The numbers tell a sobering story about the state of branded goods: From 2003 to 2005, global private-label market share grew a staggering 13%. Furthermore, price premiums have eroded, and margins are following suit. Consumers are 50% more price sensitive than they were 25 years ago. In recent surveys of consumer-goods managers, seven out of ten cited pricing pressure and shoppers’ declining loyalty as their primary concerns.
Brands are on the wane. For the many consumer-goods companies struggling against this trend, it’s tempting to blame the big-box discount retailers. Plenty of anecdotes support their point of view. Recall what happened to Vlasic, for 50 years a beloved brand in America’s kitchen cupboards, when it started discounting its pickles by offering them in gallon-size jars in the late 1990s. Wal-Mart began selling the product for an unheard-of $2.99—a price so low that Wal-Mart soon made up 30% of Vlasic’s business. The supercheap gallon jar cannibalized Vlasic’s other channels and shrank its margins by 25%. When Vlasic asked for pricing relief, Wal-Mart responded by refusing an immediate price increase and reviewing its commitments to the line. By 2001, Vlasic had filed for bankruptcy.
Wal-Mart and other powerful retailers have undoubtedly weakened some brands, but a number of consumer-product companies have done a better job than Vlasic at managing both their relationships with retailers and their brands. For example, when Foot Locker cut Nike orders by about $200 million to protest the terms Nike had placed on prices and selection, Nike cut its allocation of shoes to Foot Locker by $400 million. Consumers, frustrated because they couldn’t find the shoes they wanted, stopped shopping at Foot Locker. Sales at a competitor, Finish Line, increased. In the end, Foot Locker acceded to Nike’s terms.
At the core of the differences in how Vlasic and Nike managed their brands is a crucial disparity in strategic perspective. Vlasic used a short-term sales strategy, focusing on a single, large channel partner and discounting its product to attract consumers. In addition, the company reduced advertising by 40% between 1995 and 1998. Nike, on the other hand, positioned itself for the long term. It maintained strong relationships with a variety of retailers and invested in brand equity, allocating $1.2 billion annually to its advertising budget. By setting its sights on a distant horizon, Nike continued to own its customers—and its brand—while Vlasic ceded both to the channel.
Companies routinely overinvest in promotions and underinvest in advertising, product development, and new forms of distribution. As a result, powerhouse brands have been weakened, often beyond recovery.
Our research into the role of marketing strategy in brand performance indicates that companies are paying too much attention to short-term data and not enough to the long-term health of their brands. They routinely overinvest in price promotions and underinvest in advertising, new-product development, and new forms of distribution. As a result of these shortsighted approaches, powerhouse brands have been weakened, often beyond recovery. It’s time for changes in how companies measure brand performance, how they communicate about their brands to the markets, and how they oversee brand managers. Those changes won’t happen without a major shift in thinking at the senior-management level. Corporate managers have the ability to make these sweeping changes. Do they have the will?
The Genesis of the Short-Term View
One wonders how manufacturers became so myopic about their brands. We suggest three factors: an abundance of real-time sales data that make short-term promotional effects more apparent, thus pushing manufacturers to overdiscount; a corresponding dearth of usable information to help assess the effect of long-term investments in brand equity, new products, and distribution; and the short tenure of brand managers. We’ll discuss each in turn.
Data are proliferating.
Before the 1980s, brand managers had to wait up to two months to get sales numbers. Matching weekly discounts to changes in sales was a difficult and error-prone task. That all changed with the advent of store scanners, which gave managers real-time sales data. These figures made it possible to attribute a spike in sales to a price promotion.
Although scanner data showed brand managers the clear link between discounting and sales, the numbers didn’t necessarily tell them much about whether a given promotion was profitable. For that assessment, they needed to compare sales at the discounted price with those that probably would have occurred without the promotion. To help brand managers predict the level of sales in the absence of a discount, and thus to assess the immediate profitability of promotions, baseline sales models were developed—in part by Leonard Lodish. (It’s important to note that, contrary to the belief of many brand managers, baseline sales are estimates—albeit very good ones—not measures of actual sales. Baseline sales are estimated by extrapolating from periods when there are no price reductions or other kinds of promotions.) This new metric further highlighted the short-term effects of trade promotions.
The profusion of data has had major consequences for the allocation of marketing dollars. According to various sources, from 1978 to 2001 trade promotion spending increased from 33% to 61% of firms’ marketing budgets. This growth occurred largely at the expense of advertising, whose effects play out over a longer time frame and are thus more difficult to measure. Advertising spending fell from 40% to 24% of marketing expenditures during this period. That level has held fairly constant in recent years.
The reallocation of spending away from long-term brand building and toward temporary price reductions was predicated on a short-term mind-set. Promotions yield an incontrovertible boost in sales, known as lift over baseline. This effect, however, is generally short-lived. To understand how promotions affect brands in the long run, consider some consequences of short-term sales approaches.
- Changes in consumer behavior. Shoppers aren’t naive; regular sales promotions encourage them to wait for the next sale rather than purchase a product at full price. As more people make purchasing decisions exclusively on price (a behavior that results in decreased sales when the product is not discounted), baseline sales eventually decrease and lift over baseline increases. From a short-term perspective, this lift makes promotions look highly profitable, so managers push for more discounts. Eventually, most of a product is sold at a discount, and profit margins decrease. The average brand manager, who believes that baselines do not change with pricing policy, is left to wonder what went wrong.
Shoppers aren’t naive; regular sales promotions encourage them to wait for the next sale rather than purchase a product at full price.
In addition, customers often stockpile a product if they think the price is particularly good. In the short term, this behavior may give the appearance of an increase in sales; over the longer term, however, customers simply delay purchases as they work through their inventory. In other words, stockpiling can amplify the immediate effect of a promotion without increasing overall sales.
- Diluted brand equity. By focusing consumers’ attention on extrinsic brand cues such as price instead of on intrinsic cues such as quality, promotions make brands appear less differentiated. Consumers, over time, become more price sensitive, and the product gradually becomes commoditized. Even stores can be threatened with commodity status. A factor cited in Kmart’s bankruptcy was the retailer’s reliance on discounts to attract consumers to the store. When it tried to curtail price promotions, sales plummeted. By communicating to shoppers that low prices were its main draw, Kmart had given customers no reason to develop any loyalty.
- Competitive response. When one firm increases its discounts, others usually follow suit. As a result, individual promotions increase but overall sales do not, further lowering everyone’s margins.
Together, these factors can substantially diminish the usefulness of sales promotions. In a study of 24 brands in Europe using data from 2002 to 2005, Information Resources, Inc. (IRI) found that the total impact of discounts is only 80% of their short-term effect (in other words, the effects measured over the long term turn out to be 20% less positive than they first appear). In contrast, the long-term effect of advertising can be 60% greater than its short-term impact. Research on 71 brands by a consumer-packaged-goods marketer in the United States resulted in a similar conclusion: Price sensitivity measured weekly is seven times higher than it is when the same data are assessed quarterly. This difference can be ascribed, in part, to the fact that weekly data recognize increases in purchases but ignore subsequent competitive price reactions and changes in consumer behavior. Nonetheless, the increased availability of short-term data dramatically affects perceptions of the value of promotions. As promotional measurement becomes even more granular (with daily and hourly data for sales available on demand), this short-term orientation will probably be reinforced.
Long-term effects are harder to measure.
While immediate increases in sales arising from discounts are striking, the effects of discounts and of other components in the marketing mix—such as advertising, new products, and distribution—can be understood only over the long term. However, because long-term effects are more difficult to measure than short-term ones, few companies pay much attention to them. Research to help managers take a longer view is increasingly available. Studies by Lodish and colleagues found that advertising has a small short-term effect on sales compared with the effect of a price promotion—but a TV advertising campaign that does generate significant sales increases during the first year will continue to do so for two more years, even if the ads are no longer being aired. The revenue arising from the first year of advertising approximately doubles over the subsequent two-year period. Equally important, if a TV campaign does not have a significant impact during the first year, it will have no long-term impact (and roughly half of all TV ads generate no lift in sales, according to some recent research).
One might conclude that TV advertising is difficult to justify on a short-term basis. We disagree with this view for two reasons. First, advertisers who test their ads in the market can isolate the campaigns that will increase revenues over the long term, since advertisements that are successful in the short run also have a positive long-term effect. Second, even campaigns that don’t do much to boost sales can increase margins by differentiating brands and thus allowing companies to raise prices. Indeed, Victoria’s Secret has conducted a number of regional and local TV advertising tests in which consumers in some regions were exposed to the ads and others were not. According to Jill Beraud, chief marketing officer of Limited Brands, the parent company of Victoria’s Secret, the brand’s TV ads do not generally increase short-term sales enough to justify the cost. However, Victoria’s Secret has linked increases in TV advertising to its ability to charge higher prices over the long term. The investment in TV advertising helps build the overall strength of the brand and decrease customers’ price sensitivity.
Companies have paid even less attention to the long-term effects of distribution and new products than they have to the effects of advertising. By coupling recent statistical advances with five years of data on 25 packaged-goods categories, Carl Mela and colleagues examined the long-term effects of distribution (the number and kind of stores carrying the product) and of product-line length (the number of items) and variety (the extent to which items are distinct). Results indicate that increases in the length and variety of a product line play a major role in boosting a brand’s baseline sales. Moreover, increased product-line variety and distribution in leading retailers reduce consumers’ sensitivity to price. Together, these results suggest that increasing variety and high-quality distribution raises sales and prices in the long run. Also of note, discounts had a deleterious long-term effect on brand performance.
An example of a company that has considered the effects of distribution is Lacoste, known for tennis shirts adorned with a tiny alligator. When the French company started selling the shirts in the United States in the 1950s, they became a fashion rage. General Mills acquired the brand in 1969, and it continued to sell well. However, in the mid-1980s, General Mills lowered the price on the shirts and broadened distribution to include discount outlets instead of adding high-end stores. The short-term effect was predictable: Sales increased. Yet the brand went from elite stores’ racks to clearance bins and lost its cachet. Lacoste repurchased the brand in 1992. The company limited distribution to higher-quality clothing retailers, advertised the brand through celebrities, and raised prices. A change in senior leadership in 2002 precipitated an even stronger brand focus. Since that time, sales have jumped 800%. However, in the initial years after Lacoste repurchased the brand, the company’s marketing efforts had little immediate effect on revenues. Had the company assumed a short-term sales perspective, it may not have been able to reinvigorate the brand.
Despite the growing evidence that marketing strategies—other than price promotions—yield positive long-term returns, companies continue to manage their brands with a short-term perspective. This orientation is exacerbated by Wall Street analysts who focus on quarterly figures to value firms and advise clients. Lauren Lieberman, Lehman Brothers’ equity analyst for cosmetics, household products, and personal care products, gave us a Wall Street point of view: “We analyze quarterly revenue and profit performance because it’s the best gauge we’ve got. But what we really value is sustainable top-line growth because we feel it is indicative of higher returns to shareholders over time.”
Of course this habit of looking chiefly at quarterly performance communicates itself to the companies being watched. Managers we interviewed at a major packaged-goods firm said that distribution in high-end stores and product innovation play the greatest role in increasing sales in the long term—but they focus their marketing programs and research efforts on discounting and advertising. When asked about the emphasis on discounts, they said they are judged on quarterly sales because investors focus on those numbers, and that the link between discounts and the current quarter’s sales is transparent. Thus, short-term numbers drive out those that tell the fuller story, leading managers to manage brands with the data they have, not the data they need.
Brand managers have short tenures.
The use of short-term sales data as a yardstick for brand performance can interact in unfortunate ways with the tenure of a brand manager—which is typically quite brief, often less than a year. Any brand manager who takes a long-term perspective—investing in advertising or new-product development—is likely to benefit the performance of subsequent managers, not her own.
In sum, the increasing availability of more thinly sliced short-term sales data has led to a greater emphasis on short-term marketing productivity, to the detriment of the long-run health of brands. Scanner data have been available for decades now, so it should be easier, not harder, to take a long-term view of brands. Unfortunately, most companies discard these data, unaware of how they can be used to track a brand not just over quarters but over many years.
A Long-View Dashboard
In the short term, discounts lift sales over baseline levels. But baselines and lifts are not immutable: They change in response to marketing strategy. Those changes signal a long-term shift in brand performance. Higher baseline sales mean that consumers are buying more of a product at full price. Think of this as a quantity premium. Whereas the baseline measure reflects only the volume sold when a product is not discounted, the lift-over-baseline measure represents the difference between discounted and nondiscounted sales. Smaller lifts reflect greater customer loyalty because loyals tend to buy regardless of the discount status. Brands with loyal customers face less pressure to reduce their prices and therefore enjoy a price premium. Together, quantity and price premiums reflect a brand’s long-term health. If both increase, demand and margins will be higher—along with brand equity and profits. If consumers pay less of a premium for the brand and baseline demand is decreasing, then the brand is headed in the wrong direction—and the firm has a problem.
A C-suite manager can monitor how a brand is doing in the long term by watching the following dashboard of measures each quarter:
- Baseline sales. Recall that this is an estimate of sales at a nondiscounted price. This measure reflects a brand’s quantity premium.
- The changes in baseline sales over months, quarters, and years and the statistical significance of those changes.
- The estimated response to regular prices and price promotions. An increased response to promotions reflects a decrease in the price premium a brand can command.
- The changes in response to regular and discounted prices over months, quarters, and years and the statistical significance of those changes.
Given the relatively short tenure of brand managers and the significant reallocation of resources that changes in long-term marketing strategy entail, someone higher up in the firm must track these measures. Such measures can also be useful tools for communicating the benefits of long-term marketing investments to a firm’s analysts.
To see what insights the dashboard can yield, consider the example of a large consumer-packaged-goods firm that, in conjunction with IRI, tracked the performance of one of its beverages from 1994 to 1999. The analysis revealed a 3% decline in baseline sales—an indication that shoppers were increasingly buying the beverage only when it was on sale—and a 14% increase in price sensitivity over that period. The overall brand decline was not obvious from the short-term sales data because the firm had increased discounts, which had led to a 7% growth in sales during the period. The damage to the brand became apparent when the company tried to raise prices in 1999. Consumers’ resistance to paying full price cost the brand more than $5 million in revenues. This debacle prompted a review of the brand’s strategy: Management discovered an 8% increase in promotion spending and a 7% decrease in advertising budgets.
How long-term metrics can redress short-term myopia.
We believe that the dashboard approach can improve brand performance over the long term in three ways.
First, this view prevents an exclusive focus on short-term data. If firms supplement sales data with data for quantity and price premiums, they will have a more complete sense of how various marketing programs affect their brands. Specifically, managers can establish whether price promotions have damaging long-term effects on brand equity and can therefore make more strategic decisions about marketing spending. Moreover, Wall Street analysts can use data on price premiums to get a better sense of a company’s profitability.
Second, brand managers’ performance can be judged on a combination of quarterly sales and quantity and price premiums. The temptation to discount a strong brand will be reduced, because damage to the brand’s long-term health will become more apparent. This will encourage managers not only to take a long-term view of performance but also to expend some effort determining which factors contribute to a brand’s strength. In addition, plots of dashboard metrics over time can serve as early warning systems to alert brand managers to problems.
Finally—and most broadly—long-term metrics inform a company’s marketing decisions. Consider, for example, the launch of a new product. When Kraft introduced DiGiorno Rising Crust Pizza, thereby creating a high-quality tier in the frozen pizza category, the company anticipated that the new product would cannibalize Tombstone, a mid-tier Kraft pizza. A recent study using long-term metrics shows, however, that the launch of DiGiorno had a consequence that Kraft did not anticipate: The new product did not just steal sales from Tombstone but caused its price premium—and that of all mid-tier pizza brands—to drop sharply. Apparently, DiGiorno made the mid-tier brands seem more ordinary to consumers; as a result, Tombstone was less able to withstand discounting from other pizzas like it. Ultimately, the introduction of DiGiorno was highly profitable for Kraft, but the company, unaware of the effect on Tombstone’s price premium, may have overstated the profitability of the launch. One can easily imagine that in other situations, a company armed with such metrics might have concluded that a launch would be unprofitable.
Data and methodology.
A company doesn’t truly have a long-term orientation unless it holds on to its data for longer periods and carefully analyzes the numbers.
We are astonished by the paucity of longitudinal data collected by the firms we visit. It is hard to see how companies can attain any insights into brand building with just 52 weeks of data, yet many firms have only that. Even major data suppliers such as IRI and ACNielsen discard data after five years—at the same time that they’re building more capacity and processing power to collect hour-by-hour measures. Hour-level data can undoubtedly be useful for monitoring stock-outs. However, it is difficult to imagine that local stock-outs affect market capitalization as much as brand equity, which often takes many years to build. Interbrand calculates the market value of the Coca-Cola brand to be $67 billion. This value developed over decades. It would be fascinating to study the evolution of Coke’s marketing mix—but in all likelihood it would be impossible to do so, because the data have probably vanished.
It is hard to see how companies can attain any insights into brand building with just 52 weeks of data, yet many firms have only that.
A detailed look at methods for analyzing long-term marketing results is beyond the scope of this article. The baseline sales and price sensitivity measures we propose for the dashboard are relatively easy and available from many data suppliers. Ideally, firms should collect and retain these measures over a long period—five years or more. Other analyses are more difficult. To assess the long-term effect of marketing strategy on brand performance, one would need to statistically link marketing policy over years or quarters to price and quantity premiums. This approach allows managers to gauge simultaneously the long-term effects of marketing campaigns on price premiums and the short-term effects of a given week’s discounts on that week’s sales.
