Measuring the Strength

Of Color Brand-Name Links

The Comparative Efficacy

Of Measurement Approaches

JENNI ROMANIUK

Ehrenberg-Bass Institute

Jenni@marketingscience. info

MAGDA NENYCZ-THIEL

Ehrenberg-Bass Institute

Magda. Nenycz-Thiel@

marketingscience.info

This study provides a theoretically and empirically validated approach to measuring the

strength of color as a brand-identity element. The authors conducted a split sample

test with 880 consumers across three categories: banking, chocolate, and hair care.

Comparing four measurement approaches helped determine the effect of cuing with

the brand versus color (cue direction) and prompting with response sets versus not

prompting (difficulty of response). The key comparison measures were the number of

people who linked the brand with color (fame) and the relative presence of competitor

links (uniqueness). The color-cued, unprompted brand response measure is the

recommended approach.

INTRODUCTION

In today's cluttered media environment, one of the key challenges for brands is to stand out in the mar­ket place. With new stock-keeping units introduced into retail stores every week, distinctive packaging may help increase sales by enabling consumers to recognize and choose a brand over its competitors (Yang and Raghubir, 2005).

Distinctiveness is a function of the strength and uniqueness of the elements that form a brand's identity. These elements may include colors, logos, characters, and taglines—anything that triggers the brand name in consumer memory. When creating a distinct identity, decisions about the importance

of various distinctive elements—label, brand name, product description, or color—can be crucial to brand success (De Chernatony and McDonald, 1998). "Many times, multiple attributes will appear to be equally important. It is tough to make a deci­sion about what to keep, what to put priority on, what to subdue and what to discard" (Meyers et al., 1998, p. 63).

To guide brand-management decision making, practitioners, therefore, need correct measurement approaches and appropriate metrics to assess the distinctive strength of the various brand elements. Such knowledge also could aid academic research­ers exploring the role of brand-identity elements.

• To measure the brand linkage strength of colors, marketers should provide respondents with the color and ask which brands are linked to that color, without prompting respondents with brand names.

• Prompting for brand names encourages guessing and provides inflated assessments of brand- identity strength.

• In this research, colors are tested, but marketers can use this approach to test the strength of other brand-identity elements, such as taglines or logos.

DOI: 10.2501/JAR-54-3-313-319 September 2014 JO U B flM . DF HDUERTISIflG RESEARCH 313

MEASURING THE STRENGTH OF COLOR BRAND-NAME LINKS

In to d a y ’s c lu tte re d m e d ia e n v iro n m e n t, o n e o f th e key

c h a lle n g e s fo r b ran d s is to s ta n d o u t in th e m a rk e t p la ce .

Distinctive elements create a network of cues—beyond the brand name—that combine to evoke the brand in consumer memory. These elements often engage different neurological aspects—among them, audio memory, colors, shapes, or faces—and, therefore, the ability to extend the richness of category buyers' brand- information processing.

This network of additional cues may increase correct brand identification in advertising (Romaniuk et ah, 2007). In cases such as much of Nike advertising, where only the "swoosh" is shown, this brand identification can happen even in the absence of the brand name.

To contribute to brand identification, the link between the element and the brand name must easily be retrievable from consumers' long-term memory. Among the most widely accepted theories about the structure of human memory are the Associative Network Theories of Memory (ANT; e.g., Anderson et ah, 1988).

These theories suggest that concepts are stored in memory as nodes that can become linked together if encountered in similar circumstances. When assessing the strength of a link between two concepts, ANT highlights three areas of importance:

• the cue chosen for retrieval,• the presence of competitor links, and• the difficulty of the retrieval process.

The current research integrates these areas, contrasting the outputs from four resultant measurement approaches, spe­cifically in the context of color as a brand- identity element.

Color is a popular element used to build a brand identity (Klink, 2003), and the current study focuses on its strength as a brand-building component. Examples of brands building strong identities around color include Tiffany's blue or Coca-Cola's use of red. The importance of color use is emphasized through the attempts by com­panies to try to trademark specific colors, such as Cadbury with the color purple (Playle and Hodson, 2003).

Before a color is registered, singular own­ership needs to be established. When multi­ple colors are used by a brand and multiple brands use the same color, ownership is difficult to assert, hence the importance of a validated measurement approach.

B A C K G R O U N D A N D R E S E A R C H

Q U E S T IO N S

T h e R o le o f C o lo r

In S h a p in g a B r a n d ’s Id e n t ity

Color is one of the most common and prominent facets of a brand's identity (Klink, 2003). The role of colors in creating meaning and evoking emotion has been a frequent topic of research. When colors are changed, such as when Apple changed its logo from red to silver, consumers often react (Hynes, 2009).

Two major areas where color has an impact on brand identity are packaging/ retail outlets and advertising/marketing communications.

C o lo r U s e in P a c k a g in g /R e t a i l O u tle ts

Although most consumers have a reper­toire of brands they consider before pur­chase, they often make their final selection in stores (Dreze et ah, 1994). A successful

314 JD U R R R L O F R D U E R T I5 M G R E S E A R C H September 2014

example of establishing a distinctive color identity in a retail setting is Christian Dior, whose products can be recognized at a dis­tance by their consistent pink color (Kes­sler, 2004). The more people link the color pink to Christian Dior, the more easily con­sumers will correctly identify this display. Colors, therefore, are critically important because they help consumers "see" brands.

Color can convey meaning to the cus­tomer. Consider the claim that "60 percent of the first impression [of a new product or in-store display] comes from color" (Heath, 1997, p. 44). Moreover, variants of a brand often include colors that con­vey meaning about taste (red for tomato) or scent (yellow for lemon). As these variants often are common across brands, there is the potential for brand identities to converge. For example, many laundry detergents offer lemon-, lavender-, and pine-scented variants. If all lemon-scented variants are yellow, all lavender-scented variants are purple, and all pine-scented variants are green, then brand colors will be very similar. This potential for conver­gence makes it important that a measure of brand-identity strength includes the possibility for competitive links to identify overlap with competitor brands. Brand managers need to understand the mean­ing conveyed by color and how that color may contribute to an identity that is dis­tinct from competitors.

A d v e r t is in g a n d O th e r M e s s a g in g

R o le s o f C o lo r

Color can be used as a background to the advertisement or on creative elements within an advertisement (i.e., Kellogg's Special K®'s use of red dresses on the women featured in advertising). Although an advertisement rarely contains multiple brands, it may contain multiple colors. If a prominent color evokes a competitor brand, there is the risk that consumers incorrectly will brand the advertising.

MEASURING THE STRENGTH OF COLOR BRAND-NAME LINKS

C o lo r is o n e o f t h e m o s t c o m m o n a n d p r o m in e n t

f a c e t s o f a b r a n d ’s id e n t i t y . I t c a n b e u s e d

a s a b a c k g r o u n d t o t h e a d v e r t is e m e n t o r o n

c r e a t iv e e le m e n t s w ith in a n a d v e r t is e m e n t .

Logos also rely on color to create a dis­tinct, recognizable identity. One research scenario analyzed how a strong logo needs to be recognizable and familiar and have a shared meaning across consumers (Henderson and Cote, 1998). This means it would be advantageous that logo color should have strong links to the brand name to help facilitate these objectives.

In relation to packaging, color in a logo also can evoke emotion and influence the interpretation of the logo (Hynes, 2009). Although color may contribute to the meaning of a logo, color often can confuse a consumer: If multiple organizations use the same set of colors to evoke similar attractive emotions relevant to the cate­gory (Lee and Barnes, 1990), the consumer may get mixed messages. For example, energy drink brand managers may think it desirable to use bright, stimulating colors to reflect their sub-category. If too many brands, however, use the same dynamic color palate, the results both may include a reduced set of color options for brands to use and a greater likelihood of overlap, thereby reducing uniqueness.

Brand-Identity Metrics

Brands build up links to brand-identity elements through consumers' learning over time. Learning occurs when the con­sumer processes co-presentation of the elements and the brand name. In line with ANT (e . g Anderson et a]., 1988), when associative links are established, the brand name has the potential for retrieval when consumers see the identity element.

There are, however, factors that interfere with this process:

• Inattentiveness of consumers at encod­ing, referred to as "encoding failure" (e.g., Anderson et al, 1988). For example, if the consumer fails to process that Shell uses the color yellow, any links in mem­ory are too weak to meet the activation threshold required for retrieval.

• Competitor links (e.g., Burke and Srull, 1988). For example, if BP also were to use yellow as one of its brand-identity elem­ents, the consumer may link both BP and Shell to yellow and can retrieve either or both when presented with yellow.

These two factors mean that simply using an element in marketing activity does not ensure the creation of strong links to the brand name in consumer memory and that any measurement approach needs to

• incorporate a test of retrieval strength, and

• consider the role of competitor interference.

Knowledge about human memory pro­cesses also informs the metrics—fame and uniqueness—that the authors of the cur­rent study used to assess of the strength of brand-identity elements:

• Fame reflects how many people can retrieve the link between the identity element and the brand name. This draws

on the fact that retrieval of an item from memory depends first on having a link to the cue used to stimulate memory (Tulving and Pearlstone, 1966).

The higher the fame of the link between the brand and the color in the population, the more people have a chance of retrieving the brand in future situations, when the color is present. Lower fame means greater risk of brand- identification failure.

• Uniqueness captures the competitive­ness of other items/brands linked to the same cue. Other items linked to the cue interfere with retrieval, thus making it less likely that the target item will be retrieved (Heil et al, 1994).

For example both M acDonald's and Burger King use yellow in their logos, so that when MacDonald's uses yellow, consumers may have a chance of retrieving Burger King. M easuring uniqueness allows for the quantification of this chance of evoking competitors.

When measuring fame and uniqueness, two important methodological decisions comprise the cue:

• the brand or color, and• whether the responses (either brands or

colors) are provided or elicited by con­sumers unprompted.

The cue used determines the competitive set for retrieval. The wider the competi­tive set, the more difficult the retrieval task for any one item. In one direction, there are potential colors linked to the brand. In the other direction, there are the potential brands linked to a color. The varied sizes and natures of these two retrieval universes may affect the items retrieved from memory.

Therefore, the first research questions are:

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MEASURING THE STRENGTH OF COLOR BRAND-NAME LINKS

RQ1: What is the impact of the cueused to measure the prevalence of the link between a color and a brand name?

RQ2: What is the impact of the cueused to measure the uniqueness of the link between a color and a brand name?

When the response set is provided, retrieval is an easier process. In such instances, the information should increase the overall number of responses. As one scenario showed, however, when cued retrieval fails, there were three processes respondents can use to match brands (Pham and Johar, 1997):

• "memory-trace refreshment," in which respondents try to reconstruct the mem­ory trace, and

• "schematic inferencing," in which respondents use reasoning to reach an answer.

• Pure guessing is the third process, and its very nature will lead to lower accuracy. Prompting for responses makes it easier for respondents to guess and, therefore, may increase the proportion of guesses consumers make.

The effect of providing responses, and the possibility of guessing leads to the next set of research questions:

RQ3: What effect does promptingfor the response set have on the fame response patterns for brand/color links?

RQ4: What effect does prompting forthe response set have on the uniqueness response patterns for brand / color links?

RQ5: Which measurement approachesmore likely will lead to guessing?

METHODOLOGY

Research Design

This study utilized a 2 x 2 between- subjects design.

The first factor was cue type: brand name or element, and the second factor was the response format: prompted or unprompted. After being screened for cate­gory usage, respondents were asked ques­tions about three categories, which were hair care, chocolate, and banking. These three categories covered products and services, as well as routine and impulse product purchases and were chosen for the purpose of replication and to test the generalization of the results.

For each category, each individual responded to a different treatment to ensure no learning effects. All analyses were conducted between subjects. The data were collected online, as this pro­vided the opportunity to show colors and brand names where appropriate.

In the prompted treatment, respondents were provided with the color or brand cue and lists of possible responses. In addition, there was an open-ended text box to write any other responses. In the unprompted treatment, only open-ended text boxes were provided. All questions allowed for multiple responses, with a "none-of-these" option provided to dis­courage guessing.

The color block stimuli also included the name of the color (e.g., lighter blue) to mini­mize the variability in color perceptions between respondents. The order of presen­tation was randomized across respondents.

The sample for this study was recruited randomly from a large Australian city via an opt-in panel. A quota on gender and age was employed to ensure that the sam­ple was representative of the population.

A total of 880 respondents completed the survey online, which provided samples of approximately 200 respondents per cell for each treatment. The data collection took place in October 2009.

Metrics

The two metrics—fame and uniqueness— were calculated across the four treatments for each category for brand/color combi­nations that had large enough sample sizes for a brand (n > 20). This provided 9 pairs for banking, 22 pairs for chocolate, and 20 pairs for hair care.

The following equations describe the metrics:

• Fame is the proportion of people who link the brand to the color measured as:

N people who linked the brand to the color N of sample

For example, if 30 percent of consumers recall the brand when prompted with green, then it has 30 percent fame.

• Uniqueness is the proportion of responses one brand gets relative to competitors, measured as:

The number of times the brand is linked to the element

The number of times any brand in the category is linked to the element

For example, if green as a cue has 30 percent of people recalling the brand, but a further 10 percent asso­ciate the color to other brands, this is 30 percent/(10 percent + 30 percent) or 75 percent uniqueness.

RESULTS

The results showed high and statistically significant Pearson's correlations between the two prompted approaches for both fame and uniqueness (over 0.90; See Table 1):

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MEASURING THE STRENGTH OF COLOR BRAND-NAME LINKS

TABLE 1Pearson’s Correlations between Treatments

Banking Chocolate Hair Care

PBC# PEC UPBC PBC PEC UPBC PBC PEC UPBC

FamePEC 0 .9 2 * 0 .9 4 * 0 .9 2 *

UPBC 0 .9 6 * 0 .9 0 * 0 .8 3 * 0 .8 3 * 0 .9 9 * 0 .9 1 *

UPEC 0 .8 2 * 0 .9 6 * 0 .8 3 * 0.33 0 .51* 0.32 0 .7 9 * 0 .7 7 * 0 .7 7*

UniquenessPEC 0 .9 4 * 0 .9 6 * 0 .9 5 *

UPBC 0.61 0.56 0 .9 8 * 0 .9 6 * 0 .9 2 * 0 .9 0 *

UPEC 0 .8 0 * 0 .9 4 * 0.52 0 .7 0 * 0 .6 4 * 0 .6 4 * 0 .8 8 * 0 .8 3 * 0 .87*

#PBC = Prompted/Brand Cued; PEC = Prompted/Element Cued; UPBC = Unprompted/Brand Cued; UPEC = Unprompted/ Element Cued.*p < 0.05

• The fame scores for the Unprompted, Brand Cued (UBC) treatment were correlated highly with the scores obtained for the two prompted treat­ments, except in banking (r = 0.61 and r = 0.56, ns).

• The Unprompted, Element Cued (UEC) treatment had the lowest correlations, and, therefore, the lowest convergent validity with the other options.

To address the first three research ques­tions, the researchers compared the uniqueness and fame scores across the different treatments for each category (See Table 2). Chi-squared tests conducted on the individual pairs revealed that fame was significantly higher under the Brand Cued treatments than the Element Cued treatments.

This was evident whether the responses were Prompted (42 percent versus 28 per­cent, x 2 = 4.7, p = 0.03) or Unprompted (35 percent versus 8 percent, x 2 = 20.8, p <

0.001). There was, however, a greater dif­ference in the Unprompted treatment.

This finding addresses RQ1 and RQ3 and reveals asymmetries in associative

strength: the association between a brand and a color was stronger under the Brand Cued condition than it was under the Ele­ment Cued condition.

For uniqueness (RQ2, RQ4), cuing by brand or by color resulted in no signifi­cant differences when responses were

TABLE 2Average Scores across Treatments

PBC# PEC UPBC UPEC

FameBanking 60 37 58 1 5 * *

Chocolate 40 30 32 5 * *

Hair Care 25 19 15 4

Average 42 28* 35 8*

UniquenessBanking 49 46 53 43

Chocolate 24 24 26 9

Hair Care 18 18 21 17

Average 30 30 34 23

#PBC = Prompted/Brand Cued; PEC = Prompted/Element Cued; UPBC = Unprompted/Brand Cued; UPEC = Unprompted [Element Cued.*p < 0.05; **p <0.10

Prompted (both around 30 percent); nor was there any significant difference between the Prompted and Unprompted uniqueness scores when the brand was the cue (34 percent versus 30 percent, x 2 = 0.5, p = 0.48).

The Unprompted, Element Cued (UEC) treatment, however, did have systemati­cally lower uniqueness scores at 23 per­cent, compared to around 30 percent for the other treatments.

Therefore, for both fame and uniqueness, the combined effects of Element cued and Unprompted responses provided substan­tively different results than other meas­urement options. This approach gained fewer responses for the brand, resulting in lower fames scores and a wider variety of responses for competitors, which, in turn, resulted in lower uniqueness scores.

Therefore, it was the most conservative in its assessment of color/brand linkage strength and was not able to be substituted with other methods.

Testing Propensity to Guessing

Propensity to guessing (RQ5) was cap­tured via a "fake" brand that was added to each category wherein responses were prompted. The fake brands were brands that existed in the U.S. market at the time of the data collection, hence were real­istic options but had no presence in the Australian market. The researchers calcu­lated the proportion of people who gave a response to the fake brand to assess the level of guessing.

The results showed that the level of guessing was highest for the Prompted and Brand Cued treatments, followed by Prompted responses in the Element Cued treatment (averages of PBC = 19 percent­age points (pp); PEC = 13 pp; UBC = 7 pp).

Therefore, prompting respondents for response options could have a substantive inflation effect on the fame scores achieved and decrease the accuracy of the results.

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MEASURING THE STRENGTH OF COLOR BRAND-NAME LINKS

CONCLUSIONS AND IMPLICATIONS

The aim of this research was to com­pare four theoretically derived possible approaches to measuring the strength of the link between the brand name and a brand-identity element, in this case color.

The authors' aim was to assess the poten­tial for the color to be a stand-alone brand- identity element and replace, or supplement, the brand name in consumer touch-points.

Testing involved the impact of both the cue used (brand versus color) and the difficulty of retrieval (Unprompted ver­sus Prompted response sets). The results showed that cue direction and the difficulty of the retrieval task do interact to influence the nature of the responses obtained. Put simply, measurement approach matters.

The authors found that cuing with the brand or/and prompting for response gave the impression of higher fame and uniqueness. This could lead to a type 1 error—a false-positive result—if market­ers overestimate the distinctiveness of their identity elements.

If marketers incorrectly assume that brand-identity elements can compensate for low direct branding in communica­tions, there would be a reduction in adver­tising effectiveness.

Further, the evidence from testing with "fake" brands showed that, when cuing with the element and prompting for responses, respondents tended to have a higher level of guessing than in other treat­ments, thereby decreasing the accuracy of these inflated results. The results were con­sistent across the three categories tested.

Therefore, the recommended approach for measuring the strength of the relation­ship between a color and a brand name was to cue with the color and to elicit responses unprompted (Unprompted, Element-Cued approach).

In this approach, the authors provided an image of the color to respondents, with the following instructions:

• "Could you tell me which hair-care brands you associate with each of the following colors? You can name as many brands as you like. If you can't think of any, then just check the 'none' box."

• "Please answer in the text boxes given below (note: multiple text boxes and a 'none of these' check box provided)."

In addition to offering an empirical vali­dation, this approach matches the context for using the brand-identity element. Con­sumers encounter the element in commu­nications or packaging/retail situations, and the aim is that this encounter will evoke the brand (instead of competitors).

Further, this approach allows for testing of the differences in the shades of colors (light/dark) and the ability to capture unexpected competitor brands linked to the color.

A final advantage of this measurement approach is that it will be more sensitive to decay, as this is more likely to show in unprompted measures than ones where responses are prompted (du Plessis, 1994). This is important when tracking the devel­opment and maintenance of distinctive identity elements.

The current research also provides an important contribution to the research on asymmetries in associations' strength. Past research on human memory has addressed the possible issue of asymme­try, which has been discussed in a brand­ing context (Holden and Lutz, 1992) but typically has not been a major factor in empirical measurement (except Torres and Bijmolt, 2009). The current research shows that the bi-directional links between con­cepts—in this case brand and color—have different strengths, and this difference can lead to differing interpretations of brand- identity strength.

In addition to providing empirical evidence for a specific measurement approach, this research also presents two

key metrics to assess the strength of brand- identity elements: Fame and uniqueness capture the two key components needed for a strong brand-identity element.

Furthermore, tools are provided to be able to measure and track the progress of brand-identity development, particularly in the face of competitive activity. This will allow researchers to assess the impact of marketing activities on the building of dis­tinctive brand assets.

Uniqueness and fame each play differ­ent roles:

• Uniqueness—or being the only brand linked to the color—is crucial for brand identity, as a marketer has no control over what competitor brands communicate. Once consumers form strong links to competitor brands, it likely will be difficult to make consum­ers "unlearn" these associations and restore uniqueness.

This means that uniqueness needs to be a primary objective, independent of fame—And the goal should be 100 per­cent uniqueness.

• The importance of fame is in its link to risk. Risk, in this instance, is the level of failed links—or the proportion of consumers who do not link the brand to the element.

If fame is 100 percent, then there is lit­tle or no risk. The fewer the consumers who make the link, the greater the risk that the identity element will be ineffec­tual, and the consumer will fail to iden­tify the brand. Therefore, the goal for fame should also be 100 percent.

FUTURE RESEARCH AND LIMITATIONS

There are many avenues for future research, some of which draw from the limitations of this study. Its authors exam­ined only one element of brand identity: color. Further testing on other elements,

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such as taglines, jingles, or characters, would be useful. Given that these iden­tity elements tap into different sensory processes, it is im portant to determine whether the same measurement considera­tions are applicable.

Future research also should examine the contribution of brand-identity elem­ents to correct branding in advertising. With correct branding statistics cited at about 40 percent (whereby, on average, 6 of 10 people seeing an advertisement not correctly identifying the brand being advertised [Franzen and Bouman, 2001]), understanding how distinctive brand- identity elements can improve this score should improve advertising effectiveness.

Finally, consumer characteristics may enhance or inhibit the ability to process links in memory. Research also should explore influences on an ind iv idual's propensity to develop links between the brand name and non-brand name iden­tity elements.

Jenni R omaniuk is research professor and associate director

(International) at Ehrenberg-Bass Institute, University of

South Australia, and co-executive editor o f the Journal of

Advertising Research. Professor Romaniuk’s areas of

research cover brand equity, advertising effectiveness,

word of mouth, and brand growth.

M agda N enycz-Thiel is senior research associate at

Ehrenberg-Bass institute, University of South Australia.

Dr. Nenycz-Thiel’s main areas of expertise are buyer and

shopper behavior, private label brands, and marketing

metrics. She manages the Mars Marketing Laboratory

at the Ehrenberg-Bass Institute and is area editor for the

Journal o f Consumer Behaviour.

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