When Do Private Labels Succeed?
In 1989, private labels or store brands accounted for 65 percent of sales of frozen green and wax beans and for 25 percent of sales of liquid bleach but for only 1.1 percent of sales of personal deodorants. As shown in Table 1, private label market share (in terms of both dollar sales and units sold) varies significantly across supermarket merchandise groups. What factors account for this variation? Private labels traditionally have been merchandised on the basis of price. The conventional wisdom has been that store brands should offer acceptable quality relative to national brands, but they should emphasize price. Recently, however, some retailers have been emphasizing quality over price; they have received a great deal of attention in the trade press and caused alarm among national brand manufacturers. For example, A&P is aggressively introducing a high-end line of private label products under the Master Choice label, reportedly under the influence of its German parent, Tengelmann.1 In this paper, we propose and test a framework to explain variation across categories in private label dollar share. We try to isolate the determinants of success and examine the roles of relative price and quality. Such understanding appears particularly timely in light of recent highly publicized price rollbacks by national brands such as Marlboro and Pampers. These moves are apparently responses to the threat manufacturers perceive from lower price alternatives, including private labels. This research attempts to understand the nature of that threat.
Private labels represent a sizable fraction of general merchandise retailing.2 Our focus is on store brands in the food retailing industry, where they accounted for 13 percent of U.S. supermarket sales in the year ending 30 June 1991.3 In that period, sales in all U.S. grocery stores amounted to $368.5 billion, implying private label sales of $48 billion. Private labels have a greater share of unit sales because they are priced 21 percent below the national brands on average. When we refer to “share” in this paper, we mean dollar share unless otherwise noted.
Private labels can be exclusive retailer programs (such as the Dominick’s brand at Dominick’s Finer Foods or A&P’s Ann Page) or they can be developed by a third party (such as Topco or Loblaw). The category also includes generic products with black-and-white labels. For retailers and manufacturers, the level of private label share in a category has substantial strategic and operating implications. Private labels can confer a significant measure of exclusivity to the retailer that runs them. In many categories, private labels are the dominant “brand,” such as brick cheese. Viewed as a single brand, private labels are the number-one seller in seventy-seven Selling Areas Marketing, Inc. (SAMI) categories, out of more than 250, and one of the top three sellers in 41 percent of SAMI categories.4 Industry sources suggest that retailer gross margins on private labels are 20 percent to 30 percent higher than on national brands. In order to earn these higher margins, however, retailers must devote resources to procurement, packaging, branding, and promotion, and they must give precious shelf space to private labels. For manufacturers of national brands, private labels constitute an important source of competition, and manufacturers must have a strategy for dealing with them. Retailers, for instance, have the advantage of taking a free ride on manufacturers’ product development efforts.5 In this period of contentiousness between the two parties, it is important to be able to identify the factors that lead to private label success.6
History of Private Labels
Private labels began in the grocery chains of the turn of the century, pioneered by retailers such as A&P, then the Great Atlantic and Pacific Tea Company. Grocery chains, such as Safeway and Kroger, and wholesale and retail cooperatives, such as IGA and Certified Grocers, were all prominent in the development and use of private labels, and they typically had substantial manufacturing interests in these programs. Manufacturer brands in the food business began to develop after the Civil War. They grew with each successive innovation in advertising media, but especially with the development of supermarkets, such as King Kullen in Jamaica, New York, in the 1920s and 1930s. Early supermarkets were the discounters of their era. They employed self-service and nontraditional space such as unused warehouses to cut costs while relying on manufacturer brands to control marketing overhead. The grocery chains followed supermarkets into the use of large self-service space, gradually ceding to the promotional power of manufacturer brands in their merchandising decisions. The diffusion of commercial television in the post-war period dramatically changed the economics of mass communication and cemented the role of manufacturer brands in food retailing.7
Private labels have accounted for an average of 14.1 percent of U.S. supermarket sales over the past twenty years. They have performed substantially better in Canada and Europe. In Canada, store brands accounted for 20 percent of supermarket sales in the year ending 30 June 1990. The largest selling brand of chocolate chip cookie in Canada is Loblaw’s private label, President’s Choice. Between 1982 and 1990, while private label share declined in the United States, it rose from 13 percent to 23 percent in Germany and from 25 percent to 30 percent in the United Kingdom. Private label programs in Europe are also qualitatively different from those in the United States in that their products span the range of the quality spectrum, sometimes dominating the quality and assortment offered by manufacturers. The strength of private labels in Canada and Europe is presumably the consequence of a number of factors. Smaller national markets tend to favor fewer strong national competitors. Retail concentration also tends to be higher in Europe. And the imagination and management talent devoted to private labels in Europe also tends to be of a higher level than in the United States.8
The variation in private label share is closely linked to the business cycle. In Figure 1, private label market share is plotted against personal disposable income (we have statistically removed the yearly upward trend that is present in disposable income). Regression analysis of these data clearly demonstrates that changes in the share of private labels are inversely related to both coincident and lagged changes in disposable income.9 The belief that consumers are more price conscious during recessions is thus partly borne out; as incomes fall, consumers switch to private labels from national brands. However, we believe that the explanation is more complex. Manufacturers often set advertising budgets as a percentage of sales,10 so that they decrease their brand support during economic downturns, exacerbating the consumer income effect. Retailers, anticipating this consumer income effect, typically increase investment in their private labels during downturns. Thus performance of private labels may be due in part to a self-fulfilling prophecy about consumer behavior on the part of manufacturers and retailers.
Determinants of Private Label Success
Although variations in personal fortunes may help to explain year-to-year changes in demand for private labels, the relative performance of private labels in different categories cannot be explained so easily. There are three sets of players whose expectations and actions interact to affect private label success: consumers, retailers, and manufacturers. The needs, expectations, and behavior of consumers define the demand side. Retailer allocation decisions affect the supply. And the environment within which private labels compete is affected by the number, competitiveness, and actions of manufacturers of national brands.
Consumers
One of the primary roles of branding is to assure consumers of product quality.11 Branded products reduce consumer risk because they are likely to have lower variance in product quality.12 Although Porter and others have argued that there may be an inherent tradeoff between quality and market share, several studies of the Profit Impact of Marketing Strategy (PIMS) database have found that higher-quality products achieve higher market shares and return on investment.13 And eventhough PIMS firms are large national manufacturers, we expect similar results for private labels. Several studies quoted in the trade press attest to the importance of private label quality for consumers. A 1990 Gallup poll reported that 85 percent of consumers felt that quality was “very important” in their decision to repurchase a store brand, as contrasted with 73 percent who rated price as “very important.”14 Another Gallup study found that 73 percent of consumers rated private label quality as “very important” in their decision of where to shop, and 60 percent rated the variety of store brands offered as a “very important” determinant of store choice.15
The quality of a private label may be seen as having two dimensions: (1) the mean level of quality relative to that of national brands and (2) the variability in quality.16 The first dimension depends on technological barriers in manufacturing. In some categories (such as canned and frozen fruits and vegetables, vitamins, and sugar), the level of processing is low. Technology is inexpensive, and it has been around for a long time; there is likely to be excess manufacturer capacity. In other categories (such as paper products, batteries, laundry soap, cleansers, and frozen entrees), processing sophistication is high, and national brand manufacturers actively compete by way of continuous and expensive investments in technological innovation. The comparative quality of private labels in these categories is likely to be low.
Quality variability for private labels depends on the difficulty of implementing reliable, low-defect manufacturing. Again, for categories involving relatively unsophisticated manufacturing processes that are widely diffused, quality variability for private labels is likely to be low. For categories in which quality control involves manufacturing sophistication and plant automation levels that many private label manufacturers do not have, private label variability is likely to be high. Private label shares are likely to be higher in categories in which private labels have higher relative quality and lower variability.
The effect of private label quality on consumer choice and market share may be moderated by price. Consumers are likely to be willing to trade off price with quality, such that given a particular quality level, private labels may enjoy higher shares when their relative price is lower. However, some argue that private labels are likely to do well in categories where consumers are particularly price sensitive.17 In such categories, private labels may be sold at a smaller discount off the national brand price. Indeed one researcher found that private labels obtained higher share in categories where they sold at a small discount. Hence, the effect of relative price on consumer choice is ambiguous.18
Retailers
Having a private label brand presence in any product category requires that the retailer make an investment in packaging, inventory, everyday shelf space, promotional display space, and feature advertising. The functions of branding, packaging, production coordination or sourcing, and advertising are traditional manufacturer functions that are performed entirely by retailers for their private labels. The retailer bears the opportunity cost of shelf space as the minimum performance hurdle for maintaining everyday shelf space for private labels. In addition, promotional displays and feature advertising for national brands are funded cooperatively by the manufacturer and retailer, but they are funded entirely by the retailer in private label programs.
To recover these fixed costs, retailers must allocate resources to categories with the highest potential. Holding all else constant, the returns from a private label program will be highest in large categories (in dollar terms) that have high gross profit margins associated with them. Even a small share of a large category (e.g., ready-to-eat cereals) generates sufficient revenues to cover the overhead of the program, and high margins leave room to underprice the national brands and still make profits. We expect that private label shares will be higher in categories with higher dollar sales and higher gross profit margins. The retailer, however, cannot be myopic and ignore the effect of private labels on national manufacturer support of the major brands in the category. One study suggests that private label dominance in a category can lead to declines in manufacturer support and eventual contraction in sales and profitability for the category.19 Some industry observers believe that successful private label programs should focus on the merchandising of private labels “in addition” to national brands rather than “instead of” them and concentrate on categories with “substantial movement” and “profit opportunity.”20
Manufacturers
Manufacturers’ national brands are in direct competition with retailers’ private labels. Competition from national brands affects the difficulty of entering a category and subsequent sales success. Ease of entry into a category is dependent on the barriers created by national brand manufacturers. Two significant barriers to entry are competitive variety and advertising. Private labels are likely to be more successful in categories where they do not compete head on with differentiated national brands backed by heavy “pre-sell.”
- Product Variety. Categories differ in terms of the number of manufacturers in the market, the number of brands and product variants they offer, and the level of new product development activity. For example, there are over 1,100 shampoos on the market offered by many manufacturers with many brands in multiple sizes. In contrast, there are few national manufacturers of brands of salt and sugar and few size and flavor variants. Variety acts as a barrier to entry because market share is carved up into so many pieces.21 It’s hard for any new product, private label or national brand, to gain significant market share. Moreover, when new product activity is high, private label manufacturers will be hard pressed to mimic proprietary technology in a timely manner. We hypothesize that the greater the variety in a category, the lower the share of private labels in the category.
- Advertising and Promotion Intensity. Farris and Albion have argued that advertising may raise barriers to entry.22 Advertising can build the reputation of premium brands or raise their brand equity.23 In general, retailers will find it difficult to match the advertising levels of manufacturers. There are substantial scale differences between national manufacturers and local retailers, and margins are much tighter on the retail side. Manufacturers also have a much greater stake in their categories than retailers do; retailers have more than three hundred grocery categories to manage, and they spend significantly more of their advertising budgets on features (price and place) than on their “brand,” that is, store image. We expect that the higher the level of spending on advertising by national manufacturers, the lower the share of private labels.
The extent of promotions in a category may also have an impact on the willingness of consumers to buy private labels. Lal suggests that heavy promotional spending by national brands can crowd private labels out of the market.24 We hypothesize that private labels will obtain lower shares in categories where promotional intensity is high.
The Study
We conducted the empirical investigation to examine the influence of consumers, retailers, and manufacturers on private label success. We describe our data sources and then present the results.
Data Sources
Our data come from both primary and secondary sources. Because our market share data were for the calendar year 1987, whenever possible we attempted to find data for the explanatory variables for a comparable time period.
- Private Label Market Share. We obtained share data for 1987 from the SAMI database. The SAMI retail audit data were collected from a sample of supermarkets and therefore have a strong grocery orientation. The mix of categories is quite heterogeneous. The categories themselves typically were defined by the firms subscribing to the syndicated data and therefore tend to vary in their aggregation. In spite of this shortcoming, the SAMI categories represent a consensus of managerial judgment on what constitutes a category. We began with data for 210 categories, but, due to missing information, we ended up with 180 categories: dry grocery food (92 categories), dry grocery nonfood (35), frozen foods (16), refrigerated foods (14), and health and beauty aids (23). The SAMI data are broken down into regular private label and generic components. Generic products, however, represent a small fraction. We use total private label share as our unit of analysis, although the results are the same even when generics are excluded.
- Total Retail Sales Dollars and Gross Profit Margin. We obtained information about category size and profitability from Supermarket Business.25 This trade publication conducts a comprehensive annual survey of the food retailing industry. It surveys manufacturers, retailers, and other informed parties using questionnaires and secondary research. The product category breakdown used by Supermarket Business is directly comparable to the SAMI categorization. We obtained the following measures of category size: (1) total dollar supermarket sales (stores with more than $2 million annual sales); (2) total dollar grocery sales (includes supermarket and other food stores); and (3) total dollar retail sales (includes supermarkets, grocery stores, and all others). We also obtained an estimate of percent gross profit margin for each category.
- Product Variety. We calculated various measures of category-level variety using InfoScan data for the Chicago market in 1991. Information Resources, Inc. (IRI) creates InfoScan from scanner data from a representative sample of supermarkets. IRI also maintains a comprehensive product dictionary, which we used to double-check data in several instances. For each category, we obtained the following measures: (1) the number of national manufacturers; (2) the number of distinct brand names; and (3) the total number of Universal Product Codes (UPCs) in the category. UPCs are used to uniquely identify a particular item. These three measures represent conceptually distinct aspects of differentiation, although they all were correlated highly.26 Although we used the number of manufacturers in our empirical work, number of brands or UPCs provided very similar results. In order to capture the role of product proliferation as a consequence of the explosion of minor variants to basic brands in the 1980s, we computed the average number of UPCs per brand for each of the categories. This variable was uncorrelated with both the number of manufacturers and the number of brands, suggesting that proliferation within a category (measured by UPCs/brands) is a distinct concept from variety in the category.
- Advertising Expenditures by National Brands. Data on national advertising expenditures in 1987 came from Leading National Advertisers (LNA).27 LNA monitors national advertising on nine media (TV, radio, print, magazine, outdoor, etc.) at the brand name level (e.g., Tide detergent, Kellogg cereals). It reports the top ten advertisers for each category and the total category. In general, the product category classification used by LNA is more inclusive than that used by SAMI. For example, SAMI breaks pet food into dog and cat food that comes in wet, semi-moist, and dry versions, whereas LNA aggregates all of these product types into an overall pet food category. When there was no one-toone correspondence between SAMI and LNA (this occurred in about 50 percent of the categories), we made our best estimate in one of two ways: (1) we divided the LNA category into more specific SAMI categories based on individual brand names, or (2) we apportioned total advertising dollars on the basis of category size (i.e., relative retail dollars based on the Supermarket Business data). If these methods didn’t work, we combined multiple categories. For example, we aggregated several varieties of frozen vegetables (peas, beans, carrots) into one larger category and then weighted the other explanatory variables by their level of retail sales dollars.
We measured advertising in terms of advertising dollars per national manufacturer rather than the absolute level of advertising. We did this in order to control for category size; large categories tend to have more advertising. The measure serves as a proxy for the advertising “hurdle rate” or bond that new entrants to the category must meet. And the measure also reduces the likelihood that we would find a negative relationship between advertising and private labor share simply because categories with a greater private label presence have less national advertising.
- Pricing and Promotions. We obtained price data from a large supermarket chain in Chicago. For each category, we determined the average price of the private label (some categories have multiple private label items) and the average price of the leading national brands over a one-year period. One minus the ratio of these two prices represents the discount at which the private label sells. The InfoScan data provided us with a measure of the level of promotion intensity: the percentage of unit sales sold with some form of promotional support (e.g., price reduction, feature advertising, in-store display).
- Private Label Product Quality. We derived all of the previously described measures using reputable secondary data. When it came to obtaining information on private label product quality, we quickly realized that there was no secondary data source comprehensive enough to cover all the SAMI product categories. For example, Consumer Reports typically reviews consumer packaged goods less than once per issue. Therefore, we conducted a survey of retail experts. We identified quality assurance managers at the fifty largest supermarket chains and grocery wholesalers in the United States from Thomas Food Industry Register.28 The companies were widely dispersed across the country. These experts typically have graduate education in food science and have wide experience testing numerous product categories. We contacted each of these experts by telephone to solicit their participation and then sent them a questionnaire. Thirty-two people returned the survey (64 percent), resulting in twenty-five usable sets of responses (50 percent).
For each of the original 210 SAMI categories, the experts answered two questions concerning quality:
- How does the quality of the best private label supplier compare to the leading national brands in the product category? The respondents gave a rating using a one equals “much worse” to five equals “about the same” scale.
- Compared to other product categories, how much total variability is there in the quality of the private labels in the category? The respondents gave a rating using a one equals “much more” to five equals “much less” scale.
The experts received a one-page set of instructions explaining what we meant by each question and how to use the scales. The first question measures the retailer’s ability to procure high-quality private labels. The second question measures the consumer’s risk of buying a low-quality private label due to variability. Variability in private label product quality may arise from variability in a given retailer’s private label quality over time and from variability in quality across retailers at a point in time. We hoped that the two questions would provide us with surrogate measures of central tendency and dispersion in private label product quality across categories. These measures are meant to capture “objective” quality rather than quality as perceived by consumers. Although an exact correspondence may not exist between objective and perceived quality, convergence seems likely given the market level aggregation of our study.
The overriding sentiment of these experts was that quality of the best private label was quite close to that of the national brands (average of 4.6 on the 5-point scale). It is most likely that our experts were partisan to private labels. In fact, one aspect of their jobs involves monitoring and improving private label quality. For present purposes, however, it is not particularly problematic if the experts show a positive bias toward private labels; what is more important is whether the expert ratings help distinguish higher- from lower-quality private labels across categories. Another potential problem, however, has to do with the underlying causality between private label share and our experts’ quality ratings. In other words, does the relative success of a private label, observable by the expert, lead them to infer something about product quality? This problem is similar to that faced by researchers examining the relation between quality and market share using the PIMS database, which also relies on expert judgment. Given these issues, we searched for a convergent measure of quality.
We went through each issue of Consumer Reports (CR) for the past six years and found evaluations of thirty-six of the same product categories rated by our retail quality control experts. For each of those categories, CR provides rank-order quality information for leading national brands and some selected private labels (e.g., Safeway, Pathmark, Kroger). We computed two variables from the CR data: (1) relative rank of the best private label and (2) relative average rank of all private labels. These two measures correspond roughly with the experts’ ratings of quality of the best private label and quality variability. We averaged the quality ratings for the experts for each of the product categories and then computed the correlation between the average ratings of our retail experts and the CR ratings. The correlations were surprisingly high, an average of .77. Although these findings do not completely validate our measure of quality, they do suggest convergent validity.
- Extent of Retail Distribution. In order for a private label to have a large market share, there must be manufacturers that are willing to make it, and it must have wide distribution. Distribution penetration information for private labels is not readily available. Therefore, we used as our measure of market penetration the percentage of respondents who reported that their store carried a private label brand for each category. Our objective in controlling for distribution was to place private labels in all categories on a somewhat more level playing field. That is, by assuming that private labels were widely distributed in all categories, we could identify the other factors that influence relative success across categories.
Results
Our data analysis strategy was to estimate a series of hierarchically related regression models.29 The main objective was to examine the relationship between private label market share and the consumer, retailer, and manufacturer related variables while controlling for the impact of private label availability.
As we have indicated, we considered nine variables that could potentially account for private label success:
- Quality of the best private label;
- Quality variability of the private label;
- Category gross margin;
- Category retail sales;
- Level of price discount of private labels off national brands;
- Number of national manufacturers in the category;
- Amount of national advertising per manufacturer;
- Item proliferation; and
- Promotion intensity.
We controlled for extent of retail distribution.
In Table 2, we summarize the statistics. The results are summarized in Table 3, where we show the standardized beta coefficients for the independent variables along with their associated t-statistics and an adjusted R2 as an indication of overall fit. We estimated three different models. In Model 1, we grouped products into four broad categories: food, refrigerated (and frozen) food, nonfood, and health and beauty aids (HBA). In Model 2, we added the consumer, retailer, and manufacturer variables just described. In Model 3, we dropped out the four merchandise group variables in order to capture the effect of the variables.
When compared to food products, the Model 1 results show that private labels in refrigerated and frozen foods garner higher market shares whereas nonfood and HBA items obtain lower shares.30 This suggests that it is easier for retailers to imitate and offer value in prepared food products. This simple model explains almost 50 percent of the variation in share performance but, of course, does not provide much in terms of understanding or policy implications.
The Model 2 results demonstrate how the actions and interests of consumers, retailers, and manufacturers influence the performance of private labels. This model explains over 70 percent of the variation in share performance. The results indicate that private labels do better in categories where product quality is high and variability is low. The depth of the price discount is not a significant factor in explaining market share. Likewise, promotion intensity has no significant impact. Therefore, quality is more important than price. The results for gross margin and retail sales support the idea that retailers find it more attractive to invest their private label program dollars in larger, more profitable categories.31
The results concerning numbers of manufacturers and national advertising corroborate the notion that variety and advertising serve as barriers to entry to retailers. However, item proliferation in a category does not affect private label shares systematically. Perhaps it is the complexity of competition created by many players rather than the absolute proliferation of items that deters retailers. One could argue, however, that the negative effect of the number of manufacturers on private label share is a simple matter of arithmetic — more players means lower share for everybody, national brands included. In some sense this is probably true, but our data indicate that the effect is much stronger for private labels.32
A comparison of Models 1 and 2 suggests that consumer, retailer, and manufacturer variables account for a good portion of the observed differences in private label shares between the broad merchandise groups. The Model 3 results corroborate this view.33 In order to assess the robustness of these results, we conducted a series of cross-validations of Model 3, as shown in the fourth column in Table 3.34
Figure 2 illustrates our main findings. Private labels enjoy more success in categories where quality levels are high and variability low. They also do better in large (dollarwise) product categories that offer the retailer attractive gross margins. Private labels experience difficulties when competing against multiple national manufacturers that invest significant resources into media advertising.
Implications of the Findings
Retailer Perspective
Private labels vary dramatically across categories, both in the level of quality achievable and in the variability of that quality. It is apparent that, in some categories, consumers trade off quality for price in going to a private label whereas in other categories, consumers can attain comparable quality to national brands at a lower price. The strong relationship between private label quality and share confirms the trade press contention that the quality of private labels is a key element in success. As consumers are most interested in quality, a viable retailer strategy would be to buy from private label manufacturers that offer the best quality possible and to position themselves as offering quality similar to that of the national brands. It also suggests that retailers should think twice before offering a private label in a category where current technology prevents them from getting close to the national brands. Our findings do not support the view that consumers buy private labels merely because they are cheap; the price discount off the national brand has no significant relationship with private label share (if anything, it is in the opposite direction), suggesting that other factors explain success better. Retailer efforts to upgrade the overall quality of private label programs deserve careful attention. In many categories, consumers have sufficient familiarity with product benefits and attributes to make informed quality judgments. Here retailers can gain substantial market presence by offering high-value (high quality-lower relative price) private labels.
On the face of it, the relations between gross margin and category retail sales and private label share do not offer clean policy recommendations because it is difficult to determine causal direction. It does make intuitive sense that given scarce resources retailers should allocate merchandising effort to private labels according to category size and profitability, as apparently is guiding current practice. The underlying reasons for this have to do with retailer return on investment and the fact that in large profitable categories, retailer brands may be less likely to attract competitive responses from manufacturers.
Finally, retailers are less likely to succeed with private labels in categories where manufacturers have made substantial advertising commitments to brand equity and where there are many branded players. This affirms the view that advertising continues to play a vital competitive role for manufacturers in establishing brand preference among consumers and differentiating brands from lower price threats. The presence of many manufacturers in a category also intensifies competition in a variety of ways, the net result being a lower probability of private label success. It is interesting that other measures of competitiveness such as promotion intensity and proliferation are unrelated to private label success. Our study tends to show that competitiveness is a multidimensional idea best captured by the number of players rather than by narrower measures of competition.
In conclusion, we believe that retailers would do well to concentrate on categories where they can offer quality levels comparable to those of national brands. They should be less concerned with delivering deeply discounted prices. They also are well advised to tread lightly in categories where the number of national brand manufacturers and their advertising efforts make the arena more competitive.
Manufacturer Perspective
Manufacturers do not tend to think of retailer private labels in the way they think about other national brands, although there is some sign that this may be changing.35 This tendency may exist because private labels historically are followers, not innovators, and because private labels have limited advertising budgets.
Our research implies that this complacency may be dangerous. The increasing difficulty of finding truly innovative new products for manufacturers and the largely unexploited goodwill that retailer trademarks have in their trading areas combine to dull the edge that manufacturers have over retailers. As discussed above, the availability of high-quality products for private label programs affords a serious threat to national manufacturers. This is particularly the case for the third or fourth ranked manufacturer in a category with a “me-too” product. Indeed, as more categories mature and competition intensifies, manufacturing capacity that had previously been devoted to national brands will become available to retailers. Our findings suggest that this process is likely to be exacerbated in larger, high-margin categories. Product proliferation merely to increase variety or promotion expenditures merely to buy sales appear not to inhibit private label success.
Advertising, on the other hand, can safeguard against private label success. The traditional formula for building brands — to solve a consumer problem with a high-quality product and communicate it through advertising — has not lost relevance in creating differentiation and insulating manufacturers from price competition. Paradoxically, the presence of a large number of competitors has a silver lining for national brand manufacturers in that it does appear to deter retailer entry. In the absence of strident efforts at differentiation, it is entirely conceivable that more and more sophisticated retail marketing programs will relegate some branded manufacturers to the wings, as has been the case in several countries in Western Europe.
Limitations and Future Research
The purpose of our research was to establish some basic facts about private label success as measured by aggregate market share. There are some important limitations to an aggregate study. First, the fact that private labels have low share in a category at large does not imply that a particular retailer cannot create a successful program in that category. We have no means of measuring execution ability and differences in the quality of the merchandising and marketing support. Second, share alone is an incomplete indicator of success. Although private label market shares in the ready-to-eat breakfast cereal category are low (less than 3 percent on average in 1987), the category is the second largest in the supermarket and provides tremendous dollar sales and profit opportunities for the retailer.
Findings at the aggregate level nevertheless have value —- our study does establish the characteristics of categories where private labels do achieve market share success. For retailers, this means that they can account for these factors in evaluating the performance of their private labels across categories. The study may also provide a diagnostic tool for targeting categories in which to develop private labels. For manufacturers, the framework is useful in identifying those categories where a private label is likely to be a serious threat now or in the near future. Our findings are also instructive in their affirmation of much industry conventional wisdom regarding the importance of differentiation, via product quality and advertising, as a means of sustaining a competitive edge.
References
1. E. Shapiro, “Grocers’ Fancy Brands on the Rise,” New York Times, 14 January 1992, C1, 5.
2. B.P. Pashigian and B. Bowen, “The Rising Cost of Time of Females, the Growth of National Brands, and the Supply of Retail Services,” Working Paper No. 70 (Chicago, Illinois: Center for the Study of the Economy and the State, University of Chicago Graduate School of Business, 1991).
3. Shapiro (1992).
4. Until recently, SAMI was a major supplier of audit data collected by monitoring warehouse withdrawals in most major U.S. markets. SAMI’s product became less valuable as Nielsen and Information Resources, Inc. began offering more timely and accurate point-of-sale electronic data. See:
“The Rebirth of Private Label,” Advertising Supplement, Progressive Grocer, January 1990, pp. 75–82.
5. “National Brands, Private Labels, and How They Compete,” Progressive Grocer, October 1976, pp. 47–56; and
“Brand Power 1982,” Progressive Grocer, October 1982, pp. 49–104.
6. L.W. Stern and A.I. El-Ansary, Marketing Channels, 4th ed., (Englewood Cliffs, New Jersey: Prentice-Hall, 1992), pp. 67–73.
7. P.B. Fitzell, Private Labels: Store Brands and Generic Products (Westport, Connecticut: Avi Publishing Company, 1982).
8. The regression results, with t-statistics in parentheses, were (see here) where PLMS = private label market share and I = disposable income. The R2 for the regression is .57 and the Durbin-Watson statistic is 1.89, indicating the absence of autocorrelation.
9. “They Have Names Too,” The Economist, 24 December 1988, pp. 98–99.
10. P.K. Kotler, Marketing Management: Analysis, Planning, Implementation, and Control, 7th ed. (Englewood Cliffs, New Jersey: Prentice-Hall, 1991), pp. 581–582.
11. B. Klein and K. Leffler, “The Role of Market Forces in Assuring Contractual Performance,” Journal of Political Economy 94 (1981): 796–821;
P. Milgrom and J. Roberts, “Price and Advertising Signals of New Product Quality,” Journal of Political Economy 94 (1986): 615–641; and
B. Wernerfelt, “Umbrella Branding as a Signal of New Product Quality: An Example of Signalling by Posting a Bond,” Rand Journal of Economics 19 (1988): 458–466.
12. C.A. Montgomery and B. Wernerfelt, “Risk Reduction and Umbrella Branding,” Journal of Business 65 (1992): 31–50.
13. For more on PIMS, see:
R.D. Buzzell and B.T. Gale, The PIMS Principles: Linking Strategy to Performance (New York: Free Press, 1987);
M.E. Porter, Competitive Strategy (New York: Free Press, 1980); and
R. Jacobson and D.A. Aaker, “The Strategic Role of Product Quality,” Journal of Marketing 51 (1987): 31–14
14. “Private Label: Poised for Performance,” Advertising Supplement, Progressive Grocer, April 1991, pp. 85–98.
15. Ibid.
16. Montgomery and Wernerfelt (1992).
17. J.S. Raju, R. Sethuraman, and S. Dhar, “Cross-Category Differences in Store Brand Market Share” (Philadelphia: University of Pennsylvania, Wharton School of Business, Working Paper, 1992).
18. R. Sethuraman, “The Effect of Marketplace Factors on Private Label Penetration in Grocery Products” (Cambridge, Massachusetts: Marketing Science Institute, Report No. 92–128, 1992).
19. “Private Label’s Shortcomings,” Food and Beverage Marketing, 25 December 1989.
20. “Repositioning Private Label — It’s Part of a Broad New Strategy at Star,” Progressive Grocer, February 1977, pp. 107–108.
21. K.J. Lancaster, Consumer Demand: A New Approach (New York: Columbia University Press, 1979); and
R. Schmalensee, “Entry Deterrence in the Ready-to-Eat Breakfast Cereals Industry,” Bell Journal of Economics 9 (1978): 305–327.
22. P.W. Farris and M.S. Albion, “The Impact of Advertising on the Price of Consumer Products,” Journal of Marketing 44 (1980): 17–35.
23. Klein and Leffler (1981);
Milgrom and Roberts (1986); and
P. Nelson, “Advertising as Information,” Journal of Political Economy 82 (July-August 1974), pp. 729–754.
24. R. Lal, “Manufacturer Trade Deals and Retail Price Promotions,” Journal of Marketing Research 27 (1990): 428–444.
25. “41st Annual Consumer Expenditures Study,” Supermarket Business 43 (1988): 63–218.
26. The correlations were as follows: manufacturers with brands r = .77, manufacturers with UPCs r = .60, and brands with UPCs r = .64.
27. BAR/LNA Multi-Media Service (New York: Leading National Advertisers, 1988).
28. Thomas Food Industry Register (New York: Thomas Publishing Company, 1990).
29. The dependent variable in all the analyses was a logit transformation of each product category i’s private label market share (PLMSi),
where
logit(PLMSi) = ln{(PLMSi)/(100 - PLMSi)}.
A logit transformation is standard when the dependent variable is bounded as in the case of the market share variable (0 percent to 100 percent). The logit transformation also corrects for heteroskedasticity.
30. The food category serves as the base group with an implied coefficient of zero.
31. It is possible that an observed positive relation between margin and private label share is driven by the systematically higher margins offered by private labels. To assess the seriousness of this problem, we obtained private label margins from a large supermarket chain in Chicago for a subset of 138 of the categories and then backed them out of the aggregate category numbers. The estimated coefficient for the margin variable is actually slightly larger (.14 versus .11) when private labels are not included, suggesting that endogeneity is not a serious problem in this case.
32. The correlation between the number of manufacturers and the share of the private label is strongly negative (–.61) compared to the same correlations with shares of national brands: the top national brand (–.21), the second national brand (–.03), the third national brand (+.06), and the fourth national brand (+.17). Market share data for the top four brands in each category comes from:
Product Summary Report (New York: Mediamark Research, 1988).
33. The overall fit of this model decreases very little when the product class terms are dropped (R2 drops from .72 to .71). The decrease is not significant using the Chow models comparison test (F(3,166) = 2.29, p>.05).
34. We randomly selected two-thirds of the categories, estimated Model 3, and then used the model to predict the shares of the remaining categories in the hold-out sample. We did this procedure ten times to ensure stable results. The estimates are remarkably consistent. Also the overall fit in the hold-out samples is close to that obtained on the complete data set (.69 versus .71).
35. M.J. McCarthy, “What’s in a Name? Increasingly, Little, Research Suggests,” Wall Street Journal, 12 October 1990, p. B1; and
M.J. McCarthy, “Soft-Drink Giants Sit Up and Take Notice As Sales of Store Brands Show More Fizz,” Wall Street Journal, 6 March 1992, pp. B1–3.
Comment (1)
marc normandeau