In addition to forty-five potential stimuli word pairs, another group of ten nonsense words, selected on a priori grounds to carry some semantic associations, were included to provide a benchmark for comparison and encourage participants to use the full range of response scales (Appendix B;
Schmitt et al., 1994).
Seventy-five participants were presented with a random subset of twenty-five words from the pool of fifty-five, in random order, and asked to rate how familiar and meaningful each word was on seven-point scales anchored at 1 (not at all) and 7 (very much). We selected two brand name stimuli that were rated as significantly less familiar and meaningful than both the decoy words and the midpoint of four (all p’s < .001), indicating that the brand name stimuli were not familiar or endowed with meanings that might produce confounds (see Table 1 for means and standard deviations). Moreover, the brand name stimuli this pre-test produced – Nimilia and
Nimeld – do not differ from each other in familiarity (t(51) = .10, p = .92, d = .02), or meaningfulness (t(51) = -.11, p = .91, d = .03), but Nimilia has the most feminine possible name gender score (+2), whereas Nimeld has the most masculine possible name gender score (-2).
------Table 1 about here------
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Method
Participants. Two hundred and fifty mTurk workers (55% male, Mage = 35.92) participated for Amazon.com credit.
Procedure. Participants were welcomed to the study and told that they would be evaluating hypothetical brand names. They were then presented with warmth, loyalty, and predicted top brand status measures for both names in random order. The order in which names were presented was also counterbalanced.
Predicted Top Brand Status. Participants were asked to indicate how likely they thought a brand called Nimilia [Nimeld] was to be ranked as a top brand (compared with a brand called Nimeld
[Nimilia]) on seven-point scales anchored at 1 (not at all) and 7 (very likely).
Brand Loyalty. Hypothetical brand loyalty was assessed with four measures based on Chaudhuri and Holbrook (2001) and Brakus, Schmitt, and Zarantonello (2009): “How loyal would you want to be to a brand called Nimilia [Nimeld]?” on seven-point scales anchored at 1 (not at all) and 7
(very loyal), as well as “How likely would you be to buy a brand called Nimilia [Nimeld]?”
“How likely would you be to choose a brand called Nimilia [Nimeld]?” and “How likely would you be to recommend a brand called Nimilia [Nimeld]?” on seven-point scales anchored at 1 (not at all) and 7 (very likely) (α = .87).
Warmth. We measured warmth with the same scale used in Study 1, by asking to what extent each name sounded tolerant, warm, good natured, and sincere (Fiske et al. 1999) compared with the other name, on seven-point scales anchored at 1 (not at all) and 7 (very much) (α = .88).
Competence. We measured competence using the Fiske et al. (1999) scale by asking to what extent each name sounded competent, confident, independent, competitive, and intelligent on a seven-point scale anchored at 1 (not at all) and 7 (very much) (α = .90).
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Manipulation Check. Finally, to confirm that phonetic gender score is associated with brand name gender as predicted, we asked how masculine versus feminine each name seemed on a seven-point scale anchored at 1 (very masculine) and 7 (very feminine).
Results
Manipulation Check. Paired sample t-tests show that the name with the higher name gender score (Nimilia) was perceived to be more feminine (M = 5.87, SD = 1.19) than the name with the lower name gender score (Nimeld; M = 2.76, SD = 1.64, t(249) = 22.24, p < .001, d =
2.81), confirming that the manipulation was effective.
Discriminant Validity. Analysis of discriminant validity showed that the average variance extracted between warmth and competence was greater than their squared correlation, indicating that the variables represent separate constructs. Warmth and loyalty also passed the test for discriminant validity, as did competence and loyalty. These results were consistent in all subsequent studies.
Warmth. Participants indicated that the feminine brand name sounded warmer than the masculine brand name (M = 4.49, SD = 1.32 versus M = 3.59, SD = 1.43; t(249) = 12.68, p
< .001, d = 1.60).2
Brand Loyalty. As predicted, participants indicated a stronger inclination to be loyal toward the feminine brand name relative to the masculine brand name (M = 4.45, SD = 1.36 versus M = 3.49, SD = 1.42; t(249) = 8.57, p < .001, d = 1.08).
2 Unlike Study 1, in Study 2 both warmth and competence have equally large effects on loyalty. This may be due to the within-subject design, in which participants evaluated both warmth and competence for both hypothetical brand names.
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Predicted Top Brand Status. Participants rated the feminine brand name as more likely to be a top brand than the masculine brand name (M = 4.68, SD = 1.50 versus M = 3.76, SD = 1.59; t(249) = 7.07, p < .001, d = .89).
Mediation. Within subject mediation analysis using the MEMORE macro (Montoya and
Hayes in press; Judd et al. 2001) confirmed that warmth mediates the difference between masculine and feminine brand names on inclination toward brand loyalty (β = .79, 95% CI =
[.59, 1.01] with 5,000 bootstrapped resamples). MEMORE macro analysis also shows that warmth and loyalty serially mediate the difference between masculine and feminine brand names on predicted top brand status (β = .73, 95% CI = [.68, 1.18] with 5,000 bootstrapped resamples), supporting H2 (Figure 2).
------Figure 2 about here------
Importantly, an alternative order of mediation, from loyalty to warmth is not significant
(β = .02, 95% CI = [-.05, .12] with 5,000 bootstrapped resamples). Similarly, using the manipulation check measure of how feminine vs. masculine each name seemed to test whether perceived warmth leads to gender associations shows that this alternate order of mediation is also not supported (β = -.05, 95% CI = [-.13, .02] with 5,000 bootstrapped resamples). Thus, only the predicted order of effects is supported, such that brand name femininity enhances warmth, which increases inclination toward brand loyalty and predicted top brand status.
Given the moderating role of competence found in Study 1, we reran the analysis to separately examine those who perceived the brands as competent and those who did not. When participants perceived the brands to be of at least average competence (i.e., rated 4 or above on the seven-point scale), the aforementioned pattern of effects holds (β = .36, 95% CI = [.19, .57] with 5,000 bootstrapped resamples). However, when participants perceived the brands to be
88 below average in competence (i.e., rated below 4 on the seven-point scale), the observed effects became nonsignifcant (β = .16, 95% CI = [-.004, .79] with 5,000 bootstrapped resamples).
Discussion
Study 2 shows that feminine brand names seem warmer than masculine ones, and warmth leads people to be more inclined toward brand loyalty, and to predict top brand status. This pattern of results replicated in a study with the variables measured in reverse causal order (i.e., predicted top brand status was measured first, followed by loyalty, and then warmth), and in a third study where warmth and competence were measured on a single semantic differential scale.
The consistently robust results, and large effect sizes, suggest that the influence of brand name gender is not trivial.
However, this study only examines hypothetical brands that do not belong to any particular product category, and it is possible that feminine brand name gender is more beneficial in some product categories than others. Indeed, research has shown that warmth is a more valued attribute for hedonic than utilitarian products (Chattalas 2015). Therefore, in Study 3, we examine the moderating role of product category. In addition to examining the role of product category, we also seek to replicate the results of Studies 1 and 2 using a between-subject experimental design. Following the procedure used in Study 1, we ask participants to evaluate hypothetical brand names in terms of warmth, brand loyalty, and predicted top brand status. we predict that feminine brand name gender will increase perceived warmth, which will increase brand loyalty, as in Study 2, but this effect will be stronger for hedonic products than for utilitarian products. Thus:
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H3: Brand name gender will have a larger effect on loyalty toward hedonic than
utilitarian products.
STUDY 3
In Study 3 we randomly assign participants to either a hedonic or utilitarian product condition, and then, following on the procedure used in Study 2, ask them to indicate how warm a hypothetical brand sounds, how loyal they would want to be to that brand, and how likely it is to be a top brand in its category using a 2 (brand gender: masculine or feminine) x 2 (product category: hedonic or utilitarian) between-subjects design.
Pretests
We conducted pretests to identify a hedonic product category that is not also utilitarian, and a utilitarian product category that is not also hedonic, and to ensure that both products are perceived to be equally masculine or feminine so that the effect of brand name gender is not confounded with product gender. we examined thirty-three products based on previous studies
(e.g., Lu, Liu, and Fang 2016; Yeung and Wyer 2004) and assessed hedonic and utilitarian qualities, using scales developed by Voss, Spangenberg and Grohmann (2003) by asking participants to indicate how “fun (exciting, delightful, enjoyable)” each product was on a seven- point scale anchored at 1 (NOT fun) and 7 (FUN), and how “practical (helpful, functional, effective)” on a seven-point scale anchored at 1 (NOT practical) and 7 (PRACTICAL). We also asked how masculine versus feminine each product seemed on seven-point scales anchored at 1
(masculine) and 7 (feminine). The order of all measures was randomized. The goal was to
90 identify a product category that is only hedonic and a product category that is only utilitarian, both of which are equally masculine/feminine. Chocolate and bathroom scale met these criteria because chocolate was considered hedonic (M = 5.71, SD = 1.30; t(83) = 12.14, p < .001, d =
2.65) but not utilitarian (M = 3.46, SD = 1.95; t(83) = -2.54, p = .01, d = .55), whereas bathroom scale was considered utilitarian (M = 5.10, SD = 2.02; t(22) = 2.48, p = .02, d = 1.08) but not hedonic (M = 2.57, SD = 1.50; t(22) = -4.58, p < .001, d = 1.91). Importantly, both are rated as significantly more feminine than masculine (chocolate: M = 4.90, SD = 1.07; t(81) = 7.62, p
< .001, d = 1.68; bathroom scale: M = 4.63, SD = .97; t(22) = 3.16, p = .004, d = 1.30), and equally feminine to one another (t(22) = -3.19, p = .18, d = .57), such that product gender is controlled for.
Method
Participants. Seven hundred and eighty-one mTurk workers (53% male, Mage = 34.12) participated for Amazon.com credit.
Procedure. Participants were randomly assigned to a condition in a 2 (brand name gender: feminine or masculine) x 2 (product category: utilitarian or hedonic) between-subject design. Participants were first asked to indicate how likely it was that the brand was a ‘top’ brand in its product category. Next, they completed the same four loyalty measures used in Study 2 (α
= .93). Then the competence (α = .93) and warmth (α = .92) measures used in Study 2 were presented in random order. Finally, as a manipulation check, we asked how masculine versus feminine the hypothetical brand seemed, on seven-point scales (1 = very masculine and 7 = very feminine), followed by standard demographic questions.
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Results
Manipulation Check. Paired sample t-tests confirmed that the name with the feminine name gender score was rated as more feminine (M = 5.75, SD = 1.05) than the name with the masculine name gender score (M = 2.94, SD = 1.43, t(780) = 40.69, p < .001, d = 2.91), confirming that the manipulation was effective.
Replications. As in Study 2, warmth and loyalty serially mediated the effect of brand name gender on predicted top brand status (Hayes PROCESS model 6, 95% CI = [.26, .43] with
5,000 bootstrapped resamples), providing a replication with a between-subjects design and specific, rather than ambiguous, product categories. Furthermore, as in Study 1, competence moderated the indirect effect of name gender on loyalty (Hayes PROCESS model 14, 95% CI =
[.006, .07] with 5,000 bootstrapped resamples), providing a controlled experimental replication.
Product Category Moderation. The effect of name gender on loyalty was partially moderated such that hedonic versus utilitarian product category moderated the effect of brand name on predicted top brand status through loyalty (Hayes PROCESS model 7, index of moderated mediation 95% CI = [.03, .53] with 5,000 bootstrapped resamples) but not warmth
(Hayes PROCESS model 7, index of moderated mediation 95% CI = [-.04, .07] with 5,000 bootstrapped resamples).
Brand Loyalty. To better understand the results, we ran analysis of variance to examine the effects of brand name and product category on brand loyalty. There was a significant main effect of name (F(1,777) = 61.33, p < .001, η2 = .07), no effect of product category (F(1,777) =
1.69, p = .19, η2 = .002), and a significant product category by name interaction (F(1,777) = 4.88, p = .02, η2 = .006). When the brand name was masculine, it made no difference whether the product was hedonic (M = 3.51, SD = 1.24) or utilitarian (M = 3.42, SD = 1.27; F(1,417) = .46, p
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= .50, η2 = .001), but when the brand name was feminine, not only was the inclination toward brand loyalty generally higher, it was also higher for hedonic than utilitarian products (M = 4.35,
SD = 1.24 vs. M = 4.02, SD = 1.37; F(1,360) = 5.49, p = .02, η2 = .02).
Predicted Top Brand Status. Analysis of variance examining the effects of brand name and product category on predicted top brand status showed a similar but reversed pattern of results. There was a significant main effect of name (F(1,777) = 95.97, p < .001, η2 = .11), no effect of product category (F(1,777) = .06, p = .81, η2 < .001), and a significant product category by name interaction (F(1,777) = 11.81, p = .01, η2 = .007). In this case, when the brand name was masculine, the utilitarian product was significantly more likely to be the predicted top brand in its category (M = 3.60, SD = 1.34) than the hedonic product (M = 3.33, SD = 1.40; F(1,417) =
4.08, p = .04, η2 = .01), but when the brand name was feminine, both hedonic and utilitarian products were predicted to be equally likely to be top brands (M = 4.57, SD = 1.41 vs. M = 4.35,
SD = 1.53; F(1,360) = 2.06, p = .15, η2 = .006). Together these results support H3 (Figure 3).
------Figure 3 about here------
Discussion
Study 3 replicates the results of Studies 1 and 2. The present study also demonstrates the moderating role of product category, showing that feminine brand names benefit hedonic products more than utilitarian ones, possibly because warmth is a more valued attribute for hedonic than utilitarian products.
The previous studies have examined product categories that are used by both men and women. However, research suggests that when a product is typically used by men rather than women, feminine brand names should not be an advantage (Cassidy et al 1999; Yorkston & De
Mello 2005). Therefore, in Study 4, we examine both products that are typically used by men
93 and typically used by women. The previous studies have also relied on one set of brand name stimuli, which vary in length. It is possible that the results were due to some idiosyncratic quality of the names, or that name length may have some unintended effects, for instance through metaphorical associations (Mehrabian and Pierce 1993). Therefore, in Study 3 we rule out these possibilities by testing additional brand name stimuli and controlling for name length.
We predict that feminine brand names will be preferred when the typical product user is a woman, but not when the typical product user is a man. Specifically,
H4: Typical user gender will moderate the effect of brand name gender on loyalty such
that feminine brand names will be preferred for products typically used by women, but
not for products typically used by men.
STUDY 4
Pretest
We conducted a pretest to identify brand name stimuli that vary on name gender score while being equally and generally devoid of meaning and unfamiliar to participants, following the same procedure used in Study 2. We selected four names that were rated significantly unfamiliar and not meaningful (all p’s < .001), and equally familiar (all p’s > .80) and meaningful (all p’s > .40) with each other. Two of the names – Wolda and Steda – were moderately feminine (+1), and the other two names – Woldard and Stelad – were moderately masculine (-1) based on the name gender score (Barry and Harper 1995). Because the names are less masculine and feminine than in Studies 2 and 3, these stimuli offer a more conservative test
94 of the name gender effect. Moreover, the names are all uniformly two syllables, to control for possible metaphorical confounds with name length.
Method
Participants. Four hundred and fifty-two students at a public Midwestern university (55% male, Mage = 20.64) participated for course credit.
Procedure. Participants were randomly assigned to evaluate one hypothetical brand in a 2
(brand name gender: feminine or masculine) x 2 (typical user gender: male or female) x 2
(product type: hedonic or utilitarian) between-subject design. The product stimuli were athlete’s foot cream (utilitarian) and cologne (hedonic) – both typically used by men – and nail polish remover (utilitarian) and perfume (hedonic) – both typically used by women. Participants were welcomed to the study and asked to answer the questions based on how they imagined they would feel about an [athlete’s foot cream / cologne / nail polish remover / perfume] brand called
[Stelad / Woldard / Steda / Wolda]. Then they completed the warmth (α = .88), competence (α
= .89), and top brand status measures used in Studies 2 and 3. Participants also completed the loyalty measures (α = .89) used in Studies 2 and 3, except likelihood to recommend was replaced with a measure of likelihood to pay more because research suggests that willingness to pay a premium is a market of brand loyalty (Chaudhuri and Holbrook 2001), however we expect the same pattern of results from our previous loyalty measures to replicate. The order of all measures was randomized. As manipulation checks, we asked participants to indicate the most typical user of the product they evaluated [athlete's foot cream; nail polish remover; perfume; cologne] from among three choices: Men (coded -1), Women (coded 1), or Both (coded
0). We also asked how “fun or enjoyable” and “practical or functional” the product was, on a
95 seven-point scale anchored at 1 (not at all) and 7 (very much). Finally, we asked how masculine or feminine each hypothetical brand seemed, on seven-point scales anchored at 1 (very masculine) and 7 (very feminine).
Results
Manipulation Checks. As expected participants rated athlete’s foot cream and cologne as more typically used by men (MFoot Cream = -.75, SD = .49; MCologne = -.79, SD = .47) than nail polish remover and perfume (MPolish Remover = .91, SD = .38; MPerfume = .82, SD = .46). Participants in the hedonic conditions rated the products they evaluated as more fun and enjoyable than those in the utilitarian conditions, who rated the products they evaluated as more practical or functional than those in the hedonic conditions (all p’s < .001). Finally, participants in the feminine brand name conditions rated the names they evaluated as more feminine (MFeminine = 4.56, SD = 1.02) than those in the masculine brand name conditions (MMasculine = 3.18, SD = 0.98; t(450) = -14.69, p < .001, d = 1.38). Evaluations were averaged to form composite warmth, competence, loyalty, and top brand scores for masculine and feminine names.
Replications. As in Studies 2 and 3, warmth and loyalty serially mediated the effect of brand name gender on predicted top brand status (Hayes PROCESS model 6, 95% CI = [.09, .28] with 5,000 bootstrapped resamples). However, unlike Study 1, competence only conditionally moderated the indirect effect of name gender on loyalty; specifically, when the product was utilitarian competence moderated the indirect effect and warmth was not a significant mediator
(Hayes PROCESS model 18, 95% CI = [-.02, .07]) but when the product was hedonic competence did not moderate and the mediating role of warmth was significant (95% CI =
[.01, .10] with 5,000 bootstrapped resamples).
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Brand Loyalty. Analysis of variance revealed a significant three-way interaction brand name gender x typical user gender x product type (F(1,444) =5.66, p = .02, η2 = .01; Table 2) and no other significant interactions or main effects. Follow-up analysis revealed a significant interaction of name gender x typical user gender when the product was hedonic (F(1,208) =6.04, p = .01, η2 = .03) but not when the product was utilitarian (F(1,236) =6.04, p = .37, η2 = .003).
One-way analysis of variance showed that participants were more inclined to be loyal toward a brand with a feminine rather than masculine name when the product was hedonic and typically used by a woman, i.e., perfume (MFeminine = 3.35, SD = 1.49 vs. MMasculine = 2.65, SD = 1.23;
F(1,99) =6.71, p = .01, d = .52). However, there was no effect of brand name gender when the product was hedonic and typically used by a man, i.e., cologne (MFeminine = 2.71, SD = 1.31 vs.
MMasculine = 2.92, SD = 1.44; F(1,110) =.72, p = .39, d = .16).
------Table 2 about here------
Discussion
Study 4 lends support to the results of Studies 1, 2, and 3 and also demonstrates the moderating role of typical user gender. The feminine brand name advantage is driven by perceived warmth, is greater for hedonic than utilitarian products, and is neutralized when the typical product user is male.
The previous studies have examined product categories for which brand warmth is an asset. However, the previous pattern of effects should be reversed if warmth is an undesirable attribute for the product. Therefore, in Study 5, we examine a product for which warmth is not a desirable attribute – combat firearms. We predict that the feminine brand name advantage will be reversed when warmth is an undesirable product attribute, and therefore masculine brand names will be preferred for combat firearms. Specifically,
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H5: Participants will prefer masculine brand names when warmth is an undesirable
product attribute.
STUDY 5
Method
Participants. Three hundred and ninety-one students at a public Midwestern university
(57% female, Mage = 20.61) participated for course credit.
Procedure. Participants were randomly assigned to evaluate one of six brand names selected from the pretests conducted in Studies 2 and 3 (feminine: Stelada, Wolda, and Nimilia / masculine: Stelad, Woldard, and Nimeld). After being welcomed to the study participants were asked to imagine that the military wanted to know their opinion about a brand of combat firearm; specifically, a gun they would use to shoot an enemy who threatened their life. They were then shown one of the six brand names and asked to complete the same warmth (α = .85), competence
(α = .91), loyalty (α = .95), and top brand status measures used in Studies 2 and 3, in random order. As manipulation checks, we asked participants how masculine or feminine each brand name seemed, on seven-point scales (1 = very masculine and 7 = very feminine).
Results
Manipulation Check. Participants rated the feminine names as more feminine than average (MStelada = 5.51, SD = 1.45; MWolda = 5.19, SD = 1.55; MNimilia = 5.64, SD = 1.28) and the masculine names as more masculine than average (MStelad = 2.51, SD = 1.45; MWoldard = 2.49, SD
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= 1.39, MNimeld = 2.62, SD = 1.44; all p’s < .001). Analysis revealed no stimuli effects, so evaluations were averaged to form composite warmth, competence, loyalty, and top brand scores for masculine and feminine names.
Replications. Unlike in the previous studies, competence but not warmth mediated the effect of brand name gender on loyalty (Hayes PROCESS model 4, 95% CI competence =
[.61, .78] versus CI warmth = [-.02, .15] with 5,000 bootstrapped resamples). Competence and loyalty serially mediated the effect of brand name gender on predicted top brand status (Hayes
PROCESS model 6, 95% CI = [-.24, -.05] with 5,000 bootstrapped resamples), and warmth did not moderate the indirect effect of name gender on loyalty through competence (Hayes
PROCESS model 14, 95% CI = [-.04, .003] with 5,000 bootstrapped resamples).
Brand Loyalty. Analysis of variance revealed a significant main effect of brand name gender on loyalty (F(1,385) = 8.11, p = .005, η2 = .02) such that masculine brand names were preferred for combat firearms over feminine brand names (MMasc = 4.21, SD = 1.55 vs. MFem =
3.78, SD = 1.47).
Warmth and Competence. As before, warmth and competence were both correlated with loyalty, however this time the effect of competence on brand loyalty was greater (d = .67, 95%
CI [1.58, 2.05]) than the effect of warmth (d = .23, 95% CI [.26, .66]), and the confidence intervals around these effect sizes do not overlap, indicating that the effect of competence is significantly larger than the effect of warmth (Fritz, Morris, and Richler 2012).
Participant Gender. As in Studies 1 – 3, participant gender had no effect of on loyalty
(F(2, 386) = .11, p = .49, η2 < .001) and did not interact with brand name gender.
Discussion
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Study 5 shows that the advantage of feminine brand name only occurs when warmth is a desirable attribute. The effect reverses, and masculine names elicit greater loyalty, when warmth is an undesirable product attribute, as is the case for combat firearms. Under this condition, competence – rather than warmth – drives the positive effect of masculine brand name on loyalty, and warmth does not moderate the indirect effect. This represents a rare scenario, therefore, where warmth and competence do not interact to stimulate affiliation, and warmth is not the primary driver of loyalty.
GENERAL DISCUSSION
Summary and Implications
This research reveals important antecedents of brand loyalty – brand name gender, perceived brand warmth, and competence. The present studies offer convergent evidence that feminine brand name gender increases perceived warmth, which increase inclination toward loyalty for hypothetical brands, and self-reported loyalty for real brands. Loyalty, in turn, increases the predicted likelihood that a hypothetical brand is a ‘top brand,’ suggesting that the prevalence of feminine names among Interbrand top brands may be due to the way brand name linguistics inspire warmth and loyalty. Importantly, this effect is neutralized when the typical product user is male, and reversed when warmth is not a desirable product attribute. We show these effects both empirically, in experiments using hypothetical brands, and in observational studies using real brands, and comparing Interbrand top brands with less successful brands. To the best of our knowledge, this research is the first to demonstrate a link between brand name and brand loyalty.
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The present work contributes to the warmth / competence literature by showing the importance of warmth, which has an even larger effect than competence, for brand loyalty. We also demonstrate the role of warmth and competence in the marketing domain of consumer loyalty. The present work finds that, consistent with more recent results (e.g., Fiske et al., 2007), warmth and competence are both highly correlated with the feminine concept. This may represent a social shift among Western attitudes toward femininity.
The present research contributes to the literature on utilitarian and hedonic products by showing that feminine brand names better convey desirable warmth attributes for hedonic products (relative to masculine names). This work has important substantive implications for brand managers, finding that feminine brand names have a marketplace advantage, particularly for hedonic products. This work should therefore inform best naming practices. Brand managers of hedonic products should take careful note of the linguistic characteristics of new brand names and brand extensions.
This work also contributes to our understanding of brand name linguistics by showing that phonetics, length, and stress together influence brand perceptions and loyalty. Whereas previous research has focused almost exclusively on brand name phonetics, in isolation, we find that many linguistic qualities of a name can influential consumer perceptions. Moreover, these linguistic qualities cannot be considered in isolation.
Further Research
Future research should investigate how brand name linguistics fit within the nomological network of brand loyalty. For instance, it would be useful to examine the relationships between brand name linguistics and antecedents of loyalty such as brand attachment, and related
101 constructs such as brand attitude strength (Park et al., 2010). Relatedly, it would be useful to learn whether the relatively heuristic nature of brand name has a greater influence on low-effort consumer behaviors (e.g., wearing the logo) relative to higher effort behaviors (e.g., waiting to purchase a desired brand rather than a competitor; Park et al., 2010). Future work should also investigate the downstream consequences of brand name linguistics on brand equity, including unit price, number of units sold, and unit marketing costs.
Research might also examine whether brand name linguistics are differentially influential at different stages of the brand relationship. This may be relevant because in the relationship establishment stage it may be more important for a brand to convey positive attributes both heuristically and via more thoughtful processing, whereas at the brand attachment stage consumers may rely less on heuristics such as brand name. Thus, further research on the role of brand name linguistics in consumer-brand relationships is needed.
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APPENDIX A Name Gender Scoring System (Barry and Harper 1995)
Scale One: +2: The accent is on the second or later syllable (e.g., Nicole, Sebastian). +1: The accent is on the first of three or more syllables (e.g., Brittany, Christopher). 0: The accent is on the first of two syllables and the name has fewer than six phonemes (Mary, Michael). -1: The name has one syllable (e.g., John, James) -2: The accent is on the first of two syllables and the name has six or more phonemes (e.g., Robert, Edward)
Scale Two: +2: The last phoneme is a schwa (e.g., Donna, Joshua). +1: The last phoneme is any vowel except schwa (e.g., Ashley, Andrew). 0: The last phoneme is m, n, ng, r or l (e.g., Kathleen, Tyler). -1: The last phoneme is f, v, th, s, z, sh, ch, or j (e.g, Joseph, George). -2: The last phoneme is p, b, t, d, k, or g (e.g., Philip, Jeb).
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APPENDIX B Brands Used in Experiment 1 Listed in Order of (Un)Popularity
Well-Liked Brands Disliked Brands
Nike Pepsi Samsung Crocs Sony Lacoste Google Red Bull Adidas JC Penny Coca Cola Gucci Microsoft Lenovo Under Armour McDonalds Amazon Prada Levi's Ed Hardy Coach Victoria’s Secret LG Abercrombie & Fitch Tesla Beats Bmw Comcast Louis Vuitton Ford Nintendo Sears Chanel Kia Amd Kraft Asics Nissan Asus Old Navy Columbia Starbucks Converse Suave Tide Target Yamaha Walmart Skullcandy Gap
APPENDIX C Decoy Stimuli Used in Pretest for Study 2
Banda Pimabella Bordwok Byepod Dawnuld Bootea Bowntie Boogy Boomingstorie Bohuntur
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Figure 1 Indirect Effect of Brand Name Gender on Brand Loyalty through Warmth, Moderated by Competence
Competence Warmth
.06***
.05* .27***
Brand Name -.01 Brand Loyalty Gender
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Figure 2 Indirect Effect of Brand Name Gender on Predicted Top Brand Status through Warmth and Brand Loyalty
Warmth .60*** Brand Loyalty
.93*** 1.33***
Top Brand Brand Name -.007 Status Gender (predicted)
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Figure 3 Moderating Effect of Hedonic vs. Utilitarian Product Category
Inclination Toward Brand Loyalty Predicted Top Brand Status 7 7 6 6 5 * Utilitarian 5 4 * Utilitarian Hedonic 4 3 3 Hedonic 2 2 1 1 Masculine Name Feminine Name Masculine Name Feminine Name
114
Table 1 Study 2 Stimuli Pretest Means (and Standard Deviations)
Name Meaningfulness Familiarity Nimeld 1.58 (1.30) 1.69 (1.41) Nimilia 1.60 (1.18) 1.67 (1.31) Decoy Words 2.74 (1.59) 3.02 (1.84)
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Table 2 Moderating Effects of Typical User Gender and Product Category
Masculine Feminine Brand Name Brand Name
Utilitarian Product Typical Male User 2.95 3.22 Typical Female User 2.94 2.88 Hedonic Product Typical Male User 2.93 2.71 Typical Female User 2.65 3.35