The Structure of Survey-BasedBrand MetricsTo better understand how a brand is performing in the marketplace,firms employ a wide variety of measures, with consumer-based surveysoften playing a central role. The authors identify some core dimensions of survey-based measures of brand performance, explore howthey link to one another, and examine how they vary across both countries and categories. Studies in the United States and China of softdrinks, toothpaste, and fast food suggest that survey-based brand metrics can be categorized into six main dimensions that reflect a fourstage, hierarchy-of-effects ing: (1) comprehension; (2) comparative advantage, interpersonalrelations, and history; (3) preference; and (4) attachment. Despite differences in culture and their history, these dimensions usefully portraydifferent brands and products across the different countries.Because of the significant intangible value of brands, building andmanaging brand equity has become a priority for companies of allsizes in a wide variety of industries and markets. Consequently,monitoring brand metrics, which assess how a brand is performingin the marketplace, is critically important (Ailawadi, Lehmann, andNeslin 2003). Given the crucial role of consumers in a brand’s success, many of these metrics are designed to capture various aspectsof consumer beliefs, attitudes, and behaviors toward brands, ofteninvolving consumer surveys as input. Increasingly, such metrics arebeing summarized in an overall scorecard or dashboard for marketers and senior management (Kaplan and Norton 1992).ABSTRACTKeywords: brand metrics, brandperformance, brand measurement,global branding, internationalbrandingDonald R. Lehmann,Kevin Lane Keller,and John U. FarleyA key challenge in developing survey-based brand metrics andbrand-metrics dashboards is the wide range of possible measuresthat could be employed and the potential diversity of geographicalmarkets in which those brand metrics might be applied. Differences in survey responses from participants in different marketsmay result from different interpretations of questions, differentbeliefs about branding, or another underlying aspect of consumerbehavior. Accordingly, our research goal is to suggest a parsimonious set of brand measures, and the relations among them, thatcan be used to measure brand performance regardless of the country market involved or the particular type of product or servicebeing sold.Cross-cultural research studies show that though there is considerable commonality across countries, significant differences oftenemerge. Much of the focus of cross-cultural research is on identifying commonalities and differences and the associated underlyingfactors explaining why these patterns emerge.Journal of International Marketing 2008, American Marketing AssociationVol. 16, No. 4, 2008, pp. 29–56ISSN 1069-031X (print)1547-7215 (electronic)Reprinted with permission from the Journal of International Marketing, published by the American Marketing Association,Lehmann, Donald, Kevin Lane Keller, and John Farley, volume 16, no. 4 (2008): 29-56.29
Prior research in branding has shown that both similar and different effects can be found across cultures and countries. For example, in a meta-analysis of seven brand extension studies acrossmultiple countries involving 131 different brand extensions, Bottomley and Holden (2001) find that though evaluations of brandextensions are a function of quality of the original brand, fitbetween the parent and the extension category, and the interactionbetween the two, the relative impact of each of these componentsvaries by brand and culture. As another example, Zhang andSchmitt (2001) show how subtle differences in brand names affectbrand ratings in different countries.However, much of the published branding research has focusedprimarily on a single country—the United States—and often asingle category. Given cultural differences across countries andconsumer behavior variation across categories, it is not clear thatthe relevant measures and dimensions for brand metrics will be thesame, much less be linked together in the same way, across disparate markets and distinct categories. Here, we examine consumers in two important but quite different settings, the UnitedStates and China, across three categories in two studies.The purpose of Study 1 is primarily to refine the scale and to gaininsight into the different possible measures of brand performance.Specifically, we examine two well-known, widely advertised, andphysically similar brands (Coke and Pepsi), as well as a thirdsmaller challenger brand (Dr Pepper or Sprite), on various brandrelated measures to determine (1) how distinct the different possible measures of brand performance are and (2) whether the measured performance of brands differs significantly. To addresscultural issues, we compare the measured brand performance ofCoke and Pepsi in the United States and China.In Study 2, we use the measures and scales developed in Study 1 todeduce an underlying structure of brand metrics. We group brandperformance measures into distinct factors or core dimensions andexplore their interrelationships. Study 2 also expands our investigation to brands in two other categories (Crest and Colgate toothpaste and McDonald’s and KFC fast-food restaurants). In addition,we examine the relative contribution of brand, individual participants, category, and country-to-brand performance ratings.STUDY 1Measuring Brand Performance30We designed Study 1 to assess the broad range of potential brandperformance measures. To gain some initial insights, we focusedon a single category: soft drinks. To examine the impact of culture,we used two countries—the United States and China. Finally,much research in marketing and consumer behavior has shownthat consumer response to marketing stimuli can be characterizedalong many different dimensions. In particular, research hasshown that consumer response can vary from fairly low levels ofbrand awareness or familiarity to highly involved brand loyaltyrelationships based on affective, cognitive, and behavioral considerations (Haugtvedt, Herr, and Kardes 2008). Therefore, we examined several different research models and findings to ensure thatwe captured a wide range of possible consumer response andresulting differences in brand performance.Donald R. Lehmann, Kevin Lane Keller, and John U. Farley
Specifically, we used three main sources. First, research by Aaker(1996), Fournier (1998), Keller (2002, 2008), and Keller andLehmann (2003) suggests that consumer-based brand performancemeasures can be grouped broadly into five principal categories:awareness, associations (i.e., image and beliefs), attitudes, attachment (i.e., loyalty), and activity (e.g., purchase, consumption, wordof mouth). Accordingly, we included aspects of each of the fiveprincipal categories of customer mind-set identified by theseauthors. Second, we added three specific elements of Ambler’s(2003) brand health measures: quality, ambiance, and service.Finally, we reviewed three widely used commercial brand trackingapproaches for additional measures: Young & Rubicam’s Brand Asset Valuator (BAV), whichoriginally measured four principal dimensions: relevance,differentiation, esteem, and knowledge; Millward Brown’s BrandZ, which focuses on a pyramid offactors ranging from presence at the bottom to relevance,performance, advantage, and bonding at the top; and Research International’s Equity Engine, which describes astructural model involving five constructs: authority (heritage, trust, and innovativeness), identification (bonding,caring, and nostalgia), approval (prestige, acceptability, andendorsement), attitude, and performance.To generate scale items for the resulting 27 brand performance constructs, we began with scales in the Handbook of Marketing Scales(Bearden and Netemeyer 1998) and refined them using pilot testsand discussions with individual respondents, as well as input frommarket research suppliers that offer brand tracking and measurement services. This process resulted in the scales that appear inAppendix A (with sources indicated).Study 1 focused on a single category, soft drinks, which is bothwidely consumed and the subject of strong advertising and brandbuilding activities. Because one of our objectives was to developbrand metrics that could distinguish between functionally similarbrands in a product category, we used both Coke and Pepsi as stimuli. To determine whether the structure of brand performance, aswell as the ratings of two major brands, was similar across countries, we collected data in the United States (Chicago) and China(Shanghai). Finally, to determine how a comparatively weakerbrand would be rated, we included a third well-known brand ineach country (Dr Pepper in the United States; Sprite in China).Although different in formulation from each other, both brands represent established challenger brands in their respective markets.MethodCoke was introduced in the United States in 1886 and became thelargest-selling cola drink by the turn of the century. Pepsi wasintroduced in the United States in 1898. Coke received a stronginternational push during and after World War II. Coke and Pepsiboth secured permission to operate in China during the early 1980sas economic reforms developed. Pepsi was the first to market, withCoke close behind. Both brands sold (and sell) at significant priceThe Structure of Survey-Based Brand Metrics31
premiums in China, where consumers consider “value for money”very important (Yang et al. 1999).Research International collected data using a shopping mall intercept approach. Respondents were 100 adults (age 18 years andolder), evenly split between men and women, in each country.Respondents were paid for their participation. They rated the threebrands on the 84 items in Appendix A on five-point scales, wherehigher numbers indicated greater agreement. In addition, they provided demographic data, consumption patterns, and appropriatedollar and yuan metric preferences among the three brands.FindingsScale Evaluation. The first step in the analysis was to determinewhether the 27 constructs were internally consistent. We examinedeach construct by computing average item-to-item correlationsboth within and between each construct. We also computed coefficient alphas and reexamined question wording. This resulted inthe following modifications:1. Item 3 (“When you think of a soft drink, this brand comesto mind”) did not fit well with the other presence variables.It also was not a good fit with the awareness variables.Therefore, we dropped it from the analyses.2. Item 6 (“I am quite familiar with this brand”) correlatedbetter with the knowledge measures, and therefore weincluded it there.3. Item 22 (“This brand lives up to its promises”) was similarly related to performance and trust measures, and therefore we dropped it from the analyses.4. Item 31 (“This brand has served me well”) was moved toperformance because it was better correlated there.5. Item 64 (“There is a good substitute for this brand”) hadlow correlations to other items, and therefore we dropped itfrom loyalty.6. Items 74 and 75 (“positive associations, positive thoughts”)added nothing to the other four measures of overall attitude, and therefore we dropped them to achieve parsimony.7. Item 80 (“I am unlikely to change my opinion of thisbrand”) was dropped from persistence because it focusedon opinion versus action.Table 1 shows the final 78 items included in each construct alongwith average interconstruct correlations and coefficient alphas. Allthe constructs appeared to have adequate reliability, as all coefficient alphas were .76 or greater. We used averages of the 78 remaining items to capture the 27 brand performance constructs. Given thenature of the task, it is not surprising that there was considerablecorrelation among the constructs; that is, a large component of consumer response was overall liking of the brand, reflecting a haloeffect or common method variance.32Donald R. Lehmann, Kevin Lane Keller, and John U. Farley
Average WithinConstructCorrelationCoefficientAlphaStudy 1ItemsUnitedStatesChinaUnitedStatesChina1. Presence1, 2.64.63.77.772. Awareness4, 5.76.78.87.913. Knowledge6, 7, 8, 9.69.61.96.864. Relevance10, 11, 12, 13.75.60.92.865. Difference14, 15, 16.67.71.86.886. Esteem17, 18, 19.65.52.85.767. Performance20, 21, 31.78.59.93.808. Advantage23, 24, 25.83.72.93.889. Bonding26, 27, 28.82.75.93.8929, 30.87.70.93.82Construct10. Heritage11. Trust32, 33, 34.81.55.93.7712. Innovation35, 36, 37.73.63.89.8413. Caring38, 39, 40.73.68.89.8614. Nostalgia41, 42, 43.65.75.85.9015. Prestige44, 45, 46.74.56.89.7916. Acceptability47, 48, 49.58.63.79.8317. Endorsement50, 51, 52.78.55.91.7918. Quality53, 54, 55.81.78.93.9119. Ambiance56, 57, 58.78.67.91.8620. Service59, 60, 61.59.65.82.8521. Loyalty62, 63.74.63.85.7722. Intention65, 66.90.87.95.9323. Value for money67, 68, 69.80.62.92.8370, 71, 72, 73.89.70.97.9025. Extension potential76, 77, 78.75.72.90.8926. Persistence27. Activity79, 8182, 83, 84.62.73.57.72.76.89.73.8924. AttitudeTable 1.Final Scale Items, WithinConstruct Correlations, andCoefficient Alphas (Study 1)Predictive Power of the Dimensions of Brand Performance. We analyzed the predictive power of the measures of brand performanceusing two behavioral measures: past consumption and plannedshare of next ten purchases. Table 2 shows the simple correlationsof the 27 brand performance constructs with these key behavioralmeasures. All the correlations are positive and significantly different (p .05) from 0. In the United States, 23 of the correlationsrange from .5 to .6, suggesting a consistently strong relationship.These results indicate that there is a significant relationship ofbrand performance measures with both backward- and forwardlooking behavioral measures.If the 27 measures of brand performance are to be of much usewithin a product category, they must discriminate between brands.To determine whether they did, we computed the mean for eachThe Structure of Survey-Based Brand MetricsBrand Profiles33
Table 2.Correlations Between EquityDimensions and Product Usage(Study 1)United on.64.68.50.46Value for money.42.45.30.36Preference.60.62.37.49Extension ty.50.45.38.35brand and tested it for significant differences. In the United States,both Coke and Pepsi rated significantly higher than Dr Pepper onall 27 measures, with the smallest t-value greater than 3.1 Moreinteresting is the comparison of Coke with Pepsi (see Table 3). Atleast for the Chicago sample, respondents rated Pepsi higher on allthe measures except heritage and nostalgia and significantly higher(p .05) for eight measures: relevance, advantage, bonding, loyalty,value for money, overall, extension potential, and persistence.In China, the picture was noticeably different. Coke was statistically significantly stronger on heritage and nostalgia than Pepsi(p .05) and at statistical parity with Pepsi on the other 25 measures. (There were no significant differences and no patterns in thesigns: 11 were positive, and 14 were negative.) This finding is consistent with the notion that given its brand development, Coke’srelative advantage in marketing in the international arena is its his-34Donald R. Lehmann, Kevin Lane Keller, and John U. Farley
United 5Value for 0Commitment–.045–.62.020.38Table 3.Within-Country DifferencesBetween Coke and PepsiRatings (Study 1)tory. As in the United States, Coke and Pepsi were significantlystronger (p .05) than the third brand (Sprite) for all 27 dimensionsfor Coke and for 25 of 27 dimensions for Pepsi.Examining the differences between countries (see Table 4) is potentially informative, though some distinctions may be due to different response styles in the two locations and cultures. For Coke, itappears that only four measures are significantly higher in theUnited States than in China: knowledge, nostalgia, endorsement,and extension. However, for Pepsi, on 26 of 27 measures, the U.S.The Structure of Survey-Based Brand Metrics35
Table 4.Between-Country DifferencesBetween Coke and PepsiRatings (Study 1)36Donald R. Lehmann, Kevin Lane Keller, and John U. FarleyCokePepsiUnited StatesChinaUnited 95Quality4.3104.193.914.4874.1672.85
The Structure of Survey-Based Brand MetricsCokePepsiUnited StatesChinaUnited 9053.9054.2653.9402.09Value for tment4.7654.735.364.8104.7151.08Table 4.Continued37
scores are larger, and 18 of these are significantly so. There are nomeasures in which Pepsi is rated significantly higher in China thanin the United States. Again, this result suggests that Pepsi is not asstrong a global brand as Coke in this context: Its image is significantly stronger in the domestic U.S. market than in the foreign Chinese market.SummarySTUDY 2MethodOverall, the results of this pilot study were encouraging. Specifically, we analyzed 27 measures of brand performance. Asexpected, these measures were highly correlated. In our samples,Pepsi’s brand performance was stronger in the United States, butCoke’s brand performance was stronger in China. For a more complete view of the measures of brand performance, in the next studywe slightly modify the scales, examine the underlying factor structure to these measures, and explore how the resulting dimensionsinterre
different brands and products across the different countries. Because of the significant intangible value of brands, building and managing brand equity has become a priority for companies of all sizes in a wide variety of industries and markets. Consequently, monitoring brand metrics, which assess how a brand is performing
May 02, 2018 · D. Program Evaluation ͟The organization has provided a description of the framework for how each program will be evaluated. The framework should include all the elements below: ͟The evaluation methods are cost-effective for the organization ͟Quantitative and qualitative data is being collected (at Basics tier, data collection must have begun)
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Le genou de Lucy. Odile Jacob. 1999. Coppens Y. Pré-textes. L’homme préhistorique en morceaux. Eds Odile Jacob. 2011. Costentin J., Delaveau P. Café, thé, chocolat, les bons effets sur le cerveau et pour le corps. Editions Odile Jacob. 2010. Crawford M., Marsh D. The driving force : food in human evolution and the future.
Le genou de Lucy. Odile Jacob. 1999. Coppens Y. Pré-textes. L’homme préhistorique en morceaux. Eds Odile Jacob. 2011. Costentin J., Delaveau P. Café, thé, chocolat, les bons effets sur le cerveau et pour le corps. Editions Odile Jacob. 2010. 3 Crawford M., Marsh D. The driving force : food in human evolution and the future.