A Product-Market-Based Measure of Brand Equitymktg.uni-svishtov.bg/ivm/resources/ProductMarketMeasureofBrand... · A Product-Market-Based Measure of Brand Equity ... Existing measures

A Product-Market-Based Measure of Brand Equity

Kusum L. Ailawadi, Donald R. Lehmann, and Scott A. Neslin

M A R K E T I N G S C I E N C E I N S T I T U T E

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A Product-Market-Based Measure of Brand Equity

Kusum L. Ailawadi, Donald R. Lehmann, and Scott A. Neslin

M A R K E T I N G S C I E N C E I N S T I T U T E

W O R K I N G P A P E R S E R I E S

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Copyright © 2002 Kusum L. Ailawadi, Donald R. Lehmann, and Scott A. Neslin

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A Product-Market-Based Measureof Brand EquityKusum L. Ailawadi, Donald R. Lehmann, and Scott A. Neslin

In spite of all the attention brand equity has received in the past decade, relativelylittle is known about how to measure it or how it changes over time. In this report,authors Ailawadi, Lehmann, and Neslin propose a simple and easily quantifiablemeasure of brand equity and validate it by examining its behavior over time andacross product categories, and in response to marketing activities such as advertis-ing and promotion.

They conceptualize product-market-level brand equity as the incremental revenuethat the brand earns over the revenue it would earn if it were sold without thebrand name. The equity of the brand is calculated as the difference in revenue (i.e.,price x volume) between a branded good and the corresponding private label.

They examine the measure for brands in 23 packaged goods categories over aseven-year period. The measure is found to be stable, yet still related in expectedways to marketing activities (that is, positively associated with advertising but notwith promotion) and industry trends (in general it declined during the periodwhen conventional wisdom suggests that national brands lost out to store brands).Further, the brand equity measure is positively associated with stockpileability andhedonic categories and negatively associated with private label quality.

Finally, the “up” own-price elasticity, i.e., the effect on sales when price is increased,is significantly lower than the “down” own-price elasticity for high equity brands.

Overall, this measure of brand equity offers several advantages to marketing man-agers. It is a simple measure that can serve as a practical standard of performanceand it is readily calculable from existing internal statistics or publicly available data.Importantly, it should also have credibility with financial and operating managerswho understand and see the value of increased revenue.

Kusum L. Ailawadi is Associate Professor of Business Administration, Amos Tuck Schoolof Business Administration, Dartmouth College. Donald R. Lehmann is George E.Warren Professor of Business, Graduate School of Business, Columbia University andExecutive Director 2001-03, Marketing Science Institute. Scott A. Neslin is AlbertWesley Frey Professor of Marketing, Amos Tuck School of Business Administration,Dartmouth College.

Contents

Introduction ...........................................................................................................3

Conceptual Background .........................................................................................5

The Proposed Product-Market-Level Measure ........................................................7

Empirical Measurement........................................................................................13

Data ................................................................................................................13

Descriptive Statistics and Trends......................................................................13

Validation of the Measure.....................................................................................19

Hypothesized Association with Marketing Mix and Category Variables ..........19

Observed Association with Marketing Mix and Category Variables.................20

Impact on Price Elasticity ................................................................................21

Summary and Discussion .....................................................................................25

Notes....................................................................................................................29

References.............................................................................................................31

Tables

Table 1. Product Categories Studied................................................................14

Table 2. Descriptive Statistics for Equity Measure ...........................................15

Table 3. Changes in Equity during the 1990-1996 Period...............................16

Table 4. Equity Changes across Product Categories....................................17-18

Table 5. Correlations with Marketing Mix and Category Variables .................20

Table 6. Regression of Equity on Marketing Mix and Category Variables .......21

Table 7. Effect of Brand Equity on Price Elasticity ..........................................22

Table 8. Prepared Tea Volume and Price Data .................................................25

Table 9. Snapple Brand Equity: Prepared Tea ..................................................26

Figures

Figure 1. Gross Brand Equity Premium: Four Possibilities.................................9

Figure 2. Net Equity Premium: Four Possibilities ............................................10

Marketing Science Institute 3

IntroductionThe concept of brand equity has been widely discussed over the past decade (Aakerand Keller 1990; Aaker 1991), with much of the work stemming from aMarketing Science Institute conference on the topic (Leuthesser 1988). During thesame time period, companies have paid increasing attention to brands, often, forexample, creating the position of brand equity manager. This emphasis was espe-cially evident during 1999 as Internet-based companies spent massively, if noteffectively, to acquire customers and establish brand names. Yet, in spite of all theattention to brand equity, little is known about how to measure it or how itchanges over time. The purpose of this paper is to propose a specific measure andexamine its behavior over time, across product categories, and in response to mar-keting activities such as advertising and promotion.


Conceptual BackgroundResearch in the brand equity area has focused largely on brand extensions, particu-larly on how well equity in one product extends to other categories (e.g., Aakerand Keller 1990; Broniarczyk and Alba 1994; Park, Milberg, and Lawson 1991).More recently the focus has turned to the impact of brand extensions on the origi-nal brand (Roedder John and Loken 1993). While it is widely acknowledged thatbrand equity is related to both technical capability and image (Batra, Lehmann,and Singh 1992), remarkably few papers have addressed brand equity measure-ment per se, in spite of the fact that both brand equity and metrics have been pri-ority topics of the Marketing Science Institute for the last 10 years. Part of the lackof emphasis on measurement can be traced to confusion and disagreement overwhat is to be measured. At an MSI conference in 1999 on the topic, clear disagree-ment arose over whether it was appropriate to try to capture brand equity as a sin-gle number or if it was necessary to capture multiple facets of the construct.

Existing measures of brand equity generally fall into one of three categories (Kellerand Lehmann 2002). First, there are measures related to customer mindset, that is,the attitudes, associations, and attachment customers have toward the brand. Thiscategory has been the focus of both academic research (e.g., Ambler and Barwise1998) and the measures provided by suppliers such as Research International’sEquity EngineSM, Young & Rubicam’s BrandAsset Valuator, and MillwardBrown’s BRANDZTM. These measures have useful diagnostic power and richnessbut do not provide a simple criterion against which to measure performance.

The second category of measures focuses on outcomes at the product-market level.The most commonly mentioned of these is price premium, the extra amount paidfor branded versus private label (or generic) merchandise, or the related conceptsof brand clout and vulnerability as measured by the brand’s own and cross-priceelasticities (Kamakura and Russell 1993). Other measures of this type include theconstant term in sales response models (Srinivasan 1979) or the residual in hedo-nic regression, i.e., market inefficiency (Hjorth-Andersen 1984), but they do notcapture the interaction of equity with marketing mix activities such as advertisingand price. Recently, Dubin (1998) has proposed a product-market-level measurethat attempts to quantify the difference between the profit earned by the brandand the profit it would earn if it were sold without the brand name. While poten-tially less diagnostic, product-market-level measures have the advantage of beingfairly unambiguous as well as credible/important to executives outside the market-ing function. In the rest of this paper, we focus on a measure of this type.

The final category of measures is based on the financial market. Specifically, theseassess the value of the brand as a financial asset. Purchase price when a brand is soldor acquired (Mahajan, Rao, and Srivastava 1994) and discounted cash flow valua-tion of licensing fees and royalties are measures of this type. Interbrand’s measure isa hybrid of product-market and financial-market measures, which basically startswith the revenue premium the brand enjoys and adjusts it for growth potential etc.

6 Marketing Science Institute

Simon and Sullivan (1993) develop a measure that is the residual once other sourcesof firm value are accounted for. While these measures obviously have relevance toCFOs and CEOs, they are subject to both considerable variability (e.g., Snapple’ssale price went from $1.7 billion to $300 million in just over two years, and thenback to about $1 billion a few years later) and subjective judgment (i.e., the multi-ples applied by Interbrand). They also have less immediate relevance to marketingsince many things other than marketing activities impact them. Thus, we focus on aproduct-market measure, both because such measures have received relatively littleattention, and because this metric is relevant to product managers, chief marketingofficers, and CEOs alike.


The Proposed Product-Market-Level Measure

Conceptually, it makes sense to define product-market-level brand equity as theincremental profit that the brand earns over the profit it would earn if it were soldwithout the brand name. However, it is not as easy to quantify this definition sincebrands can have multiple impacts. First, they increase choice per se (through theirimpact on consideration sets as well as overall appeal). Second, they decrease sensi-tivity to price increases, which allows them to command a price premium. Third,they make other activities such as advertising more effective, which allows foreither more impact from the same dollars or a smaller budget to achieve a givenimpact. Brands also help secure distribution (which in turn increases sales, and,through purchase-event feedback, loyalty). More generally, the impact of brands ismulti-faceted and involves a complex series of relationships among the elements ofthe marketing mix. Therefore, one approach to assessing the value of the brand isto develop a structural model of all these relationships. However, this approach isdifficult, likely to suffer from specification error, and generally unappealing tomanagers.

Dubin (1998) takes another approach whereby he estimates demand functions forall the branded and unbranded products in the market, and, with the help of a setof simplifying assumptions, develops an expression for the incremental profit of abrand over what it would earn if it were unbranded. This expression is primarily afunction of the sales of the brand relative to the sales it would have were itunbranded, its market share, and its price elasticity. However, this approach,though economically elegant, also has its practical drawbacks. First, many assump-tions made for purposes of tractability may not hold up in practice. For example,the elimination of a branded product from the market will not affect the total sizeof the market; when a brand is eliminated, the former consumers of that brandspread their purchases in proportion to attractiveness (share) to other products,branded and unbranded. Further, the measure relies on the estimated price elastici-ty of demand for the brand. Demand functions are not only cumbersome to esti-mate when working with a large number of product-markets, they are also verysensitive to specification error and therefore may give biased estimates of price elas-ticity. Therefore we employ a simpler alternative to Dubin’s measure here.

The method we use is based on the implicit assumption that the outcomes in themarket involve optimal decisions by firms who select a price (and resulting sales)for their brands in order to maximize net revenue (and hence discounted cashflow and financial market value). Their decisions depend on the (different)demand curves faced by branded and unbranded goods (i.e., private label orgeneric products). The revenues received by a firm are a reflection of the valuecustomers place on the various alternatives. In essence, these revenues result froma reduced form of the complex relations among brand, marketing mix elements,


and customers discussed earlier. We would like to know how much extra revenueis generated by a brand relative to an unbranded equivalent product. Instead oftrying to estimate the hypothetical revenue that a branded product would earn ifit did not have the brand name, we use the revenue of the private label product asa benchmark. Hence, the difference in revenue (i.e., price x volume) between abranded good and the corresponding private label represents the value of the par-ticular brand.

This measure of brand equity has several advantages, as we will show. First, it is asimple measure so it can serve as a practical standard of performance. Second, it isreadily calculable from existing internal statistics or publicly available data (e.g.,annual reports, IRI and Nielsen data for packaged goods). Third, while subject tothe usual accounting vagaries like timing of booking of sales, it is for the most partobjective. It also does not require simultaneous estimation of complex relationshipsbetween variables or even demand functions where specification error is likely (e.g.,modeling effects of simultaneous relationships among advertising, distribution, andmarket share). Finally, it has credibility with financial and operating managers (i.e.,they understand and see the value of increased revenue).

Of course a number of complexities may exist. For example, private labels vary byproduct category in terms of their quality level (e.g., Sethuraman 1992; Hoch andBanerji 1993). Consequently, our measure of equity is based not on an absolutestandard but one that shifts from category to category. We believe that this is as itshould be. If unbranded products achieve higher quality in certain product cate-gories than in others, it is only reasonable that branded products in those cate-gories will find it more difficult to create equity.1 Of course, our measure wouldcapture and reflect inter-brand differences within a given category. Similarly, theattraction effect (Huber and Puto 1983) suggests a brand that is superior to a pri-vate label may not sell well (or at all) if another brand dominates it. Such a brandclearly does not have as much equity as the brand that dominates it, and thiswould be reflected in inter-brand differences in our revenue premium measure.Also, temporary actions like price wars or premiums can affect the revenue premi-um in a particular time period although they will not cause period-to-periodchanges if they are regularly scheduled events. Finally, there may be heterogeneityin the “up-marketness” of some private labels versus others within a product cate-gory, or in the equity of brands in some customer segments or regions versus oth-ers. In general, heterogeneity is not well captured by an aggregate-market-level rev-enue premium measure, but it is a useful and simple starting point for assessingaggregate brand equity. Therefore, the argument here is not that it is a perfect mea-sure; rather, we suggest that it is a simple one that is worth investigation.

In determining the revenue premium in a given period (e.g., year), it is useful toconsider four conditions depending on the relative price and sales of the brandedversus the private label product. Figure 1 depicts these four conditions. In eachcase, price is on the X-axis and unit sales are on the Y-axis. The symbol B standsfor the branded product while PL stands for the private label equivalent. The areadepicted by the “+” sign represents the revenue premium of the brand, while the


area depicted by the “-” sign shows the revenue premium of the private label, i.e.,the negative premium of the brand.

Figure 1. Gross Brand Equity Premium: Four Possibilities

Case A represents the desired (and a very common) state where the brand is bothpriced higher and sells more than the private label product. It is the case depictedby Dubin (1998, p. 86). Here, not only does the brand receive extra income versusthe private label for every unit it sells, it also receives revenue for the extra unitssold. Ignoring for now the extra cost of producing and selling these, this means(gross) brand equity is just the difference in revenues, i.e., the darker-shaded areadepicted with a “+” sign.

Case B is a bit more complex. Here the brand sells at a higher price but has fewersales than the private label. This may be because the brand is simply not strongenough to be able to command a price premium without giving up sales orbecause it operates in a market niche (e.g., as in the case of the luxury cars). In theformer case, it is fair to use the difference in revenue as a measure of the brand’sequity. This may be positive or negative depending upon the relative size of thebrand’s positive premium due to its higher price (depicted by “+” in the figure)and its negative premium due to lower sales (depicted by “-”). In the latter case, wemust define the market appropriately (e.g., luxury car market).

Case C is in some ways the most puzzling. Here the branded good enjoys greatersales than the private label but at a lower price. In this case, the brand has a positive

Case A: PB > PPL; SB > SPL Case B: PB > PPL; SB < SPL

Unit Sales Unit Sales

SB

SPL

+

–

SB

SPL

PPL

PB

Price PPL

PB

Price

Case C: PB < PPL; SB > SPL Case D: PB < PPL; SB < SPL

Unit Sales

S

B –

S

PL

P PLPB Price

+

Unit Sales

S

PL

–

S

B

P PLPB Price

+


premium due to higher sales (depicted by “+”) and a negative premium due to itslower price (depicted by “-”). Again, the total revenue premium may be positive ornegative depending on the relative size of these components. Thus, the difference inrevenue measure works here also.

Finally, Case D is the reverse of Case A where the brand sells fewer units at a lowerprice than the private label. Here the (negative) brand equity is again the differencein revenue.

There are two types of costs that complicate this calculation if one is interested in netequity (i.e., to the company) versus gross equity (i.e., from the customer’s perspec-tive, who is uninterested in cost). First, additional units typically require additionalvariable (direct) cost, so the variable cost per unit x additional volume can be used toadjust the gross difference in revenue. Figure 2 shows how the variable cost (VC)enters into the calculation of net equity for each of our four cases. As the figureshows, inclusion of variable costs will decrease equity in cases A and C, and increaseit in cases B and D. In all the analyses reported in this paper, we examine the behav-ior of a “gross” equity measure but it is fairly straightforward to account for thesevariable costs and compute a net equity measure. We repeated all of our analysiswith this net equity measure and found few substantive differences in results.2

Figure 2. Net Equity Premium: Four Possibilities

Case A: PB > PPL ; SB > SPL Case B: PB > PPL; S B < S PL

Unit Sales Unit Sales

SB

SPL

+

SB

SPL

PPL

PB

Price PPL

PB

Price

Case C: PB < PPL; S B > S PL Case D: PB < PPL; SB < SPL

Unit Sales

S

B

–

S

PL

P PLPB Price

+

Unit Sales

S

PL

S

B

P PLPB Price

+

VC

– +

VC

VC

+ –

VC

–

–


Second, brand equity is often maintained through investment in the brand (e.g.,advertising), which represents a fixed annual cost. There are two ways to capturethis. First, we can subtract this annual fixed cost from net revenue and then dis-count future revenues:

Total Equity = Σt

(RevenuePremiumt - AdditionalVariableCostt - Annual

FixedBrand Costt) (1 )t = (RevenuePremium - AdditionalVariableCost -

AnnualFixedBrandCost)( 1 + d ) where d = discount rate

Alternatively, we can assume equity decays in the absence of this annual expenditure:

Total Equity = Σt

(RevenuePremiumt - AdditionalVariableCostt)((1 )(r))t

= (RevenuePremium - AdditionalVariableCost)( 1 + d ) where r = the

portion of equity retained from period to period

For the purposes of this paper, we examine the annual equity, i.e., the revenue pre-mium in a given year rather than a discounted value of future revenue premiums.This avoids the need to predict future revenue premiums and select a discountrate. The current revenue premium represents a reasonable floor on the overalllong-term value of a brand (see also Dubin 1998, p. 78), and allows us to makecomparisons between different brands.

Finally, note that this revenue premium measure varies directly with the size of aproduct category. In order to remove this scale effect and make the measure moreeasily comparable across categories of different sizes, one can examine the revenuepremium as a percentage of private label revenue.

We use national grocery store scanner data for several categories of packaged goodsto calculate the proposed measure of brand equity and then attempt to validate itby examining its behavior over time as well as its relationship with marketing mixvariables and category characteristics.

1

1 + d

1 + d

1 + d - r


Empirical Measurement

Data

The mature packaged goods industry in the U.S. generally does not see majorchanges in marketing activity and strategy from year to year. In the early nineties,however, P&G’s well-publicized and broad-based value pricing move created amajor change in this otherwise staid marketplace. The company made significantincreases in advertising spending and drastic cuts in promotion in an effort tobuild customer loyalty and cut costs (Shapiro 1992). One would expect that such amajor and sustained policy change would also have a significant influence onbrand equity. Thus, P&G’s value pricing move provides a valuable opportunity tovalidate our proposed equity measure. We compile share, price, promotion, andadvertising data on 23 different product categories in which P&G is a player, forthe period in which value pricing was implemented, i.e., 1990 to 1996. The share,sales per thousand households, price, and promotion data are taken from IRI’sannual Market Fact Book, which covers sales in the grocery channel. These aresupplemented with data on media advertising from Leading National Advertisersannual publication. In addition, we use Narasimhan, Neslin, and Sen’s (1996)measure of category stockpileability, Hoch and Banerji’s (1993) category-level dataon retail margins and private label quality, and a classification of the 23 productcategories into hedonic versus utilitarian goods made by multiple judges. In eachcategory, we selected the P&G brand, two or three other major brands, a smallshare brand, and private label as the basis for analysis. More details on the data areavailable in Ailawadi, Lehmann, and Neslin (2001).

Descriptive Statistics and Trends

Table 1 lists the product categories we study, along with the average equity, adver-tising, and dealing in each category. It also provides a measure of perceived privatelabel quality in each category obtained from retail managers by Hoch and Banerji(1993). The table shows substantial cross-category variation in equity as well as theother variables. Health care and paper products tend to have relatively lower levelsof equity compared to personal care, cleaning, and food products. Later, weattempt to explain some of this cross-category variation.

The distribution of the brands in our sample over the four cases depicted earlier inFigure 1 is interesting to note. Forty-eight percent of the brands fall in Case A(i.e., they have higher price and higher unit sales than private label); 41 percent fallin Case B (i.e., they have a higher price but lower sales than private label); 9 per-cent fall in Case C (i.e., they have lower price but higher sales than private label);and only 3 percent fall in Case D (i.e., they have lower price and lower sales thanprivate label). As might be expected, the majority of small brands (defined, follow-ing Ailawadi, Lehmann, and Neslin [2001], as brands that had less than 5 percentof the total market share of the top three brands in the category in 1990) fall in


Case B, with none in Case A, while the majority of other brands (that we call“major brands”) fall in Case A, with none in Case D.

Table 1. Product Categories Studied

CategoryMean Equity

(% of PL)

Mean Equitya

($/1000 HH)

Mean Advertisingb

($ bill)

Mean % on Dealc

Pvt. Label Qualityd

Food Products

Brownie mix 355.94 303.88 .194 34.10 4.24

Frosting 552.51 486.47 .208 34.843 4.53

Potato chips 47.40 600.96 .920 65.30 4.72

Shortening 189.13 367.09 .644 36.74 5.00

Health Care Products

Cold/allergy/sinus liquid -34.91 -98.94 1.243 29.13 4.83

Cold/allergy/sinus tabs -50.83 -309.21 2.417 26.43 4.83

Cough syrup 137.75 160.68 1.650 32.70 4.75

Personal Care Products

Bar soap 3,152.99 1,025.56 1.628 28.82 4.00

Hair conditioner 746.34 146.71 .698 39.80 4.18

Liquid soap 994.97 1.088 22.02 4.00

Mouthwash 24.32 36.32 1.340 35.63 4.43

Shampoo 249.22 304.99 2.736 38.61 4.25

Toothbrushes 151.45 118.44 1.249 40.03 4.75

Toothpaste 850.93 638.96 2.111 34.57 4.17

Paper Products

Diapers -12.08 -361.84 2.111 43.87 4.17

Paper towels 41.43 572.76 .808 57.22 3.95

Tissue–facial 27.94 285.55 1.122 39.29 3.95

Tissue–toilet 91.14 1,270.89 .610 55.36 4.11

Cleaning Products

Dishwashing liquid 806.03 1,264.05 1.409 46.18 4.41

Dishwasher detergent 392.65 902.86 .875 30.768 4.16

Dry bleach 156.92 225.71 .606 8.873 5.00

Liquid laundry detergent 421.75 1,348.50 1.813 60.24 4.35

Powdered laundry detergent 651.98 2,259.46 2.050 43.20 4.35

a Dollars per 1,000 householdsb Media advertising spending from LNAc Data from IRI Market Fact Bookd Measured on 1 to 5 scale (1 = low, 5 = high) in a survey conducted by Hoch and Banerji (1993)

271.97


Descriptive statistics of our equity measure for the whole sample, as well as for var-ious sub-groups, are given in Table 2. We examine P&G brands as a separate sub-group because, as noted earlier, the company’s major policy change during thisperiod could have interesting implications for its equity. Note also that we reportdescriptive statistics for not only dollar equity (which is calculated per thousandhouseholds) but also equity as a percentage of private label revenue. For ease ofinterpretation and comparison across categories, we use the ratio measure in all ofour subsequent analyses.

Table 2. Descriptive Statistics for Equity Measure

As shown in Table 2, the mean equity is about 450 percent the revenue of the pri-vate label across all brands. As would be expected, it is higher for major brandsthan for small brands, and higher for P&G brands than for non-P&G brands. Ingeneral, there is tremendous variability across brands and categories in the equitymeasure, thus providing an opportunity for us to subsequently examine the associ-ation of equity with relevant brand and category characteristics.

According to the business press, the position of private labels has significantlyimproved during the past decade, at the expense of national brands. To see if ourequity measure bears this out, we tracked the direction of changes in the measurefrom 1990 to 1996 for the same groups of brands as in Table 2.3 Table 3 showsthat the trends in brand equity are indeed consistent with an improved position ofprivate label in general. On average, brands lost 65 percent of their equity duringthis time period. Both the mean and the median change are negative for all groupsexcept small brands, which increased their equity by about 17 percent on average.Interestingly, the mean and median changes for P&G are not very different fromother brands, though there is much less variability in P&G’s changes than in thechanges of other brands. In total, only 16 out of 101 brands in the sample

Group Mean Std. Deviation Minimum Maximum

Equity as a % of Private Label Revenue

Complete Sample 447% 1,047% -98% 10,632%

Major Brands 620% 1,168% -93% 10,632%

Small Brands -50% 61% -98% 174%

Non-P&G Brands 363% 985% -98% 10,632%

P&G Brands 756% 1,205% -85% 7,930%

Dollar Equity ($ per 1000 households)

Complete Sample 515 1,421 -2,507 10,431

Major Brands 886 1,422 -1,211 10,431

Small Brands -532 668 -2,368 605

Non-P&G Brands 282 1,157 -2,507 7,332

P&G Brands 1,378 1,900 -713 10,431


increased their equity over this period. P&G gained equity only in the potato chipscategory; its equity decreased in the remaining 22 categories.4

Table 3. Changes in Equity during the 1990-1996 Period

Table 4 lists the average percent change in equity for each product category. Itshows only two categories in which the equity of brands increased on average—hair conditioner and liquid laundry detergent. In the hair conditioner category,two companies accounted for this increase—Alberto-Culver and RedmondProducts—while in the liquid laundry detergent category, Dial was the only com-pany to increase its equity. In all the other categories, equity decreased on average.The worst-hit categories on average are cold/allergy/sinus medications, where theAH Robbins and Miles brands lost the most equity on a percentage basis and pota-to chips, where Anheuser-Busch brands lost the most.

In summary, the descriptive statistics provide some face validity for our measure.Its median values across various product categories look reasonable; small brandshave lower equity than major ones, as one would expect; and the overall trend isdownward during the nineties, consistent with the conventional wisdom that thepower of the brand was decreasing. Interestingly, our descriptive statistics also showthat P&G lost equity during the period when it instituted value pricing, althoughone of the company’s objectives in doing so was to strengthen customer loyalty andthe strength of their brand. While we do not claim a causal relationship betweenthe two phenomena, it is interesting to note that the rate of decline in equity forP&G brands was actually somewhat steeper than for non-P&G brands.

GroupPercent Change From 1990 to 1996

Mean Median Minimum Maximum

Change in Equity as a % of Private Label Revenue

Complete Sample -65% -47% -1,587% 918%

Major Brands -90% -59% -1,587% 403%

Small Brands 17% -2% -205% 918%

Non-P&G Brands -70% -47% -1,587% 918%

P&G Brands -47% -53% -131% 164%

Change in Dollar Equity ($ per 1,000 households)

Complete Sample -114% -29% -4,049%

Major Brands -131% -24% -4,049% 412%

Small Brands -57% -83% -543% 1,087%

Non-P&G Brands -135% -26% -4,049% 1,087%

P&G Brands -37% -34% -148% 152%

1,087%


Table 4. Equity Changes across Product Categories

CategoryPercent Change in Equity (% of Pvt. Label Revenue)

Mean Minimum Maximum

Food Products

Brownie mix -17% -38% -1%

Frosting -21% -39% -9%

Potato chips -169% -1,187% 170%

Shortening -11% -21% -1%


Cold/allergy/sinus liquid -387% -1,587% -10%

Cold/allergy/sinus tabs -174% -598% -2%

Cough syrup -88% -131% -44%


Bar soap -78% -81% -74%

Hair conditioner 82% -76% 404%

Liquid soap -71% -82% -44%

Mouthwash -94% -176% -30%

Shampoo -87% -205% 33%

Toothbrushes -17% -73% 77%

Toothpaste -77% -134% -43%

Paper Products

Diapers -46% -96% -1%

Paper towels -62% -99% -1%

Tissue–facial -24% -73% 14%

Tissue–toilet -43% -64% 1%

Cleaning Products

Dishwashing liquid -30% -47% 1%

Dishwasher detergent -55% -63% -42%

Dry bleach -53% -83% -36%

Liquid laundry detergent 142% -85% 918%

Powdered laundry detergent -55% -83% -26%


Table 4. Equity Changes across Product Categories (continued)

CategoryPercent Change in Equity ($ per 1,000 households)

Mean Minimum Maximum

Food Products

Brownie mix -16% -35% 4%

Frosting 10% -15% 26%

Potato chips -126% -947% 152%

Shortening -9% -35% 17%


Cold/allergy/sinus liquid -1,061% -4,049% -127%

Cold/allergy/sinus tabs -540% -1,693% -128%

Cough syrup -81% -148% -13%


Bar soap -15% -29% -.80%

Hair conditioner 88% -76% 412%

Liquid soap 51% -9% 192%

Mouthwash -221% -547% -33%

Shampoo -77% -282% 131%

Toothbrushes -13% -92% 55%

Toothpaste -107% -543% 56%

Paper Products

Diapers -101% -127% -67%

Paper towels -95% -247% -5%

Tissue–facial -39% -135% 4%

Tissue–toilet -40% -53% -30%

Cleaning Products

Dishwashing liquid -30% -47% 1%

Dishwasher detergent -26% -40% -5%

Dry bleach -59% -85% -45%

Liquid laundry detergent 183% -83% 1,087%

Powdered laundry detergent -51% -120% -4%


Validation of the MeasureTo be useful, the measure needs to have several properties. It needs to be reason-ably stable over time and yet vary with marketing mix variables in expected ways.It should also vary across product categories in a sensible way. Finally, since equityis supposed to insulate a brand from price competition, it should also be associatedwith price sensitivity. We validate our measure by examining its association withthese variables.

Hypothesized Association with Marketing Mix and Category Variables

Heavily advertised brands should enjoy greater awareness and product differentia-tion, and hence have higher equity, consistent with the market power view ofadvertising. Of course, if advertising is information, price competition wouldincrease and hence equity could decrease (Albion and Farris 1981). In recent years,researchers have suggested that advertising builds equity and presented someempirical evidence to that effect (e.g., Mela, Gupta, and Lehman 1997).Therefore, we expect a positive association of our measure with advertising.

As the promotional activity of a brand increases, customers will be more likely toattribute their choice to the promotional price cut rather than brand preference(Dodson, Tybout, and Sternthal 1978), thus reducing equity. Customers may alsofind it easier to buy from deal to deal (Neslin and Schneider Stone 1996), thuslowering the average price paid and therefore equity. Alternatively, managers maychoose to use deals when their brand’s equity is low and they are threatened by aprivate label. This would also produce a negative association between equity andpromotion. In fact, Lal’s (1990) model would suggest that promotion is a coordi-nated strategy national brands use when faced with a store brand and a large num-ber of brand switchers. Therefore, we expect a negative association of our measurewith promotion.

The longer the purchase cycle for a product category, the weaker will be the mem-ory of past choice. In addition, packaged goods with long purchase cycles are alsoused less frequently, contributing to lower recall. As a consequence, products withlong purchase cycles should be lower in equity, and we expect a negative associa-tion of our measure with length of purchase cycle.

In easily stockpiled categories, loyal users can stockpile their favorite nationalbrands, insulating them from private label competition and increasing nationalbrand market share. Prior research has also shown a positive relationship betweenloyalty and stockpiling behavior (Neslin, Henderson, and Quelch 1985) and thatstore brand buyers are less apt to stockpile (Ailawadi, Neslin, and Gedenk 2001).Since loyalty goes hand in hand with equity (Chaudhuri and Holbrook 2001), weexpect national brands in stockpileable categories to have higher levels of equity.Of course, it may also be true that stockpileable categories are promoted more, andhigher promotion lowers equity. Still, after controlling for amount of category pro-motion, we expect a positive association of our measure with stockpileability.


Hedonic (as opposed to utilitarian) products provide intangible rather than func-tional benefits, which are harder to compare. Therefore, hedonic products shouldhave higher levels of equity and we expect a positive association of our measurewith hedonic products.

Product categories in which the private label product is perceived to be of highquality should have lower levels of brand equity, since the revenue premiumenjoyed by the brands will be lower. Therefore, we expect a negative association ofour measure with private label quality.

Finally, highly concentrated product categories should exhibit higher levels ofbrand equity since there are only a handful of major players in such markets.

Observed Association with Marketing Mix and Category Variables

Table 5 provides the correlation of our equity measure with its own lagged value aswell as with the marketing mix and category variables discussed above. It shows astrongly positive correlation between current year and previous year equity of .85,suggesting that the measure is stable (reliable) and hence capable of capturinglong-term value. As we expected, it also shows a positive association of equity withadvertising and a negative one with dealing. In terms of category characteristics, wefind that, as expected, our measure is positively correlated with stockpileability andconcentration, and negatively correlated with private label quality. The correlationwith purchase cycle and hedonic goods is not significant.

Table 5. Correlations with Marketing Mix and Category Variables (Between 539 and 616Observations)

We further examine these relationships using regression analysis. Table 6 providesthe results of the following regression, which models the inertia or carry-over ofequity as well the association with marketing mix and category variables:

EquityLagged Equity

Adver-tising

DealsPurchase

CycleStock- Concen-

trationHedonicCategory

Private Label

Quality

Equity 1

Lagged Equity .85* 1

Advertising .31* .25* 1

Deals -.11* -.11* -.13* 1

Purchase Cycle .04 .02 .01 -.45* 1

Stockpileability .25* .22* .04 .09** .06 1

Concentration .17* .16* -.02 -.15* .24* .19* 1

Hedonic Category -.03 -.05 -.23* .09** -.16* -.36* -.21* 1

Private Label Quality -.26* -.22* .02 -.12* .39* -.61* -.34* .06 1

p p* < .01; ** < .05

pileability


Equityijt =α + β1Equityijt-1 + β2Advtgijt + β3Dealsijt + β4Pur.Cyclej + β5Stockpilej +

β6Concenj + β7Hedonicj + β8PLQualityj + ijt

Note that our intention in estimating this regression model is not to infer causality.We simply wish to validate our measure by examining whether its association withother variables is positive when it should theoretically be positive and negativewhen it should be negative.

Table 6. Regression of Equity on Marketing Mix and Category Variables (529 Observations)

The regression generally reinforces the simple correlations. First, equity decays overtime. The unstandardized coefficient of lagged equity in the above equation is.473. This carry-over or “retention” rate suggests that the total value of brand equi-ty over time, ignoring discounting and assuming advertising and promotion cease,would be almost twice its current value (1 divided by 1 minus .473 is 1.9). Putanother way, unless the brand continues to be supported by advertising etc., itscurrent equity will dwindle by almost 75 percent by the end of two years. Second,advertising has a significant positive association with equity, and promotion doesnot. Third, the coefficients of stockpileability, hedonic categories, and private labelquality are significant and of the expected sign. The coefficients of purchase cyclelength and concentration are not statistically significant.

Impact on Price Elasticity

It has been suggested that one of the major advantages of brand equity is that itisolates a company from price competition. Effectively, this means high equitybrands should have lower self-price elasticities than low equity counterparts. Thisproposition is supported by the findings of researchers like Blattberg andWisnewski (1989) and Sethuraman (1995) who find that high tier or large sharenational brands enjoy an elasticity advantage relative to low tier brands or private

Independent Variable Standardized Coefficient t-statistic

Lagged Equity .78* 32.30

Advertising .13* 5.41

Deals -.02 -.54

Average Purchase Cycle .05 1.34

Stockpileability .08** 1.91

Hedonic Category Dummy .10* 3.38

Concentration .01 .41

Private Label Quality -.07** -1.73

R2 .75

Adjusted R2 .74

F-stat (df1, df2) 188.62 (8,520)

p p* < .01; ** < .05

∈


labels. However, this view may be a bit simplistic. Sivakumar and Raj (1997) showthat high quality brands gain more than low quality brands with a price reduction,and they lose less when they increase price. Their findings would suggest that highequity brands may benefit from an asymmetric effect of increasing versus decreas-ing their price. In other words, their “price up” elasticities may be significantlysmaller (less negative) than their “price down” elasticities. Low equity brands areless likely to exhibit this asymmetric “up” versus “down” effect. Although our pri-mary reasoning is for the self-price elasticity, a similar argument may also be madefor the cross-price elasticity. A high equity brand may be hurt less when competi-tors cut price and benefit more when competitors increase price. Thus, a highequity brand may have a higher (more positive) “up” cross-elasticity and a lower“down” cross-elasticity.

We investigate this particular type of asymmetry in elasticities with a modified ver-sion of the market share response model used by Ailawadi, Lehmann, and Neslin(2001). Specifically, we estimate a first-differenced log-linear model on data pooledacross brands and categories, accounting for brand and category differences as didAilawadi, Lehmann, and Neslin (2001). However, we add an interaction betweenprice and a dummy variable that takes the value 1 if there was a price increasefrom the previous year and 0 if there was not. We estimate this modified modelseparately for high and low equity brands.5 Although there are a large number ofcoefficients in the regression model (accounting for main effects of the marketingmix variables as well as their interactions with various brand and category charac-teristics), we focus only on the coefficient of the “up/down” price interactions. Ifour proposition holds, we would expect high equity brands to have a significantlypositive coefficient for both the self-price up/down interaction and the cross-priceup/down interaction. On the other hand, we would not expect either interactionterm to be statistically significant for low equity brands. Table 7 reports the esti-mated coefficient of this interaction with the self- and cross-prices of low and highequity brands.

Table 7. Effect of Brand Equity on Price Elasticity

VariableCoeffi cient

(Std. Error)

t-statistic

(p-value)

Low Equity Brands

Own Price Increase Dummy x Own Price.02

(.41)

.05

(.96)

Competitor Price Increase Dummy x Competitor Price1.57

(1.15)

1.37

(.17)

High Equity Brands

Own Price Increase Dummy x Own Price1.25

(.31)

3.98

(.00)

Competitor Price Increase Dummy x Competitor Price-1.00

(.33)

-3.06

(.00)


Our expectation about the “up” versus “down” asymmetric effect is borne out forthe self-price elasticity. The interaction term with own-price is not statistically sig-nificant for low equity brands. In contrast, it is positive and highly statistically sig-nificant for high equity brands. In other words, we do find that the “price up” elas-ticity is significantly smaller in magnitude (less negative) than the “price down” forhigh equity brands. For low equity brands, there is no significant difference in “up”and “down” elasticity.

Interestingly, the pattern for the cross-price elasticity interaction is not as intuitive.According to our results, high equity brands have weaker “up” cross elasticitiesthan “down” elasticities. This may be, at least partly, because the competition is anamalgam of small and large equity brands. Our sample, pooled across multiple cat-egories, does not permit us to estimate separate cross-elasticities with respect toeach individual competitor.


Summary and DiscussionThis paper has proposed and examined a measure of brand equity based on abrand’s sales and price in the product-market. Specifically we argue that the addi-tional (net) revenue versus private label is the manifestation of a complex combina-tion of various psychological associations held by customers and efficiencies, com-petitive decisions, and interactions that result therefrom. Put differently, one inter-pretation is that this metric measures the impact of not having the brand on rev-enues in equilibrium (i.e., after the firm and both other brands and private labelsmake decisions). While not as rich in interpretative power as a large system ofequations incorporating all factors, the measure has the important advantage ofbeing simple to understand and calculate as well as having credibility in the orga-nization outside marketing (e.g., to CFOs and COOs). In fact its objectivity sug-gests it may have potential as a key metric for performance evaluation.

Table 8. Prepared Tea Volume and Price Data (IRI Market Fact Book)

Based on aggregate data on 23 categories over a seven-year period, the measureproved to be stable (carryover correlation of over .80), yet still related in expectedways to marketing activities (i.e., positively to advertising but not promotion) andindustry trends (in general it declined during the period when conventional wis-dom suggests that brands lost out to store brands). Further, its association with

YEAR BRAND SHARE PRICE/POUND POUNDS/HH

1992 Private label 4.0 .45

Snapple 22.6 .71

Arizona –

Lipton 24.9 .53

Nestea 21.9 .55


Snapple 25.10 .75

Arizona 7.00 .71

Lipton 34.30 .44

Nestea 8.30 .66

4.60


Snapple 29.16 .39

Arizona 6.14 .71

Lipton 36.52 .36

Nestea 17.45 .36

6.65

–


category characteristics (positive with stockpileability and hedonic goods, and neg-ative with category dealing), and with “up” versus “down” price elasticity is alsolargely as expected.

Table 9. Snapple Brand Equity: Prepared Tea

The simple measure is also diagnostic. Consider Snapple, which was purchased for$1.7 billion by Quaker and then sold to Triarc for $300 million about two yearslater, an 82 percent decrease. Table 8 shows market share, price, and market size(per household) data for prepared tea from IRI’s Market Fact Book (which is, ofcourse, only part of Snapple’s product line), for 1992 (pre-sale), 1994 (just aftersale to Quaker), and 1996 (just before sale to Triarc). A simple inspection of Table8 shows the problem; while sales continued to grow (both market size and share),price decreased dramatically as both Lipton and Nestea cut price and Arizonaemerged as the funky, upscale brand. In Table 9, we calculate our annual dollarequity measure for Snapple, both gross and net of variable costs, for 1994 and1996. Gross annual equity per household is simply Snapple’s revenue (price x sharex market size) minus private label’s revenue. Net annual equity is calculated bysubtracting the variable cost of the additional units from the gross equity measure.Variable cost, in turn, is estimated as 80 percent of the price of private label(assuming that private label margin is 20 percent, which is close to the mean retailmargin of the categories in our data). Finally, the net annual equity per householdis multiplied by 100 million to get the total net annual equity for the U.S. market.As Table 9 shows, our measure of net annual dollar equity for Snapple decreased

Annual Gross Revenue Equity/HH

1994 [(.251)(.75) – (.099)(.24)] (4.60) = (.165) (4.60) = $.76

1996 [(.2916)(.39) – (.0505)(.25)] (6.65) = (.101) (6.65) = $.67

Annual Equity Net of Extra Variable Cost/HH(Assume 20% private label margin)

1994 .76 – [(.251 – .099)(.80)(.24)] (4.60) = .76 – .13 = $.63

1996 .67 – [(.2916 – .0505)(.80)(.25)] (6.65) = .67 – .32 = $.35

Total Annual Equity Net of Extra Variable Cost(Based on 100 million households)

1994 ($.63)(100 mill) = $63 million

1996 ($.35)(100 mill) = $35 million


by about 44 percent from 1994 to 1996, suggesting the huge drop in financialmarket value was not justified by the product-market situation. This is supportedby the comeback Snapple has achieved since then, leading up to its sale for approx-imately $1 billion to Cadbury-Schweppes in 2000. This is a 41 percent decreasefrom the original $1.7 billion value—much more in line with the 44 percentdecrease in our measure.6 We note that the diagnostic ability of our measure is notsensitive to the private label margin used in the calculation of net equity. Forinstance, if we used a margin of 30 percent, which is at the high end of the rangetypically found in industry, the values of 1994 and 1996 annual net equity perhousehold would be $.64 and $.38, implying a decrease of about 39 percent.

Of course, a number of specific concerns exist. For example, in addition to incom-plete specification of determinants, the relations among equity and marketing deci-sions are likely to be bi-directional. As a result, as acknowledged earlier, causalinterpretation of the results, though tempting and seemingly sensible, is not justi-fied solely on the basis of these results. In addition, the equity measure is affectedby the quality of private label, which varies by category. While this may seem alimitation, in fact it represents reality: the additional value (revenue) due to abrand depends on the strength of its competition with unbranded products in thatcategory. It is also the case that when a brand is new, its investments in advertising,etc., require time before the brand’s position is established, so the measure worksbetter for mature brands in relatively stable categories (which a large number ofconsumer packaged goods are). Nonetheless, the results are sufficiently encourag-ing to suggest that the measure is worth considerably more investigation.


Notes1. The same argument holds for differences across countries. For instance, the

quality of private label products in the U.K. and perhaps Canada is higherthan in the U.S. National brand products in these countries would find itmore difficult to create equity for themselves.

2. In calculating this net equity measure, we assume that the variable cost of pro-duction is the same for the private label and the brand. We obtain the variablecost for each product category by applying the retail category margin data fromHoch and Banerji (1993) to the price of the private label in that category.Retail margins for the categories in our dataset vary from approximately 13percent to 27 percent.

3. One company in the toothpaste category, Gillette, lost 24,123 percent of its1990 equity during this period. We deleted this severe outlier from the samplebefore computing the descriptive statistics in the table. Note, of course, thatequity can decrease by more than 100 percent since it is possible for a brand tohave negative equity.

4. If private label revenue is growing at a very fast rate, our equity measure as apercentage of private label revenue may decrease even if the total dollar equityof a brand is increasing. We also examined trends in total dollar equity andfound that the overall trend was very similar. The mean percent change in dol-lar equity across our sample was -114 percent and the median change was -29percent. There were only two categories, frosting and liquid soap, where dollarequity increased both on average for the category (9.5 percent and 51 percentrespectively) and for P&G (18 percent and 8 percent respectively), althoughour equity measure as a percentage of private label revenue decreased.

5. High and low equity brands are defined using a median split of equity in thebase year of 1990. The results are not sensitive to the year used for defining themedian split.

6. Note, of course, that we have calculated annual equity, not the net presentvalue of the future stream of equity. Therefore, the magnitude of our measureis not comparable with the magnitude of the financial market value. However,we can and do compare the percentage change in our measure versus the finan-cial market value over time.


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Further ReadingOther MSI working papers on the topic of brand equity include:

No. 01-113 Consumption Symbols as Carriers of Culture: A Study ofJapanese, Spanish, and North American Brand PersonalityDimensionsby Jennifer Lynn Aaker, Verónica Benet-Martínez, and JordiGarolera

No. 01-107 Building Customer-Based Brand Equity: A Blueprint forCreating Strong Brandsby Kevin Lane Keller

No. 01-100 Building Corporate Brands: An Exploratory Studyby Gabriel J. Biehal and Daniel A. Sheinin

No. 00-114 Global Brandingconference summary by Pedro Sousa

No. 00-111 Towards a System for Monitoring Brand Health from StoreScanner Databy C. B. Bhattacharya and Leonard M. Lodish

No. 00-110 What Makes Consumers Pay More for National Brands Thanfor Store Brands: Image or Quality?by Raj Sethuraman

No. 99-116 Towards Understanding the Value of a Loyal Customer: AnInformation-processing Perspectiveby Rohini Ahluwalia, H. Rao Unnava, and Robert E. Burnkrant

No. 98-128 Brands Constructs: The Complementarity of ConsumerAssociative Networks and Multidimensional Scalingby Geraldine R. Henderson, Dawn Iacobucci, and Bobby J. Calder

No. 97-128 The Ownership Effect in Consumer Responses to Brand LineStretchesby Amna Kirmani, Sanjay Sood, and Sheri Bridges

No. 97-126 Why Do Consumers Pay More for National Brands than forStore Brands?by Raj Sethuraman and Catherine Cole

No. 97-123 The Effects of Brand Name Suggestiveness on AdvertisingRecallby Kevin Lane Keller, Susan E. Heckler, and Michael J. Houston

No. 97-122 Brands, Brand Managers, and the Management of Brands:Where to Next?by Pierre Berthon, James M. Hulbert, and Leyland F. Pitt

No. 97-115 Asymmetric Quality Tier Competition: An AlternativeExplanationby K. Sivakumar

No. 97-114 Why Store Brand Penetration Varies by Retailerby Sanjay K. Dhar and Stephen J. Hoch

No. 97-106 Managing the Corporate Brand: The Effects of CorporateMarketing on Consumer Evaluations of Brand Extensionsby Kevin Lane Keller and David A. Aaker

No. 97-100 Brand Alliances as Information About Unobservable ProductQualityby Akshay R. Rao, Lu Qu, and Robert W. Ruekert

No. 96-127 The Long-term Impact of Promotion and Advertising onConsumer Brand Choiceby Carl F. Mela, Sunil Gupta, and Donald R. Lehmann

No. 96-124 Designing Recognizable Logosby Pamela W. Henderson and Joseph A. Cote

No. 96-123 Designing Positively Evaluated Logosby Pamela W. Henderson and Joseph A. Cote

No. 96-114 Erosion and Variability in Brand Loyaltyby Marnik G. Dekimpe, Martin Mellens, Jan-Benedict E. M.Steenkamp, and Piet Vanden Abeele

No. 96-101 Pioneer Brand Advantage in Japan and the United Statesby Frank Alpert, Michael Kamins, John Graham, Tomoaki Sakano,and Naoto Onzo

No. 95-111 Brand Equity and the Marketing Mix: Creating Customer Valueconference summary by Sanjay Sood

No. 95-109 To Standardize or Not to Standardize: Marketing MixEffectiveness in Europeby Hubert Gatignon and Piet Vanden Abeele

No. 95-105 National Brand and Store Brand Competition: Who HurtsWhom?by Raj Sethuraman

For additional MSI working papers on the topic of brand equity, and to orderpublications, visit the Publications section of www.msi.org or [email protected]

MARKETING SCIENCE INSTITUTE1000 Massachusetts AvenueCambridge, MA 02138 USA

Phone: 617.491.2060www.msi.org



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