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G BRAN *EQT: A Model and Simulator for Estimating, Tracking, and P

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R Venkatesh Shankar, Pablo Azar, and Matthew Fuller S E R I

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BRAN*EQT: A Model and Simulator for Estimating, Tracking, and Managing Multicategory Brand Equity

Venkatesh Shankar, Pablo Azar, and Matthew Fuller

This innovative, rigorous application of economic and econometric models to a large publicly listed company changed the way senior management looks at the value of their flagship brand.

Report Summary leading insurance company and its foremost There is a growing recognition that brands are competitor with the same brand name in mul- valuable intangible assets for improving share- tiple product categories. They use a combina- holder value. Many models have been pro- tion of hard financial data and survey data. posed for estimating brand equity. These models are developed either for firms with a The model provides reliable estimates of brand single brand in a single product category or for equity for the focal brand and the leading Venkatesh Shankar is firms with the same brand in multiple cate- competitor brand. The results show that Professor of Marketing gories. The models assume that the equity of advertising has a strong, long-term positive and Coleman Chair in the brand is the same in each category. influence on brand equity and that brand Marketing, Mays Because most firms have the same brand in equity is positively related to shareholder value Business School, Texas multiple categories and the same brand per- for the focal company. Key executives in the A&M University. Pablo forms differently in different categories, these company in the study use the model, the Azar is Assistant Vice models may provide incorrect estimates. brand equity estimates, and the decision sup- President, Marketing port simulator across functional areas such as Strategy and Consumer Here, authors Shankar, Azar, and Fuller marketing, strategy, accounting, and finance. Insights, Allstate develop a model for estimating, tracking, and The brand equity model and simulator have Corporation. Matthew managing brand equity for multicategory enabled the company to reallocate its advertis- Fuller is Director, Allstate brands based on a combination of customer ing resources to improve brand equity and Corporation. surveys and financial measures for each prod- shareholder value, and offer better guidance to uct category. They apply this model to esti- managers, analysts, and investors. I mate the equity of the flagship brand of a

WORKING PAPER SERIES 51 Introduction brand equity as a revenue premium over a generic product’s revenues. Kamakura and “Brand Coca-Cola is at the core of our business Russell (1993) calculate brand equity as a vol- and brand-building is our expertise.” ume premium based on a choice model esti- mated on scanner panel or survey data. —Douglas Daft, former CEO, Coca-Cola, Inc. (Miller 2005). Hjorth-Anderson (1984) and Holbrook (1992) treat brand equity as a price premium. Daft’s statement sums up the growing recogni- Park and Srinivasan (1994); Srinivasan tion that brands are valuable intangible assets. (1979); Srinivasan, Park, and Chang (2005); Brand equity has recently been the focus of and Swait et al. (1993) compute brand equity academic research and managerial practice by estimating price and volume premiums (e.g., Aaker 1996; Ailawadi, Lehmann, and from consumer survey data. Simon and Neslin 2003; Farquhar, Han, and Ijiri 1992; Sullivan (1993) estimate brand equity as a Keller 1993, 2003; Srinivasan, Park, and Chang residual effect on market capitalization after 2005). Brand equity can be defined as the net controlling for some known effects. Roberts et present value of the incremental cash flows attrib- al. (2004) estimate brand equity as a ratio of utable to a brand name and to the firm that outcome for the focal brand over the sum of owns that brand name, relative to an identical outcomes for all the brands in the category. In product with no brand name or brand-building their model, outcome (measured by variables efforts (Shocker and Weitz 1988). such as behavioral intentions) is regressed on sources of brand equity such as awareness, Brand equity is an important construct to consideration, and association to understand study because it is associated with key benefits the drivers of brand equity. CoreBrand for both consumers1 and firms. From a con- Analysis (2004) estimates brand equity as a sumer viewpoint, it signals credibility, improv- contribution to market capitalization based on ing customer perceptions about the brand and executives’ opinions of brand familiarity and increasing confidence in brand claims, leading favorability. Fischer (2004) computes brand to lower information costs, lower perceived equity as the portion of cash flow attributable risk, lower costs of thinking, and greater utility to brand relative to other marketing mix vari- for the brand (Erdem and Swait 1998; Erdem, ables. Interbrand (2006) estimates brand Swait, and Valenzuela 2006; Shugan 1980). equity as the brand-related share of future From a firm perspective, brand equity allows a cash flows as predicted by analysts and judges. firm to leverage its brand reputation in one Damodaran (2006) suggests accounting market to alleviate an information asymmetry approaches such as historical, discounted cash problem in other markets (Balachander and flow, and excess returns approaches to meas- Ghose 2003; Choi 1998) and permits high- ure brand value. Young and Rubicam’s brand quality brands to extend to other markets asset valuator computes brand equity from (Cabral 2000). For a detailed review of the two survey-based dimensions—brand stature conceptual foundations of brand equity, see and brand strength or energy (Young and Swait et al. (1993). Rubicam 2006).

Many approaches have been proposed for Existing brand equity models are developed estimating brand equity. A summary of the for corporate brands or for firms with a single basic principles, categories of application, and brand in a single category, or in cases where the major limitations of selected approaches, a firm has the same brand in multiple cate- including the approach used in this paper, gories, existing models implicitly assume that appears in Table 1. Ailawadi, Lehmann, and brand equity is the same in each category. Neslin (2003) and Dubin (1998) compute Because most firms have the same brand in

MARKETING SCIENCE INSTITUTE 52 Table 1 Summary of Selected Brand Equity Models

Author(s) Principle Categories Type of Data Main Limitations Ailawadi, Revenue premium calculated as Consumer Weekly sales and Uses contribution margin, not actual cash Lehmann, the incremental difference of packaged goods price promotion flow, as the financial metric. The premium and Neslin brand revenues over private variables data for measure is relative to private label, which (2003) label’s revenues a grocery chain is assumed to have no brand equity. Does not isolate the role of brand relative to other drivers of market performance. CoreBrand Estimation of market capitalization Publicly listed firms Survey of executive Judgment or opinion data. Brand power Analysis due to brand power operationalized opinions on brands measure limited to familiarity and (2004) as familiarity and favorability and financial data favorability. Potential multicollinearity opinions problems in regression analysis. Potential endogeneity of variables in the brand power and stock price equations. Damodaran Brand expenditure is amortized Illustration and No empirical data Measures the expenditures on the brand, (2006) over an assumed horizon, and examples of not the value of the brand. Generic the unamortized portion is treated categories comparison firms are difficult to obtain. as brand equity. DCF and excess Cannot attribute excess returns to return differences over generic firm. brand name. Dubin (1998) Economic measure of difference Breakfast foods Nielson store audit Based on contribution margin. Does not between a brand’s profit and a data, SAMI Burke isolate the role of brand relative to generic product warehouse other drivers of market demand. withdrawal data Fischer (2004) Portion of cash flow attributable to German automobiles, Consumer survey Assumes either single category brand or brand relative to marketing mix cosmetics, grocery and financial data that brand equity is equal in all product variables stores categories. No analysis of relationship between brand equity and advertising/ brand-building measures. Hjorth- Econometric estimation of price Broad range of Price data Volume premium or cash flow not Anderson premium from hedonic regression consumer packaged considered (1984) function goods Holbrook Econometric estimation of price Consumer electronics Price data Volume premium or cash flow not (1992) premium from hedonic regression considered function Interbrand Estimation of brand-related share Broad range of Expert ratings, Judgment based (driven by expert (2006) in future brand cash flows predicted industries projected cash flows ratings) by analysts Kamakura Estimation of perceived quality and Laundry detergents Scanner panel data Nonfinancial measure of brand equity. and Russell intangible value index from brand Does not partial out the effects of all (1993) utility function possible marketing variables. Single- category brand equity measure. Park and Survey-based estimation of attribute Toothpaste and Consumer survey Nonfinancial measure of brand equity. Srinivasan and nonattribute components of mouthwash Only a relative measure of brand equity. (1994) brand equity in terms of market share Relies on last purchased brand. and price premiums attributable to brand

WORKING PAPER SERIES 53 Table 1 Continued

Author(s) Principle Categories Type of Data Main Limitations Roberts et al. Ratio of outcome of brand equity 1,710 brands in Consumer survey, Consumer-based measure, not translated (2004) (regressed on sources such as 60 categories face-to-face interviews into financial value ($) awareness, consideration, and associations) for the focal brand over the sum of outcomes for all brands Simon and Regression-based decomposition of Broad range of industries Published annual reports Assumes one brand firm, share price Sullivan a firm’s market capitalization due to reflects anticipated value of all activities (1993) intangibles such as brand assets of that brand, and coefficients to be same for all brands in the industry Srinivasan Estimation of brand-specific effects Health care facilities Consumer survey Preference measure of brand equity in (1979) as component of brand preference terms of premium price in multi-attribute model Srinivasan, Estimation of price and volume Cellphones Consumer survey Uses incremental contribution, not actual Park, and premium from brand utility function cash flow as the financial metric; does not Chang (2005) include price promotions; measurement errors due to use of industry experts to judge availability Swait et al. Estimation of price premium from Deodorants, jeans, Consumer survey Volume premium or cash flow not (1993) brand utility function athletic shoes considered. Young and Estimation of brand strength and Variety of product Consumer survey Not well connected to financial measures; Rubicam brand stature (two dimensions of categories single category model (2006) brand equity) This paper Estimation of incremental cash flow Insurance industry Consumer survey data Analysis of relationship between brand (2007) attributable to brand in each category and financial and equity and advertising based on limited in which the brand competes. Study marketing measures sample size. of relationships between brand equity and advertising and between brand equity and shareholder value.

multiple categories and the same brand can egory, resulting in incorrect estimates of its have different performance outcomes in differ- equity. ent categories, these models can provide incor- rect estimates of brand equity. For example, Current models of brand equity do not study the Hewlett-Packard (HP) brand is stronger the relationship of brand equity with advertis- than its competitor brands in the printer cate- ing or shareholder value. Marketing executives gory, but is competitively weak in the com- need to better understand how advertising puter server category. A model of brand equity efforts are related to brand equity so that they that assumes equal or comparable strengths of can make appropriate decisions on advertising the brand in all its categories would produce spending. More importantly, at the senior incorrect and misleading estimates of overall management and board of director levels, a brand equity for the HP brand. Moreover, clear understanding of the relationship of approaches that assume a single category brand equity to shareholder value is critical for brand do not capture the spillover effects of a making appropriate marketing investment brand name from one category to another cat- decisions and for providing valuable guidance

MARKETING SCIENCE INSTITUTE 54 to the investors and analysts about the value of Swait et al. 1993) and those using brand out- the brand to the stockholder. comes and sources based on consumer surveys (e.g., Roberts et al. 2004) by incorporating In this paper, we develop a model and decision cash flows and further isolating the role of support simulator (BRAN*EQT) for estimat- brand in total cash flow. Fourth, we extend ing, tracking, and managing brand equity for models based on expert judgments (e.g., multicategory brands based on a combination CoreBrand Analysis 2004; Interbrand 2006; of financial- and customer-based measures. In Young and Rubicam 2006) by using objective addition, we study the relationships between financial data and consumer perception data brand equity and advertising and between and performing a rigorous analysis of the role brand equity and shareholder value. Our gen- of brand in consumer choice. Fifth, we extend eral model can be applied to a good or service models based on market capitalization (e.g., in a business-to-consumer (B2C) or a busi- CoreBrand Analysis 2004; Simon and Sullivan ness-to-business (B2B) context. We apply our 1993) by rigorously separating the effects of model to measure the brand equity of the flag- brand from those of other variables and by ship brand (hereafter, “the focal brand”) of a basing brand equity estimation on cash flows leading insurance company (hereafter, “the rather than on potentially speculative investor company”) and its closest competitor, each of behavior. Sixth, we go beyond single-category which offers its brand in multiple categories. accounting approaches that treat investments We validate this model by comparing the rela- as a measure of brand value and do not isolate tive brand importance and brand equity the effect of brand (e.g., Damodaran 2006) by obtained from a brand choice model to those using projected cash flows and consumer data from an alternative method, namely, a brand and by isolating the relative importance of perception score method. We examine the brand. Seventh, we extend models based on relationship between advertising and brand only customer survey (Young and Rubicam equity and between brand equity and share- 2006) and those that combine consumer holder value for the focal company, using data choice data and financial measures (e.g., on multiple brands and categories. We discuss Fischer 2004) from single-category brand the implications for tracking, building, and equity estimation to multicategory brand managing brand equity based on these results. equity estimation. Our approach allows for spillover effects of the brand from one cate- We extend prior brand equity models in sev- gory to another. Such spillover effects have eral ways. First, we extend models that treat been found to be significant in other contexts brand equity as price or revenue premiums such as brand extension and umbrella brand- (e.g., Ailawadi, Lehmann, and Neslin 2003; ing (e.g., Balachander and Ghose 2003; Dubin 1998; Hjorth-Anderson 1984; Erdem 1998; Erdem and Sun 2002). Our Holbrook 1992) by incorporating cash flows model estimates relative brand importance at that truly reflect the financial value of the the individual customer level, thereby allowing brand. Second, we build on models of volume the firm to segment and target customers premiums based on consumer choice models based on the firm’s ability to leverage the value estimated using scanner panel data (e.g., of the brand. We also extend all prior brand Kamakura and Russell 1993) by including equity models by investigating the relationship cash flows and by separating out the effects of between brand equity and advertising expendi- multiple marketing variables. Third, we go tures and between brand equity and share- beyond models measuring marginal contribu- holder value. tion of brands based on consumer surveys (e.g., Park and Srinivasan 1994; Srinivasan In the following sections, we introduce a con- 1979; Srinivasan, Park, and Chang 2005; ceptual framework and our model of multi-

WORKING PAPER SERIES 55 Figure 1 Conceptual Framework of Brand Equity

Advertising Brand Equity Shareholder Value

Relative Brand Offering Value Importance

Revenues Brand Reputation Other Marketing Brand Image Mix Elements EBITDA Margin Ratio Brand Uniqueness

Marginal Tax Rate Brand Fit

Expected Inflation Rate Brand Association

WACC+ Brand Trust

Investment Rate Brand Innovation

Brand Regard

Brand Fame

category brand equity, provide company back- framework, advertising impacts brand equity, ground, and describe the data and outline the which in turn, affects shareholder value. Brand estimation of the model. We present the equity has two components—offering value results and discuss model validation, brand and relative brand importance. Offering value image drivers, and robustness checks. We is the net present value or financial worth of empirically analyze the relationship between an offering (a good or service or a bundle of brand equity and advertising spending and goods and services) carrying a brand name. between brand equity and shareholder value Relative brand importance is derived from and describe the brand equity simulator and consumer brand choice and is driven by mar- its impact of the model on the company. We keting mix attributes and brand image percep- close by outlining the limitations of our tions along several dimensions. Our focus is model, suggesting some useful directions for on developing a model for estimating brand future research. equity using financial and consumer survey data, identifying the main brand dimension drivers, and relating brand equity to advertis- A Conceptual Framework and Model ing and shareholder value. for Estimating Multicategory Brand Equity A model that estimates brand equity would have to identify the effect of the brand name on A conceptual framework relating brand equity the cash flow values of the offerings carrying to its components, drivers, advertising, and the brand name and determine the cash flows shareholder value appears in Figure 1. In this attributable to the brand name. For a multicate-

MARKETING SCIENCE INSTITUTE 56 gory brand, brand equity can be defined as the suggested time periods for their measures are sum of the products of relative brand impor- also indicated. The data on most of these vari- tance and offering value in each category. ables can be obtained from company internal records and publicly available databases such J as Bloomberg, Compustat, Yahoo Finance, BE ϭ OV RBI , (1) and Thomson Financial. The suggested opera- it Σ ijt ijt j =1 tionalization for most variables is average measures of the most recent three years or the where BE is brand equity, OV or offering value current year, depending on the variable. is the discounted cash flow value, RBI is rela- tive brand importance, i is brand, j is product Relative brand importance category, t is time, and J is the total number of We define relative brand importance (RBI) as product categories carrying brand i’s name. the incremental choice probability attributable to the brand name divided by the sum of Offering value incremental choice probabilities due to the The offering value of brand i in category j at brand name and the marketing mix variables. time t is given by: We determine relative brand importance from

a consumer brand choice model. Let Uijkt ϱ denote the utility of brand i in category j to an ( Ϫ ) ϭ f t r it t Ϫ OVijt e Rijt (1 xit ) ͐ individual k at time t. Let Uijkt comprise a t deterministic component V and a stochastic Ϫ␯ ijkt (EBITDAMRijt it )dt, (2) ␧ ␧ component ijkt such that Uijkt = Vijkt + ijkt. Furthermore, assume that individuals maxi- where f is the expected long-term inflation mize their utility and the stochastic compo- ␧ rate, r is the weighted average cost of capital nent ijkt is independently and identically (WACC) for the firm owning the brand, R is distributed (i.i.d.) according to Gumbel or the expected revenues from the offering that type I extreme-value distribution. The proba- carries the brand name, x is the marginal tax bility of individual k choosing brand i at time

rate for the firm, EBITDAMR is the earnings t, Prijkt, is given by the ubiquitous multinomial before interest, taxes, depreciation, and amor- logit model of brand choice (Guadagni and tization margin ratio, ␯ is the firm’s investment Little 1983; Erdem et al. 1999; McFadden rate, and the other terms are as defined earlier. 1974; Roberts and Lilien 1993; Roberts and Nedungadi 1995; Roberts and Urban 1988). When the time horizon is infinite, as is the case for a “going concern,” this offering value eVijkt Pr ϭ (4) expression becomes the following perpetuity ijkt L ΣeVljkt formula of financial valuation (Copeland, l ϭ 1 Koller, and Murrin 2000; Copeland and Weston 1988). where l = brand, L is the total number of brands in a given product category, and the other terms Ϫ Ϫ␯ are as defined earlier. The deterministic part of Rijt(1 xit)(EBITDAMRijt it) OV ϭ (3) the utility function, V, is given by: ijt Ϫ rit ft ϭ ␤ ϩ ␤ ϩ ␤ ϩ Z ␤ , (5) A summary of the variables, their definitions, Vijkt 0ij Xijkt 1j 2jYijkt ijkt 3j and potential data sources used in our model is shown in Table 2. All the variables except where X is a vector of the offering’s brand perception variables are financial vari- attributes/factors/marketing mix elements, ables. Their potential data sources and the including the brand name that influences con-

WORKING PAPER SERIES 57 Table 2 Summary of Variable Definitions and Data Sources

Variable Variable Definition Suggested Potential/Suggested Comments Name Time Period Data Source Brand R Net revenues for the brand in Average of past Internal records Longer time period may be considered if the revenues the category of interest four years/quarters Annual reports industry is cyclical. EBITDA EBITDAMR Earnings before interest, Average of past Internal records, Longer time period may be considered if the margin taxes, depreciation, and five years Bloomberg, industry is cyclical. If catastrophe losses are ratio amortization as % of brand Compustat, critical and difficult to predict, then a longer revenues Yahoo Finance, time horizon should be considered. Thomson Financial Investment N Investment rate for Average of past Bloomberg, Longer time period may be considered if the rate replacement expenditures as three years Compustat, industry is cyclical. % of brand revenues Yahoo Finance, Thomson Financial Weighted R Mixture of cost of private Current rate Bloomberg, May vary significantly across the different average cost equity and debt according Thomson financial players in the industry. of capital to target capital structure Marginal X Effectively paid taxes as % Current rate Internal records, Tax rate to be adjusted for differences in tax rate of cash profits Bloomberg subsidiaries’ tax rates if different product categories are managed as subsidiaries. Expected F Expected long-term rate of The next 10 years World Bank, Longer time period may be considered if long-term inflation World Market there is longer visibility in the business. rate of inflation Monitor Attribute X, Z, Perceived levels of attributes Annual Consumer survey Multiple items/dimensions of brand ratings and brand and brand, including its perception should be used. brand perceptions dimensions perception

sumer utility (e.g., Dillon et al. 2001; Erdem where B = brand, Q = quality, P = price, D = and Swait 2004), Y is a variable representing distribution, C = communication, and S = sales past brand choice that captures the effect of force are the key marketing mix elements, that state dependence or past choice or longevity of is, {B,Q,P,D,C,S} ʦ X. The choice of the X ownership on brand choice, Z is a vector of variables is consistent with the brand choice brand image scores from other categories that literature, which formulates utility primarily in carry the same brand name (to capture the terms of marketing mix elements (e.g., spillover effects of the brand from other cate- Guadagni and Little 1983; Erdem et al. 1999; gories),2 and ␤ is a vector of coefficients associ- Roberts and Lilien 1993). Furthermore, by ated with the variables. In the context of the including the marketing mix decision vari- insurance industry, it can be shown that relative ables, we can better separate out the role of brand importance is given by the following the brand in consumer choice. Equation 6 can expression (see Appendix 1 for a derivation) be further written out as:

V ␤ X RBI ϭ Bijkt (6) RBI ϭ Bj Bijkt . (7) ijkt ϩ ϩ ϩ ijkt ␤ ϩ ␤ ϩ ␤ ϩ VBijkt VQijkt VPijkt Bj XBijkt Qj XQijkt Pj XPijkt ϩ ϩ ␤ ϩ ␤ ϩ ␤ VDijkt VCijkt VSijkt Dj XDijkt Cj XCijkt Sj XSijkt

MARKETING SCIENCE INSTITUTE 58 We aggregate relative brand importance over about $29 billion worth of auto, property consumers to get the overall relative brand (home), and life insurance products and finan- importance for the brand in a category. In cial services to approximately 17 million aggregating over consumers, each consumer’s households through 14,000 exclusive agencies relative brand importance needs to be and finance professionals and other channels, weighted by the quantity of purchases made including online. About one of every nine by the consumer. Further adjustments can be autos and one of every eight homes in the made to this expression of brand importance, United States are insured by the company. It if necessary, with the availability of additional has a huge advertising budget (several hun- relevant data or data on other relevant vari- dreds of million dollars) and was one of the ables.3 For each product category, we use a official sponsors of the 2006 Winter multinomial logit or mixed logit or het- Olympics. eroscedastic extreme value model of brand choice after determining the appropriate Our work has important implications for the model through suitable tests. realization of the value of marketing within the company. We began this brand equity Our model satisfies the considerations for project when the company was in the throes of valuing brand assets from an accounting per- a marketing transformation. A new chief mar- spective. Brand equity has attracted some keting officer was hired by the company to attention in accounting under valuation of enable the following: The view of marketing, intangible assets (e.g., Barth and Clinch 1998; which was equated to advertising, needed to Barth, Krasnik, and McNichols 2001; Barwise be changed to one that encompassed the entire et al. 1989; Damodaran 2006; Kallapur and marketing mix. The view of the brand needed Kwan 2004; Lev 2001). Some firms, notably to be changed from that of brand as a symbol European companies such as Celemi and of an advertising slogan to that of an asset Skandia, have used supplementary statements with measurable equity. Advertising needed to valuing intangible assets (Celemi 2003). Our be treated as an investment rather than as an model meets many of the considerations of expense. The company wanted to fully utilize accounting research for valuing intangible its position as a multicategory insurance com- assets and, importantly, of the U.S. Generally pany and not be centered on automobile as a Accepted Accounting Principles’ (GAAP) category. To enable these transformations, and Financial Accounting Standards Board’s brand equity quickly emerged as the central (FASB 2001a, b) accounting criteria of rele- issue in understanding the value of marketing. vance, reliability, comparability, understand- ability, and cost effectiveness. The model also Our brand equity project is particularly reflects future orientation, completeness, and important to the company not only from the verifiability, which are also important charac- perspective of enhancing the value of the com- teristics of intangible assets from an account- pany’s flagship brand and making strategic ing standpoint. decisions on advertising, but also in tangibly linking brand equity to its advertising efforts and its shareholder value. Because the insur- Company Background ance industry and the company’s earnings are vulnerable to catastrophes such as hurricanes The company is the largest publicly held per- (e.g., Katrina and Rita), earthquakes, and sonal insurance company in the United States other acts of nature, from the standpoint of with approximately $156 billion in assets guiding managers and investors, senior man- under management and approximately agement needs a tool to estimate and commu- $37 billion in market capitalization. It sells nicate the company’s brand equity (which is

WORKING PAPER SERIES 59 more reflective of the core value of the firm mixed logit model (Hensher and Greene than are catastrophe-dependent earnings) to 2003). We also test for the independence of managers, investors, and Wall Street analysts. irrelevant alternatives (IIA) assumption using the Hausman-McFadden test (Greene 2000). If the IIA assumption is violated, we estimate Data and Model Estimation the model using the heteroscedastic extreme value model (Train 2003). We use the likeli- Basic data hood ratio statistics to determine if individual The data needed for estimating our brand brand-specific constants need to be included. equity model comprise two major compo- nents—financial data and consumer survey data from the insurance industry. The financial Results data include cash flows of the brand broken out by product category (e.g., auto, property, The parameter estimates from the final brand and life insurance product categories) and data choice model for each category for data col- on the variables summarized in Table 2. The lected in 2004 appear in Table 3. The parame- consumer survey data are collected from a ran- ter estimates associated with inertia and dom sample of customers in each product cat- outside good preference variables were not sig- egory. These data cover attribute importance nificant as expected, so we do not report them. toward brand choice, perceptions of brand The best-fitting models for auto, property, and attributes, including brand image, brand favor- life insurance were heteroscedastic extreme ability, and brand perception scores or ratings value, multinomial logit, and multinomial logit or the variables contained in X and Z. model, respectively based on the BIC and like- lihood ratio criteria, so we report the results In addition, advertising expenditures are avail- for these models in Table 3. The model fits are able for the focal brand of insurance during fairly good with McFadden LRI of .66, .56, the period from 1998 to 2005. These data are and .46 for auto, property, and life insurance, particularly useful in analyzing the relationship respectively. The model fit is lower for the life between brand equity and advertising expendi- category than for the auto and property cate- tures. The results of such an analysis can gories, mainly because the sample size is lower provide important guidelines for tracking, for life than it is for auto or property (158 for building, and managing brand equity.4 life versus 443 for auto and 441 for property). The relative importance of a particular brand Model estimation in a product category can be determined once To determine relative brand importance for a the coefficients of all the variables in the brand in each product category, we estimate model are estimated. The coefficients for the three possible choice models: a multinomial other covariates are in the expected directions. logit model, a mixed logit model, and a het- As outlined earlier, the overall relative brand eroscedastic extreme value model, consistent importance of each brand in each category is with Fischer (2004). We select the appropriate computed by determining the predicted rela- model based on fit and interpretation of tive brand importance for each respondent and results. We first estimate the standard multi- aggregating it over all the respondents for each nomial logit model, consistent with Guadagni brand in each category. and Little (1983). Next, we test for hetero- geneity among consumers through fixed and The spillover effects of the brand from other random effects using the Hausman (1978) categories to the focal categories also appear test. If the test result suggests the need for in Table 3. The spillover effects of auto on controlling for heterogeneity, then we use a property and life categories and that of prop-

MARKETING SCIENCE INSTITUTE 60 lead over the focal brand in the auto category, Table 3 and its auto brand equity is higher than the Results of Choice Model Estimation for the Focal Brand focal brand’s by about $1.32 million. In the property and life insurance categories, how- Attribute Parameter Estimate (Standard error) ever, the focal brand’s equities are higher than Auto Property Life those of the overall market leader. In the prop- Brand image .18 (.05)*** .15 (.07)* .11 (.03)** erty insurance category, although the focal Insurance coverage/quality 1.14 (.24)*** .09 (.23) .05 (.02)* brand is ahead of the market leader in esti- Customer service –.04 (.16) .11 (.21) .11 (.26) mated offering value, it is behind the market Rates/price/premiums .55 (.12)*** .63 (.17)*** .32 (.14)* leader in estimated relative brand importance. Convenience .62 (.17)*** 1.17 (.23)*** .26 (.22) The estimated offering value is lower for the market leader, mainly because of lower cash Communication .11 (.18) .35 (.25) .37 (.26) flows due to catastrophic damages. In the life Sales force .44 (.18)** .39 (.20)* .40 (.24) insurance category, both the market leader and Spillover from auto NA .06 (.02)*** .04 (.02)* the focal brand have almost the same esti- Spillover from property .03 (.01)*** NA .03 (.09) mated relative brand importance, but because Spillover from life .02 (.05) .01 (.11) NA the focal brand has a higher offering value Final choice model used HEV # Multinominal Multinomial (due to superior cash flows) than that of the logit logit market leader, it has a greater estimated brand Sample size 443 441 158 equity as well. The contributions of spillover effects of the auto brand on the equities of the Log likelihood ratio –225.92 –186.26 –127.37 property and life brands are about 23% and McFadden’s LRI .66 .55 .46 21%, respectively, while that of the property Note: NA – Not applicable; *** p < .001, ** p < .01, * p < .05 brand on the auto brand is about 12%. These # – Hierarchical extreme value model. differences underscore the importance of esti- mating brand equity by category and across erty on the auto category are positive and sig- categories so that the true picture of the nificant (p < .05 or better). However, the brand’s health can be seen. spillover effects of life on the other two cate- gories are not significant (p > .10). Furthermore, the spillover effects of the auto Model Validation, Dimensions of brand on the other two product categories are Brand Image, and Robustness Checks higher than the remaining spillover effects. The results on spillover effects suggest that Model validation and brand image sustaining and enhancing the brand is more dimensions critical in the auto category than in the other To validate our model, we performed several two categories. analyses. First, we compared the estimate of brand equity from our model with that From the offering value (computed from obtained from an alternative method based on financial data) and the relative brand impor- self-explicated brand perception or dimension tance estimate, we calculated the estimates of scores obtained from the survey data. We brand equity for the focal brand and its closest chose the brand perception method as a competitor, the overall market leader. These benchmark over other complex methods such estimates are shown in Table 4. The focal as conjoint experiments because self-explicated brand has a multicategory brand equity of brand perception scores do a reasonably good $2.928 billion, but lags behind the overall job of eliciting consumer preference structures. market leader, which has a brand equity of In this method, we first determined the gen- $3.978 billion. The market leader has a huge eral relative importance of brand in each cate-

WORKING PAPER SERIES 61 Table 4 Brand Equity of the Focal Brand and Its Leading Competitor by Category

Brand Company Category Estimated Offering Estimated Relative Estimated Brand Value ($M) Brand Importance Equity ($M) Focal brand “The Company” Auto 37,276.75 4.43% 1,651.36 Property 19,633.81 4.17% 818.73 Life 8,657.66 5.29% 457.99 Focal brand Multicategory 65,568.22 2,928.08 State Farm State Farm Auto 64,616.96 4.60% 2,972.38 Property 14,688.10 4.37% 641.87 Life 6,884.12 5.29% 364.17 State Farm Multicategory 86,189.18 3,978.42

gory through an analysis of self-explicated The means of the brand perception dimensions brand importance. To obtain the relative brand and the overall relative importance of the brand importance for the focal brand, we adjusted in the category are provided in Table 5.6 The the overall brand importance by the impor- general importance of brand is highest in the tance of the focal brand relative to other life category (5.49%) and lowest in the property brands, based on the brand perception scores category (4.13%). To determine the relative for each brand in each category. brand importance for a brand relative to other brands, we need to predict brand image for the We also collected data on brand perception different brands. To come up with predicted scores for each brand on a set of 24 items (see brand image, we need to estimate a regression Appendix 2 for an exhaustive list) that extends model of self-explicated brand image on brand previous research (e.g., Aaker 1996; Fischer perception dimensions in which the coefficients 2004; Keller 2003). Based on a factor analysis reflect the weight of each brand impression of the survey data, we were able to identify dimension toward the overall brand image score eight key brand dimensions or factors.5 These for that brand. The perception scores vary by dimensions of the brand are: reputation, dimension and by brand. In the auto category, regard, uniqueness, fame, trust, fit, association, the focal brand’s perception scores are the high- and innovation. Our dimensions of brand per- est on the fame (3.58) and reputation (3.54) ception extend Fischer’s (2004) proposed dimensions and lowest on the fit (3.13) and dimensions to include fit, association, and innovation (3.15) dimensions. The market innovation components. The dimensions— leader also has high and low scores on the same uniqueness, innovation, fit, regard, and reputa- dimensions. However, the market leader’s aver- tion—can be viewed as equivalent to the age scores on these dimensions are higher than dimensions—differentiation, adrenaline, rele- the corresponding scores of the focal brand. For vance, esteem, and knowledge, respectively— example, the market leader’s brand fame score is advanced by Young and Rubicam (2006). We 3.66 and brand innovation score is 3.23. The also identify three additional dimensions— patterns in the property and life categories are trust, fame, and association—offering a com- similar to those in the auto category; only the prehensive set of drivers of brand image. The average scores in the property and life cate- five-point brand perception scale is more gories are higher than those in the auto formative than reflective. category.

MARKETING SCIENCE INSTITUTE 62 Table 5 Relative Brand Importance from Brand Perception Score Method

Brand Perception Dimensions General Brand Reputation Regard Uniqueness Fit Fame Trust Association Innovation Importance in the Category Auto 4.45% Focal brand 3.54 3.28 3.34 3.13 3.58 3.32 3.25 3.15 GEICO 3.47 3.22 3.49 3.16 3.48 3.17 3.17 3.48 Progressive 3.37 3.18 3.28 3.11 3.36 3.21 3.17 3.35 State Farm 3.64 3.42 3.42 3.29 3.66 3.42 3.37 3.23 Property 4.13% Focal brand 3.57 3.36 3.42 3.20 3.62 3.40 3.28 3.23 Farmer’s 3.42 3.26 3.15 3.11 3.29 3.27 3.20 3.10 Nationwide 3.43 3.29 3.25 3.11 3.38 3.24 3.15 3.14 State Farm 3.73 3.53 3.55 3.36 3.75 3.58 3.47 3.33 Life 5.49% Focal brand 3.54 3.29 3.36 3.19 3.48 3.36 3.28 3.23 MetLife 3.58 3.48 3.38 3.33 3.52 3.48 3.39 3.33 NY Life 3.83 3.65 3.61 3.42 3.79 3.66 3.55 3.43 Northwestern 3.70 3.56 3.51 3.38 3.69 3.56 3.51 3.38

Note. The brand perception scores are measured on a five-point scale.

The results of the regression of the brand validity of our proposed approach. From a image score on brand perception components theoretical standpoint, the proposed choice appear in Table 6.7 The goodness of fit modeling approach explicitly considers the (adjusted R2) for each category is high, given role of brand relative to other attributes (such that the data are purely cross-sectional as quality, service, and salesperson influence). (Hanssens, Parsons, and Schultz 2001). In From an empirical perspective, because both each category, uniqueness and fit are signifi- the proposed choice modeling approach and cant determinants of brand image. For the the brand perception score method provide auto and the property categories, innovation is similar estimates of relative brand importance a significant driver of brand image (p < .05). for the focal brand, we need to evaluate the Association is significantly related to brand predictive validity of our proposed method to image for the life category (p < .01), unlike its be able to justify its use. We assess the pre- relationship to brand image for the auto and dictive validity of the choice model by com- the property categories. paring the results from its estimation to those derived from the brand perception score A comparison of the results for relative brand method. The comparative results are shown importance between the choice model and in Table 8. The proposed method based on the brand perception score method is shown choice model outperforms the brand percep- in Table 7. The relative brand importance tion score method in each category. There- values obtained from these two methods are fore, we retain the proposed approach for not very different, suggesting strong face estimating brand equity.

WORKING PAPER SERIES 63 Second, we compare the relative positions of Table 6 the focal brand and the overall market leader Results of Model of Brand Image on Its Drivers (Brand based on estimates of brand equity from our Dimensions) model and estimates of price premiums that consumers are willing to pay to stay with the Dependent Variable: Brand Image Score chosen brand. Price premium has been used as Auto Property Life a measure of brand equity by prior studies Intercept .86 (.08)*** .31 (.05)*** .66(.08)*** (e.g., Hjorth-Anderson 1984; Holbrook Reputation .06 (.05) .03 (.05) .01 (.05) 1992). The average switching price premiums Regard .14 (.06)** .05 (.03) .12 (.05)* for the different brands in the three categories Uniqueness .26 (.04)*** .28 (.03)*** .21 (.05)*** are shown in Table 9. These data are obtained Fit .45 (.04)*** .41 (.03)*** .36 (.05)*** directly from the consumers through a specific question in the survey that asks the respon- Fame .10 (.04)** .04 (.03) –.02 (.04) dent to report the percentage price decrease Trust –.07 (.05) .02 (.03) .01 (.05) needed for the respondent to switch from her Association .02 (.05) .05 (.03) .13 (.05)** or his current brand of insurance. The price Innovation .08 (.04)* .05 (.02)* .04 (.04) premiums are fairly consistent with the esti- Sample size 1,716 1,466 716 mated brand equities, suggesting face validity Adjusted R 2 .74 .70 .71 for our brand equity approach.

Note. Standard errors in parentheses. *** p < .01, ** p < .05, * p < .10 Third, we compare the relative positions of the focal brand and the overall market leader based on brand equity estimates from our

Table 7 model and measures of loyalty toward the Comparison of the Focal Brand’s Relative Brand Importance from chosen brand, intention to repurchase the Choice Model and Brand Perception Score Method brand, and intention to recommend the brand to others, consistent with Lam et al. (2004). Category Estimated Relative Brand Difference Statistically These brand loyalty items are measured on a Importance in % Significant? (p < .05) five-point scale. The average estimates of Choice Model Brand Perception score brand loyalty appear in Table 10. These loyalty estimates are consistent with the estimates of Auto 4.43 4.39 No brand equity for different brands in Table 9. Property 4.17 4.18 No The correlations of brand equity with the Life 5.29 5.35 No repeat buy and recommend measures of loyalty are positive and significantly (p < .01) high at .73 and .92, respectively.

Table 8 Robustness checks Predictive Validity (Hit Rates*) of Choice Model and Brand We performed several robustness checks for Perception Score Method for the Focal Brand the proposed choice model. First, we tested for interactions between brand and each attribute Auto Property Life or marketing mix element in the choice of a Choice model 81.0% 83.5% 73.4% brand. The likelihood ratio tests did not reject Brand perception score method 75.2% 76.5% 62.1% the null hypothesis of no interactions (p > .10) Sample size 443 441 158 in each of the three categories. Second, we

*Hit rate is the proportion of correct predictions of the actually chosen brand. For prediction purposes, compared a multiplicative attraction model in each category, the brand with the highest purchase probability is defined as the predicted brand with log-transformed variables to our choice choice. model using non-nested model tests and

MARKETING SCIENCE INSTITUTE 64 variables as necessary. In sum, the robustness Table 9 checks showed that the proposed choice model Model Validation: Average Switching Price Premiums is able to estimate relative brand importance fairly well for all three categories. Auto Property Life Focal brand 41.19% 35.35% 41.35% State Farm 40.50% 43.32% NA Relating Brand Equity to Advertising GEICO 39.83% NA NA and Shareholder Value Progressive 37.80% NA NA Farmer’s NA 36.23% NA A firm’s advertising efforts lower its systematic risk and may be related to its shareholder value Nationwide NA 43.28% NA (McAlister, Srinivasan, and Kim 2007). MetLife NA NA 48.57% Advertising is an ideal marketing instrument NY Life NA NA 40.14% for preserving and enhancing brand equity Northwestern Mutual Life NA NA 54.13% and shareholder value (Keller 1993; Joshi and No. of observations 443 441 158 Hanssens 2004). One way in which advertis-

Note. NA – Not applicable or the brand is not a big player in the category. ing could be related to shareholder value is through brand equity. To explore this link, we found that our proposed choice model offers investigate the relationships between brand a better fit than alternative models (p < .05) equity and advertising and between brand (Davidson and MacKinnon 1981; Pollack and equity and shareholder value. Identification of Wales 1991). Third, we included demographic these relationships can help determine effec- variables as additional covariates and tested for tive advertising expenditure levels through model differences, using likelihood ratio tests. “what if ” scenarios. The tests rejected the additional demographic covariate model for auto and property cate- Relating brand equity to advertising gories (p < .10). For the life category, the test spending was rejected at a marginal level (p < .12), so To examine the role of advertising spending in we do not view the inclusion of demographic creating brand equity, we estimate a regression

Table 10 Model Validation: Average Loyalty Scores

Auto Property Life Repeat Buy Recommend Repeat Buy Recommend Repeat Buy Recommend Focal brand 4.67 4.36 4.53 4.18 4.65 4.21 State Farm 4.73 4.40 4.61 4.21 NA NA GEICO 4.73 4.58 NA NA NA NA Progressive 4.48 4.18 NA NA NA NA Farmer’s NA NA 4.68 4.34 NA NA Nationwide NA NA 4.50 4.06 NA NA MetLife NA NA NA NA 4.68 4.15 NY Life NA NA NA NA 4.60 4.26 Northwestern Mutual Life NA NA NA NA 4.78 4.55 No. of observations 443 441 158

Note. NA – Not applicable or the brand is not a big player in the category. The loyalty scores are on a five-point scale.

WORKING PAPER SERIES 65 Relating brand equity to shareholder value Table 11 To examine the relationship between brand Results of Regression of Brand Equity on equity and shareholder value, we compute the Advertising Stock correlation between the net present value (NPV) of abnormal stock market returns for Variable Estimate (Standard Error) the company and its brand equity. Consistent Intercept .7626 (.0457)*** with prior event studies in finance (e.g., Fama Advertising stock .0026 (.0001)*** and French 1993) and in marketing (e.g., Sample size 7 Kalaignanam, Shankar, and Varadarajan 2007; R2 .91 Sorescu, Chandy, and Prabhu 2003; Sorescu,

Note. *** p < .001 Shankar, and Kushwaha 2007), we use abnor- mal returns as a measure of stock market per- formance. Following Fama and French (1993), model of brand equity on advertising stock we compute the monthly abnormal returns for using advertising spending data over multiple the company owning the brand using the fol- 9 time periods. Following Broadbent (1979) and lowing three-factor model. Rizzo (1999), we first developed the advertis- Ϫ ϭ ␣ ϩ ␤ Ϫ ϩ ing stock variable, using a Koyck form that Rpt Rft p p(Rmt Rft) captures the distributed lag structure of adver- ␥ ϩ ␦ ϩ ␧ pSMBt pHMLt pt (10) tising’s effect as follows.

where Rpt is the rate of return of the firm p ϭ Ϫ ␭ ϩ ␭ owning the brand during month t, and R is ADSit (1 ) Ait ADSi (t Ϫ 1) (8) ft the rate of return on a U.S. Treasury bond f where ADS is advertising stock in dollars, A is during the same period. Rmt is the average rate advertising spending in dollars, ␭ is the peri- of return of all stocks trading on the U.S. stock odic advertising carryover or decay rate, and t market, SMBt is the difference between the is the time period.8 For the focal brand’s rate of returns of small and big firm stocks advertising spending data over a period of (small minus big), and HMLt is the difference 10 years, this formulation produced a decay in returns between high and low book-to-mar- rate of .20. ket stocks (high minus low), all during month ␧ ␣ t. pt is an error term, is the model intercept, We then estimated the brand equity- and ␤, ␥, and ␦ are parameters associated with advertising model, which is given by: the three factors used in the model. We multi- ply the monthly abnormal returns by 12 and ϭ ␪ ϩ ␪ ϩ␵ BEit 0 1ADSit it (9) the market capitalization of the firm at the end of the year to obtain the change in NPV where ␵ is an error term, ␪ and ␪ are param- t 0 1 or aggregate abnormal returns for the firm in eters, and the other terms are as defined the year. before. The results of the brand equity- advertising stock regression model for the We examine the correlation between the focal brand appear in Table 11. Although the change in the firm’s NPV and its brand equity 2 sample size is small, the high degree of fit (R predicted from the brand equity-advertising = .91) indicates that advertising stock is signif- stock model. This approach is consistent with icantly positively related to brand equity. We that of Barth et al. (1998), who analyze the use the predicted values of brand equity from relationship between share price and brand this equation in the subsequent model relating equity as reported by Interbrand. The correla- brand equity to shareholder value. tion turns out to be significant (.44, p < .05) in our data, indicating that brand equity has a

MARKETING SCIENCE INSTITUTE 66 Figure 2 Brand Equity, Advertising, and Abnormal Returns over Time

positive and significant relationship with which, in turn, is positively and significantly shareholder value. We also computed the correlated with shareholder value. abnormal returns, using the buy-and-hold method, and the results were similar to those from the three-factor model. The results are Tracking and Managing Multicategory consistent with the finding that corporate Brand Equity branding strategy (the use of the firm name across categories) is positively associated with Brand equity is dynamic and needs to be firm performance as measured by Tobin’s q measured and monitored periodically. (Rao, Agarwal, and Dahloff 2004). Tracking, building, and managing brand equity involves periodically measuring brand A time plot of the focal brand’s brand equity, equity and planning and executing suitable advertising stock, and abnormal returns from marketing initiatives, including advertising the three-factor model and buy-and-hold campaigns. To track brand equity and to gen- method appears in Figure 2. At higher levels erate answers to “what if ” scenarios, counter- of advertising stock and brand equity, the factuals, or policy experiments, we developed a abnormal returns are less volatile. This result brand equity simulator. The simulator is based on advertising is consistent with McAlister, on an Excel spreadsheet and takes as inputs Srinivasan, and Kim (2007). Therefore, we the financial variables such as long-term infla- conclude that advertising efforts are positively tion rate, the firm’s WACC, marginal tax rate, and significantly linked to brand equity, investment rate, and EBITDA margin ratio

WORKING PAPER SERIES 67 with and without catastrophes for each prod- Methodological impact: Use of marketing uct category. In addition, an executive can science methodology input the quarterly or annual projected rev- Our model and the simulator have brought enues and operating costs for the brand by innovative and rigorous applications of mar- category. The simulator provides the upper keting science (economic and econometric) and lower bounds of brand equity for the models to the largest publicly-listed company company’s brand and the corresponding adver- in one of the most important industries, con- tising spending for that period that would sistent with Lilien and Rangaswamy (2002). maintain the particular value of brand equity. Although the company could have chosen an Conversely, for given financial rates and ratios approach from a large number of alternative and a target value of brand equity, one can brand equity models, it chose our model determine the operating profits or the adver- because we were able to demonstrate the value tising spending needed to achieve the targeted addition of our approach over the other mod- brand equity. els (see Table 1 and the next section for a comparison of our method with several alter- The simulator offers useful managerial guide- native methods). lines. First, managers can use the simulator to estimate the equity of their brands, particularly The most innovative aspects of our approach in situations where their brands are in multiple relate to how we developed a model for esti- categories. Second, they can perform sensitiv- mating the equity of a brand that cuts across ity analyses by exploring the impacts of finan- multiple product categories and how we cial measures such as cash flows, investment implemented it. First, our brand equity model rate, and discount rate and of survey measures combines financial data with marketing data, such as attribute ratings. They can better esti- and secondary data with primary data, in a mate the return on improving specific brand way that is both economically and econometri- equity dimensions through “what if ” sensitiv- cally sound. Second, our analysis goes beyond ity or simulation analyses of the effect on estimation of brand equity to determination of brand equity together with cost estimates of the relationships between brand equity and such improvements. Third, an executive can advertising spending and between brand track the levels of brand equity by category equity and shareholder value. Analysis of these over time and take suitable actions based on relationships provides managers with the diag- the changes to the equity. He or she can drill nostics and insights into formulating effective down into the components of brand equity to advertising budgets. Third, our model satisfies assess the relative effects of changes in the many of the considerations of accounting components. Fourth, by analyzing the rela- research for valuing intangible assets, namely, tionship between advertising and brand equity the U.S. GAAP and FASB criteria of rele- and shareholder value, managers can better vance, reliability, comparability, understand- estimate the impact of advertising and change ability, and cost effectiveness. Furthermore, the their advertising expenditures appropriately for model has a future orientation and is complete desired results. and verifiable, which are also important from an accounting viewpoint. Fourth, the model captures the spillover effects of the brand from Organizational Impact one category to another. Fifth, it enables the brand managers to identify the key dimensions Our work has had significant organizational that drive brand equity and take suitable impact along several dimensions—method- actions to improve the brand’s position. Sixth, ological, strategic, financial, portability, busi- in addition to being a rigorous model, it is ness practice, and cultural. easy to implement through the brand equity

MARKETING SCIENCE INSTITUTE 68 simulator. Finally, a unique feature of our auto category than it had in the past. Further- model is that it accounts for the impact of more, by understanding the key drivers of catastrophes, which is critical in the insurance brand equity, the company could determine industry. ways to improve its brand equity by about 5% and its contribution to market capitalization Strategic impact by 11%. The model and the simulator helped The estimation of brand equity from a con- senior management reallocate fixed marketing sumer perspective—particularly, the relative expenses among different product categories brand importance or the utility of the brand (brand tax). An insightful financial result is relative to other attributes—quantified the that the benefits experienced by the life insur- tradeoffs involved in spending on brand build- ance product category or business from the ing, price reductions, and customer experience company’s focal brand were disproportionately enhancements. Furthermore, the relative greater than the marketing resource allocation importance of the brand dimensions provided it received. The long-term benefits of the useful directions in setting brand communica- model and simulator are expected to be tion objectives. In addition, the model and substantial. simulator enabled the company to determine the areas in which the company was stronger Portability or cross-functional/knowledge and weaker than its competitors and plan management impact appropriate strategic actions. It has also helped The BRAN*EQT simulator is truly cross- the company better understand how its brand functional in that it can be used by executives equity is derived from the auto, property, and from marketing, finance, accounting, and life insurance businesses and how changes in strategy. It is also portable in that the learning its product mix across these categories could and best practice derived from BRAN*EQT impact brand equity. can be leveraged to measure the equities of other brands owned by the company and out- Financial impact side brands that could be potential acquisi- The financial impact of BRAN*EQT is hard to tions. The model is broad, that is, it can be estimate because many of its benefits will used for both goods and services in different likely be realized in the long term.10 However, contexts, B2C and B2B. Importantly, it repre- one estimate of the return on investment sents a rare case of the marketing function (ROI) for the development and implementa- taking the leadership and owning a strategic tion of BRAN*EQT is more than 2,500%. This initiative that is scientifically and tangibly estimate is partly based on a short-term net linked to the fundamental goal of the enter- savings of about $10 million, resulting from a prise, namely, the maximization of shareholder reallocation of advertising budget to improve value in the largest publicly traded insurance the value of the company’s offerings and brand company. In this regard, we have the backing equity, after accounting for the cost of building of the senior management team, including the model and the simulator. The model sup- the senior vice president and chief marketing ported an increase in advertising allocation of officer. 70%. As a result of the reallocated advertising efforts, brand awareness increased by 18% in Cultural impact the first year after reallocation, although the Culturally, the model and simulator have share of advertising in the market did not sig- changed the way senior management looks at nificantly increase. the value of the company’s flagship brand in four ways. First, prior to our work, the value The spillover effects enabled the company to of the brand within the company had always redirect advertising efforts more toward the been “fuzzy” (e.g., statements such as “We

WORKING PAPER SERIES 69 have a valuable asset” or “Our brand has to be challenging because it needed accurate national or international recognition or measures of all costs, involving input from appeal” were the common ways in which the several finance and accounting departments value of the brand was articulated). Not much within the company. Moreover, financial data effort had gone toward determining the equity for some competitors proved elusive. For of this brand and how top management could example, one of the competitors, GEICO, is use this measure to track the health of the a subsidiary of Berkshire Hathaway, so its company and improve its return on its adver- detailed financials are not available by cate- tising efforts and shareholder value and guide gory. Furthermore, the market leader is a investors. Our modeling approach brought mutual company, so its category-level finan- about a fundamental change in the mindset cials are not publicly available. In this regard, and culture of the company with regard to we learned to be prepared to pore over differ- branding and advertising. The mindset has ent sources and triangulate from these sources changed from a view of these activities as to arrive at reasonable and reliable estimates. “warm and fuzzy” to one that considers brand- ing and advertising as a scientific way to lever- The second problem concerns forecasting age a key marketing asset for improving catastrophes and estimating the potential costs shareholder value. Second, the model has been that go into the future earnings stream. able to convince nonmarketing functional Although we could use past incidences of executives of the value of brand and marketing catastrophes and their financial consequences in general. Third, our approach has brought as a guide, an accurate assessment of the inci- accountability to senior managers because it dence and severity of catastrophe is difficult enables them to focus on brand equity and on because even the best meteorologists’ predic- ways to improve it. Finally, there is a change tions are unreliable. To overcome this problem, in top managers’ view from marketing as an we computed multiple estimates of earnings expense to marketing as an investment. based on different scenarios and came up with upper and lower bounds for brand equity. In summary, our brand equity model and proj- ect served as a turning point as the company The third problem relates to linking brand rediscovered the value of marketing. The equity to advertising in an intuitive and user- model’s strategic, financial, operational, and friendly manner so executives can make cultural impacts have been significant, and the decisions on reallocation of advertising expen- company’s marketing team is now perceived as ditures. Our model estimates an advertising leading the company and the industry. stock and relates it to brand equity over time. The principle guiding the computation of advertising stock was not readily understood Some Practical Issues and Managerial by nonmarketing executive users of the Learning BRAN*EQT simulator tool. The simulator had to be redesigned in such a way that it provided There are several implementation hurdles we a step-by-step account of how a change in had to cross to successfully design and imple- advertising spending affected brand equity. We ment our model, leading to valuable manage- learned that when it comes to a decision sup- rial lessons. The first hurdle relates to data port simulator, ease of understanding, not just collection. Although the financial data for ease of use, is important. the company appear to be easiest to collect because they are internal in nature, compu- The fourth issue relates to setting up a system tation of accurate measures such as to track brand equity. To update brand equity EBITDAMR at a category level turned out estimates, the company needs to collect con-

MARKETING SCIENCE INSTITUTE 70 sumer survey data periodically. However, some is that although the composition of cash flows team members who are involved in the data needs to be scrutinized, the time spent on such collection might get promoted or transferred an effort should be commensurate with the to different positions in the company during anticipated gains in improving the quality of the course of the year. To ensure that data col- the brand equity estimate to justify such an lection and estimation are consistent, the com- onerous task. pany needs to follow a standard procedure. We learned that documentation of survey data col- lection procedure is critical to successful adop- Limitations, Future Research, and tion of a brand equity model. Summary

The fifth challenge concerns revisions to Our approach has certain limitations that financial estimates. The simulator allows users could be addressed by future research. First, to revise the inputs, including projected rev- our consumer survey data may contain meas- enues and interest rates, as and when they get urement errors. Second, we make certain more accurate estimates of these variables. assumptions on the financial variables such as These revised inputs may lead to changes in cost of capital and investment rate. While the levels of effective advertising expenditures. these assumptions are fairly accurate for the If decisions on advertising allocations and company providing the data, we may not have media-buying decisions have already been reliable private information on these variables made, it is not practical to change the budget. for the competitor firms. Third, the empirical To limit this problem, the company needs to analyses of the relationships between brand plan for flexibility in the advertising budget equity and advertising spending and between and media-buying decisions. The company has brand equity and shareholder value are based already moved in this direction. For the 2006 on limited sample size, so the results need to TV season, of a total TV network advertising be treated with caution. With greater data, a budget of about $100 million, the company more comprehensive analysis could be per- slashed its upfront spending to $10 million formed. Fourth, survey data were available for from $70 million two years before (Angwin only a limited number of periods, so the esti- and Vranica 2006). Thus, keeping the model mates of brand equity in some periods are and simulator flexible to receive new or revised based partly on imputations. Addressing these input data is important to the success of a issues might lead to a more accurate estimate brand equity model and simulator. and the discovery of more interesting relation- ships between brand equity and firm value. The sixth challenge was to disentangle the cash flows attributable to the offerings carry- In conclusion, we have developed a robust ing the focal brand name during the data model and decision support simulator for esti- period when the company acquired another mating, tracking, and managing brand equity small brand. With the help of the company’s for multicategory brands based on a combina- finance department executives, we followed a tion of customer survey and financial measures careful and systematic process of separating for each product category. To our knowledge, the cash flows by the brand based on the orig- this is the first model to rigorously estimate inal accounting data. However, the cash flows the equity of a multicategory brand capturing associated with the acquired brand were rela- spillover effects across categories, identify tively very small, so the removal of the cash brand image drivers, and relate brand equity to flows related to this brand did not result in a advertising and shareholder value. We have significant change in the estimate of the focal applied this model to estimate the equity of brand’s equity. Our key takeaway in this regard the flagship brands of a leading insurance

WORKING PAPER SERIES 71 company and its leading competitor, which reallocating its advertising resources to carry their brand names in multiple product improve brand equity and shareholder value, categories. Furthermore, we identified the and by offering better strategic guidance and drivers of brand image and examined the rela- insights to managers, investors, and analysts. tionships between advertising and brand equity and between shareholder value and brand equity, using longitudinal data on adver- Acknowledgments tising, brand equity, and abnormal returns. Our model provides reliable estimates of brand We thank Tarun L. Kushwaha, Kartik equity for the focal brand and a leading com- Kalaignanam, and Thomas Dotzel for data petitor brand, and our results show that assistance. We are grateful to Steve Shugan, advertising has a strong long-term positive John Roberts, Gary Lilien, anonymous review- influence on brand equity for the company. ers, participants at the 2006 Marketing The model, the brand equity estimates, and Science conference, the 2006 Fall Marketing the simulator are used by key executives in Science Institute (MSI) Trustees meeting, the company across multiple functional areas research seminars at Harvard University, the such as marketing, strategy, accounting, and University of Houston, and the University of finance. This brand equity model and simula- California at Davis, the MSI review team, and tor have enabled the company to substantially Alina Sorescu for helpful comments. gain by realizing the value of marketing, by

Appendix 1: Derivation of Relative The relative brand importance or the share of Brand Importance brand image toward choice is given by:

Recall that we define relative brand impor- RBI ϭ tance as the incremental choice probability ik ѨPr attributable to the brand image divided by the ik dV sum of incremental choice probabilities due to Ѩ Bik VBik ϭ (A1.2) brand image and the marketing mix variables. dPr Following Fischer (2004), we decompose a ik ␳Pr (1 Ϫ Pr )dV change in consumer k’s probability of choosing ik ik Bik brand ( ) through its total differential. ␳ Ϫ ϩ ϩ ␳ Ϫ i Prijkt Prik(1 Prik)dVPik ... Prik(1 Prik)dVBik Dropping category and time subscripts j and t, respectively, for expositional ease, we get: RBIik = dV Bik (A1.3) ѨPr ѨPr dV + dV + dV + dPr ϭ ik dV ϩ ik dV ϩ ... ϩ Pik Qik Dik ik Ѩ Pik Ѩ Dik VPik VDik dVCik + dVSik + dVBik

ѨPr Assume that there exists a situation where ik dV ϭ ␳Pr (1 Ϫ Pr )dV ϩ ... ϩ Ѩ Bik ik ik Pik individual k derives zero utility from brand i, VBik i.e., Vik* = 0. Without loss of generality, if the ␳ Ϫ utility function is allowed only non-negative Prik(1 Prik)dVBik (A1.1) values for the subutilities, then V Pik* = V Qik* = where ␳ is a scaling factor for utility resulting V Dik* = V Cik* = V Bik* = 0. Thus, Vik – V ik* =Vik from normalizing the error variance for model and the share of brand image toward choice identification. reduces to:

MARKETING SCIENCE INSTITUTE 72 ␤ X RBI = B Bik (A1.4) ik ␤ X + ␤ X + ␤ X + ␤ ␤ ␤ B Bik Q Qik P Pik DXDik + CXCik + SXSik

Appendix 2: List of Measurement Items for Brand Perception/Impression Completely Does not describes the describe the brand brand at all

_____ a. The brand has a good reputation. 5 4 3 2 1 _____ b. I have high regard for this brand. 5 4 3 2 1 _____ c. The brand stands out well from the other brands of insurance. 5 4 3 2 1 _____ d. The image of this brand of insurance fits my personality well. 5 4 3 2 1 _____ e. This brand is a leading brand of insurance. 5 4 3 2 1 _____ f. I trust this brand. 5 4 3 2 1 _____ g. I would be proud to be associated with this brand. 5 4 3 2 1 _____ h. This brand is innovative. 5 4 3 2 1 _____ i. This brand is good value for money. 5 4 3 2 1 _____ j. This brand has a rich history. 5 4 3 2 1 _____ k. I admire this brand. 5 4 3 2 1 _____ l. This brand is distinct from other brands in the category. 5 4 3 2 1 _____ m. This brand is of high quality. 5 4 3 2 1 _____ n. This is a popular brand. 5 4 3 2 1 _____ o. This brand projects a positive image. 5 4 3 2 1 _____ p. This brand carries little risk. 5 4 3 2 1 _____ q. This brand is reliable. 5 4 3 2 1 _____ r. This brand is novel. 5 4 3 2 1 _____ s. This brand is modern. 5 4 3 2 1 _____ t. This brand is a classic. 5 4 3 2 1 _____ u. I identify myself with this brand. 5 4 3 2 1 _____ v. This brand is a mature brand. 5 4 3 2 1 _____ w. This brand is a premium brand. 5 4 3 2 1 _____ x. This brand is a high-performance brand. 5 4 3 2 1

Appendix 3: Glossary of Terms Offering value: The net present value or financial worth of an offering (a product or a good or service or a bundle Brand equity: The net present value of the incremental of goods and services) carrying a brand name. cash flows attributable to a brand name and to the firm that owns that brand name, relative to an identical prod- Relative brand importance: The importance of brand uct with no brand name or brand-building efforts. image relative to all the attributes in brand choice in a given product category. The incremental choice probabil- Brand revenues: Net revenues for the brand in the cate- ity attributable to the brand name divided by the sum of gory of interest. incremental choice probabilities due to the brand name and the marketing mix variables. EBITDA: Earnings before interest, taxes, depreciation, and amortization. Shareholder value change: The change in the net pres- ent value of aggregate abnormal returns for the firm dur- Investment rate: The rate of investment or replacement ing a given year. expenditures as a percentage of brand revenues. WACC: Weighted average cost of capital. A weighted Marginal tax rate: Effectively paid taxes as a percentage percentage of the mix of the cost of private equity and of cash profits. debt according to the firm’s target capital structure.

WORKING PAPER SERIES 73 Notes

1. For expositional ease, we use the terms consumer and 6. We checked the reliability and discriminant validity of customer interchangeably throughout the paper. the measures and found them to be satisfactory. The details are available from the authors. 2. If time series data are available for the same respon- dent/consumer, we could also use the category-level 7. We checked for possible multicollinearity among the brand equity values estimated from the previous period. brand dimensions. The correlations among the brand dimensions were not very high. The VIF factors were 3. Relative brand importance can be adjusted for brand between 1.3 and 2.7, suggesting that multicollinearity is awareness, preference, and availability where necessary not a problem in our data. and when data are available. Relative brand importance can also be determined using a conjoint analysis study. 8. We deflated a period’s nominal advertising spending dollars using the consumer price index (CPI) for all 4. The data are disguised to preserve confidentiality of items during the corresponding period. the information owned by the company. 9. We also estimated a four-factor model that includes 5. We could also use constrained component analysis the momentum factor (Carhart 1997), but the substan- (CCA) recommended by Dillon et al. (2001) to disen- tive results did not change, so we retain the three-factor tangle ratings on general brand impressions from those model. on brand or offering attributes. However, in our case, because the product attributes are already captured in the 10. We are constrained in reporting the full financial choice model, a factor analysis is more appropriate. impact due to confidentiality of company information.

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