A Product-Market-Based Measure of Brand Equity. Kusum L. Ailawadi, Donald R. Lehmann, and Scott A. Neslin

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1 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 A Product-Market-Based Measure of Brand Equity Kusum L. Ailawadi, Donald R. Lehmann, and Scott A. Neslin WORKING PAPER REPORT NO W O R K I N G P A P E R S E R I E S

2 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 A Product-Market-Based Measure of Brand Equity Kusum L. Ailawadi, Donald R. Lehmann, and Scott A. Neslin WORKING PAPER REPORT NO W O R K I N G P A P E R S E R I E S

3 MSI was established in 1961 as a not-for-profit institute with the goal of bringing together business leaders and academics to create knowledge that will improve business performance. The primary mission was to provide intellectual leadership in marketing and its allied fields. Over the years, MSI s global network of scholars from leading graduate schools of management and thought leaders from sponsoring corporations has expanded to encompass multiple business functions and disciplines. Issues of key importance to business performance are identified by the Board of Trustees, which represents MSI corporations and the academic community. MSI supports studies by academics on these issues and disseminates the results through conferences and workshops, as well as through its publications series. This report, prepared with the support of MSI, is being sent to you for your information and review. It is not to be reproduced or published, in any form or by any means, electronic or mechanical, without written permission from the Institute and the author. The views expressed in this report are not necessarily those of the Marketing Science Institute. Copyright 2002 Kusum L. Ailawadi, Donald R. Lehmann, and Scott A. Neslin

4 M ARKETING S CIENCE I NSTITUTE Report Summary # A Product-Market-Based Measure of Brand Equity Kusum L. Ailawadi, Donald R. Lehmann, and Scott A. Neslin In spite of all the attention brand equity has received in the past decade, relatively little 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 quantifiable measure of brand equity and validate it by examining its behavior over time and across product categories, and in response to marketing activities such as advertising and promotion. They conceptualize product-market-level brand equity as the incremental revenue that the brand earns over the revenue it would earn if it were sold without the brand 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 a seven-year period. The measure is found to be stable, yet still related in expected ways to marketing activities (that is, positively associated with advertising but not with promotion) and industry trends (in general it declined during the period when conventional wisdom suggests that national brands lost out to store brands). Further, the brand equity measure is positively associated with stockpileability and hedonic 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 managers. It is a simple measure that can serve as a practical standard of performance and it is readily calculable from existing internal statistics or publicly available data. Importantly, it should also have credibility with financial and operating managers who understand and see the value of increased revenue. Kusum L. Ailawadi is Associate Professor of Business Administration, Amos Tuck School of Business Administration, Dartmouth College. Donald R. Lehmann is George E. Warren Professor of Business, Graduate School of Business, Columbia University and Executive Director , Marketing Science Institute. Scott A. Neslin is Albert Wesley Frey Professor of Marketing, Amos Tuck School of Business Administration, Dartmouth College Massachusetts Avenue Cambridge, MA USA

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6 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 Period...16 Table 4. Equity Changes across Product Categories 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

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8 Introduction The concept of brand equity has been widely discussed over the past decade (Aaker and Keller 1990; Aaker 1991), with much of the work stemming from a Marketing Science Institute conference on the topic (Leuthesser 1988). During the same time period, companies have paid increasing attention to brands, often, for example, creating the position of brand equity manager. This emphasis was especially evident during 1999 as Internet-based companies spent massively, if not effectively, to acquire customers and establish brand names. Yet, in spite of all the attention to brand equity, little is known about how to measure it or how it changes over time. The purpose of this paper is to propose a specific measure and examine its behavior over time, across product categories, and in response to marketing activities such as advertising and promotion. Marketing Science Institute 3

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10 Conceptual Background Research in the brand equity area has focused largely on brand extensions, particularly on how well equity in one product extends to other categories (e.g., Aaker and 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 original brand (Roedder John and Loken 1993). While it is widely acknowledged that brand equity is related to both technical capability and image (Batra, Lehmann, and Singh 1992), remarkably few papers have addressed brand equity measurement per se, in spite of the fact that both brand equity and metrics have been priority topics of the Marketing Science Institute for the last 10 years. Part of the lack of emphasis on measurement can be traced to confusion and disagreement over what is to be measured. At an MSI conference in 1999 on the topic, clear disagreement arose over whether it was appropriate to try to capture brand equity as a single 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 (Keller and Lehmann 2002). First, there are measures related to customer mindset, that is, the attitudes, associations, and attachment customers have toward the brand. This category has been the focus of both academic research (e.g., Ambler and Barwise 1998) and the measures provided by suppliers such as Research International s Equity Engine SM, Young & Rubicam s BrandAsset Valuator, and Millward Brown s BRANDZ TM. These measures have useful diagnostic power and richness but 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 paid for branded versus private label (or generic) merchandise, or the related concepts of brand clout and vulnerability as measured by the brand s own and cross-price elasticities (Kamakura and Russell 1993). Other measures of this type include the constant term in sales response models (Srinivasan 1979) or the residual in hedonic regression, i.e., market inefficiency (Hjorth-Andersen 1984), but they do not capture the interaction of equity with marketing mix activities such as advertising and price. Recently, Dubin (1998) has proposed a product-market-level measure that attempts to quantify the difference between the profit earned by the brand and the profit it would earn if it were sold without the brand name. While potentially less diagnostic, product-market-level measures have the advantage of being fairly unambiguous as well as credible/important to executives outside the marketing 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, these assess the value of the brand as a financial asset. Purchase price when a brand is sold or acquired (Mahajan, Rao, and Srivastava 1994) and discounted cash flow valuation of licensing fees and royalties are measures of this type. Interbrand s measure is a hybrid of product-market and financial-market measures, which basically starts with the revenue premium the brand enjoys and adjusts it for growth potential etc. Marketing Science Institute 5

11 6 Marketing Science Institute Simon and Sullivan (1993) develop a measure that is the residual once other sources of firm value are accounted for. While these measures obviously have relevance to CFOs and CEOs, they are subject to both considerable variability (e.g., Snapple s sale price went from $1.7 billion to $300 million in just over two years, and then back to about $1 billion a few years later) and subjective judgment (i.e., the multiples applied by Interbrand). They also have less immediate relevance to marketing since many things other than marketing activities impact them. Thus, we focus on a product-market measure, both because such measures have received relatively little attention, and because this metric is relevant to product managers, chief marketing officers, and CEOs alike.

12 The Proposed Product-Market- Level Measure Conceptually, it makes sense to define product-market-level brand equity as the incremental profit that the brand earns over the profit it would earn if it were sold without the brand name. However, it is not as easy to quantify this definition since brands can have multiple impacts. First, they increase choice per se (through their impact on consideration sets as well as overall appeal). Second, they decrease sensitivity to price increases, which allows them to command a price premium. Third, they make other activities such as advertising more effective, which allows for either more impact from the same dollars or a smaller budget to achieve a given impact. Brands also help secure distribution (which in turn increases sales, and, through purchase-event feedback, loyalty). More generally, the impact of brands is multi-faceted and involves a complex series of relationships among the elements of the marketing mix. Therefore, one approach to assessing the value of the brand is to develop a structural model of all these relationships. However, this approach is difficult, likely to suffer from specification error, and generally unappealing to managers. Dubin (1998) takes another approach whereby he estimates demand functions for all the branded and unbranded products in the market, and, with the help of a set of simplifying assumptions, develops an expression for the incremental profit of a brand over what it would earn if it were unbranded. This expression is primarily a function of the sales of the brand relative to the sales it would have were it unbranded, its market share, and its price elasticity. However, this approach, though economically elegant, also has its practical drawbacks. First, many assumptions 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 size of the market; when a brand is eliminated, the former consumers of that brand spread their purchases in proportion to attractiveness (share) to other products, branded and unbranded. Further, the measure relies on the estimated price elasticity of demand for the brand. Demand functions are not only cumbersome to estimate when working with a large number of product-markets, they are also very sensitive to specification error and therefore may give biased estimates of price elasticity. 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 the market involve optimal decisions by firms who select a price (and resulting sales) for their brands in order to maximize net revenue (and hence discounted cash flow and financial market value). Their decisions depend on the (different) demand curves faced by branded and unbranded goods (i.e., private label or generic products). The revenues received by a firm are a reflection of the value customers place on the various alternatives. In essence, these revenues result from a reduced form of the complex relations among brand, marketing mix elements, Marketing Science Institute 7

13 and customers discussed earlier. We would like to know how much extra revenue is generated by a brand relative to an unbranded equivalent product. Instead of trying to estimate the hypothetical revenue that a branded product would earn if it did not have the brand name, we use the revenue of the private label product as a benchmark. Hence, the difference in revenue (i.e., price x volume) between a branded good and the corresponding private label represents the value of the particular brand. This measure of brand equity has several advantages, as we will show. First, it is a simple measure so it can serve as a practical standard of performance. Second, it is readily calculable from existing internal statistics or publicly available data (e.g., annual reports, IRI and Nielsen data for packaged goods). Third, while subject to the usual accounting vagaries like timing of booking of sales, it is for the most part objective. It also does not require simultaneous estimation of complex relationships between variables or even demand functions where specification error is likely (e.g., modeling effects of simultaneous relationships among advertising, distribution, and market 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 by product category in terms of their quality level (e.g., Sethuraman 1992; Hoch and Banerji 1993). Consequently, our measure of equity is based not on an absolute standard but one that shifts from category to category. We believe that this is as it should be. If unbranded products achieve higher quality in certain product categories than in others, it is only reasonable that branded products in those categories will find it more difficult to create equity. 1 Of course, our measure would capture and reflect inter-brand differences within a given category. Similarly, the attraction effect (Huber and Puto 1983) suggests a brand that is superior to a private label may not sell well (or at all) if another brand dominates it. Such a brand clearly does not have as much equity as the brand that dominates it, and this would be reflected in inter-brand differences in our revenue premium measure. Also, temporary actions like price wars or premiums can affect the revenue premium in a particular time period although they will not cause period-to-period changes if they are regularly scheduled events. Finally, there may be heterogeneity in the up-marketness of some private labels versus others within a product category, or in the equity of brands in some customer segments or regions versus others. In general, heterogeneity is not well captured by an aggregate-market-level revenue premium measure, but it is a useful and simple starting point for assessing aggregate brand equity. Therefore, the argument here is not that it is a perfect measure; 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 to consider four conditions depending on the relative price and sales of the branded versus the private label product. Figure 1 depicts these four conditions. In each case, price is on the X-axis and unit sales are on the Y-axis. The symbol B stands for the branded product while PL stands for the private label equivalent. The area depicted by the + sign represents the revenue premium of the brand, while the 8 Marketing Science Institute

14 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: P B > P PL ; S B > S PL Case B: P B > P PL ; S B < S PL Unit Sales Unit Sales S B S PL + S PL S B + P PL P B Price P PL P B Price Case C: P B < P PL ; S B > S PL Case D: P B < P PL ; S B < S PL Unit Sales S S B PL + Unit Sales S PL S B P B PPL Price P B PPL Price Case A represents the desired (and a very common) state where the brand is both priced higher and sells more than the private label product. It is the case depicted by Dubin (1998, p. 86). Here, not only does the brand receive extra income versus the private label for every unit it sells, it also receives revenue for the extra units sold. 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 area depicted with a + sign. Case B is a bit more complex. Here the brand sells at a higher price but has fewer sales than the private label. This may be because the brand is simply not strong enough to be able to command a price premium without giving up sales or because it operates in a market niche (e.g., as in the case of the luxury cars). In the former case, it is fair to use the difference in revenue as a measure of the brand s equity. This may be positive or negative depending upon the relative size of the brand 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, we must define the market appropriately (e.g., luxury car market). Case C is in some ways the most puzzling. Here the branded good enjoys greater sales than the private label but at a lower price. In this case, the brand has a positive Marketing Science Institute 9

15 premium due to higher sales (depicted by + ) and a negative premium due to its lower price (depicted by - ). Again, the total revenue premium may be positive or negative depending on the relative size of these components. Thus, the difference in revenue measure works here also. Finally, Case D is the reverse of Case A where the brand sells fewer units at a lower price than the private label. Here the (negative) brand equity is again the difference in revenue. There are two types of costs that complicate this calculation if one is interested in net equity (i.e., to the company) versus gross equity (i.e., from the customer s perspective, who is uninterested in cost). First, additional units typically require additional variable (direct) cost, so the variable cost per unit x additional volume can be used to adjust 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 figure shows, inclusion of variable costs will decrease equity in cases A and C, and increase it in cases B and D. In all the analyses reported in this paper, we examine the behavior of a gross equity measure but it is fairly straightforward to account for these variable costs and compute a net equity measure. We repeated all of our analysis with this net equity measure and found few substantive differences in results. 2 Figure 2. Net Equity Premium: Four Possibilities Case A: P B > P PL ; S B > S PL Case B: P B > P PL ; S B < S PL Unit Sales Unit Sales S B S PL + + S PL S B + VC P PL P B Price VC P PL P B Price Case C: P B < P PL ; S B > S PL Case D: P B < P PL ; S B < S PL Unit Sales Unit Sales S B S PL + S S PL B + VC P B PPL Price VC P B PPL Price 10 Marketing Science Institute

16 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 capture this. First, we can subtract this annual fixed cost from net revenue and then discount future revenues: Total Equity = Σ t (RevenuePremium t - AdditionalVariableCost t - Annual FixedBrand Cost t ) ( 1 ) t = (RevenuePremium - AdditionalVariableCost d AnnualFixedBrandCost)( 1 + d ) where d = discount rate 1 Alternatively, we can assume equity decays in the absence of this annual expenditure: Total Equity = Σ (RevenuePremium t - AdditionalVariableCost t )(( 1 )(r)) t t = (RevenuePremium - AdditionalVariableCost)( 1 + d 1 + d ) where r = the 1 + d - r portion of equity retained from period to period For the purposes of this paper, we examine the annual equity, i.e., the revenue premium 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 discount rate. The current revenue premium represents a reasonable floor on the overall long-term value of a brand (see also Dubin 1998, p. 78), and allows us to make comparisons between different brands. Finally, note that this revenue premium measure varies directly with the size of a product category. In order to remove this scale effect and make the measure more easily comparable across categories of different sizes, one can examine the revenue premium as a percentage of private label revenue. We use national grocery store scanner data for several categories of packaged goods to calculate the proposed measure of brand equity and then attempt to validate it by examining its behavior over time as well as its relationship with marketing mix variables and category characteristics. Marketing Science Institute 11

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18 Empirical Measurement Data The mature packaged goods industry in the U.S. generally does not see major changes 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 a major change in this otherwise staid marketplace. The company made significant increases in advertising spending and drastic cuts in promotion in an effort to build customer loyalty and cut costs (Shapiro 1992). One would expect that such a major and sustained policy change would also have a significant influence on brand equity. Thus, P&G s value pricing move provides a valuable opportunity to validate our proposed equity measure. We compile share, price, promotion, and advertising data on 23 different product categories in which P&G is a player, for the period in which value pricing was implemented, i.e., 1990 to The share, sales per thousand households, price, and promotion data are taken from IRI s annual Market Fact Book, which covers sales in the grocery channel. These are supplemented with data on media advertising from Leading National Advertisers annual publication. In addition, we use Narasimhan, Neslin, and Sen s (1996) measure of category stockpileability, Hoch and Banerji s (1993) category-level data on retail margins and private label quality, and a classification of the 23 product categories into hedonic versus utilitarian goods made by multiple judges. In each category, we selected the P&G brand, two or three other major brands, a small share brand, and private label as the basis for analysis. More details on the data are available in Ailawadi, Lehmann, and Neslin (2001). Descriptive Statistics and Trends Table 1 lists the product categories we study, along with the average equity, advertising, and dealing in each category. It also provides a measure of perceived private label 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 the other variables. Health care and paper products tend to have relatively lower levels of equity compared to personal care, cleaning, and food products. Later, we attempt to explain some of this cross-category variation. The distribution of the brands in our sample over the four cases depicted earlier in Figure 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 fall in Case B (i.e., they have a higher price but lower sales than private label); 9 percent 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 than private label). As might be expected, the majority of small brands (defined, following Ailawadi, Lehmann, and Neslin [2001], as brands that had less than 5 percent of the total market share of the top three brands in the category in 1990) fall in Marketing Science Institute 13

19 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 Category Mean Equity (% of PL) Mean Equity a ($/1000 HH) Mean Advertising b ($ bill) Mean % on Deal c Pvt. Label Quality d Food Products Brownie mix Frosting Potato chips Shortening Health Care Products Cold/allergy/sinus liquid Cold/allergy/sinus tabs Cough syrup Personal Care Products Bar soap 3, , Hair conditioner Liquid soap Mouthwash Shampoo Toothbrushes Toothpaste Paper Products Diapers Paper towels Tissue facial Tissue toilet , Cleaning Products Dishwashing liquid , Dishwasher detergent Dry bleach Liquid laundry detergent , Powdered laundry detergent , a Dollars per 1,000 households b Media advertising spending from LNA c Data from IRI Market Fact Book d Measured on 1 to 5 scale (1 = low, 5 = high) in a survey conducted by Hoch and Banerji (1993) 14 Marketing Science Institute

20 Descriptive statistics of our equity measure for the whole sample, as well as for various sub-groups, are given in Table 2. We examine P&G brands as a separate subgroup because, as noted earlier, the company s major policy change during this period could have interesting implications for its equity. Note also that we report descriptive statistics for not only dollar equity (which is calculated per thousand households) but also equity as a percentage of private label revenue. For ease of interpretation and comparison across categories, we use the ratio measure in all of our subsequent analyses. Table 2. Descriptive Statistics for Equity Measure 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 , Non-P&G Brands 282 1,157-2,507 7,332 P&G Brands 1,378 1, ,431 As shown in Table 2, the mean equity is about 450 percent the revenue of the private label across all brands. As would be expected, it is higher for major brands than for small brands, and higher for P&G brands than for non-p&g brands. In general, there is tremendous variability across brands and categories in the equity measure, thus providing an opportunity for us to subsequently examine the association of equity with relevant brand and category characteristics. According to the business press, the position of private labels has significantly improved during the past decade, at the expense of national brands. To see if our equity measure bears this out, we tracked the direction of changes in the measure from 1990 to 1996 for the same groups of brands as in Table 2. 3 Table 3 shows that the trends in brand equity are indeed consistent with an improved position of private label in general. On average, brands lost 65 percent of their equity during this time period. Both the mean and the median change are negative for all groups except 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 from other brands, though there is much less variability in P&G s changes than in the changes of other brands. In total, only 16 out of 101 brands in the sample Marketing Science Institute 15

21 increased their equity over this period. P&G gained equity only in the potato chips category; its equity decreased in the remaining 22 categories. 4 Table 3. Changes in Equity during the Period Group Percent 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% 1,087% 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% Table 4 lists the average percent change in equity for each product category. It shows 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 Redmond Products while in the liquid laundry detergent category, Dial was the only company 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 the AH Robbins and Miles brands lost the most equity on a percentage basis and potato 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 brands have lower equity than major ones, as one would expect; and the overall trend is downward during the nineties, consistent with the conventional wisdom that the power of the brand was decreasing. Interestingly, our descriptive statistics also show that P&G lost equity during the period when it instituted value pricing, although one of the company s objectives in doing so was to strengthen customer loyalty and the strength of their brand. While we do not claim a causal relationship between the two phenomena, it is interesting to note that the rate of decline in equity for P&G brands was actually somewhat steeper than for non-p&g brands. 16 Marketing Science Institute

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