Eight weeks. That’s all that separated the launch of Apple’s revolutionary iPhone, on June 29, 2007, and Motorola’s next-generation Razr2 (pronounced Razr Squared) cellular telephone, on August 24. Before unveiling the successor to the Razr, which PC World magazine in 2005 ranked 12th on a list of the 50 greatest gadgets of the past 50 years, Motorola’s top management team was more worried than usual. With sales of the American communication giant’s other cellular telephones tapering off, the company’s fate rested squarely on the Razr2. Moreover, senior executives like chairman and CEO Edward J. Zander wondered if the iPhone had changed the competitive dynamics of the market in ways they hadn’t foreseen. Had the iPhone created a new niche or would it take the Razr2 head-on? How much extra could they charge for the Razr2’s new features? Should Motorola play up the Razr2’s noise-filtering technology, which it had patented? The executives couldn’t wait for the results of focus group sessions or sample surveys. They needed a fast, yet reliable way of capturing changes that were emerging in the market so they could finalize strategy quickly.
Like Motorola, most companies have to build fresh competitive advantages and destroy others’ advantages faster than they used to. As innovation pervades the value chain, they must migrate quickly from one competitive position to another, creating new ones, depreciating old ones, and matching rivals’. The process is disorderly and unstable. Senior executives desperately need new tools to help them systematically analyze their own and other players’ competitive positions in hypercompetitive markets.
One way to do that is to track the relationship between prices and a product’s key benefit over time. However, it isn’t easy to come to grips with either benefits or prices. Most customers are unable to identify the features that determine the prices they are willing to pay for products or services, according to a 2004 survey by Strativity, a global research and consulting firm. Worse, 50% of salespeople don’t know what attributes justify the prices of the products and services they sell.
If customers don’t know what they’re paying for, and managers don’t know what they’re charging for, it’s almost impossible for companies to identify their competitive positions. Whenever I’ve asked senior executives to map the positions of their company’s brands and those of key rivals, we end up confused and dismayed. Different executives place their firm’s offerings in different spots on a price-benefit map; few know the primary benefit their product offers; and they all overestimate the benefits of their own offerings while underestimating those of rivals. The lack of understanding about competitive positions is palpable in industries such as consumer electronics, where the number of features makes comparisons complicated; in markets like computer hardware, where technologies and strategies change all the time; and when products, such as insurance policies, are intangible.
Seven years ago, I came up with a way companies could capture competitive positions graphically to serve as the basis for strategy discussions. Drawn by using simple statistical analysis, a price-benefit positioning map provides insights into the relationship between prices and benefits, and tracks how competitive positions change over time. Executives can use the tool to benchmark themselves against rivals, dissect competitors’ strategies, and forecast a market’s future, as we shall see in the following pages. By creating an accurate map of the competitive landscape, companies can also get everyone in the organization on the same page. During my consulting and research work, I have applied this tool in more than 30 industries, including automobiles, advanced materials, artificial sweeteners, cellular telephones, restaurants, retailing, turbines, tires, motorcycles, and ships. Let me show you how to create and read a positioning map.
Drawing Positioning Maps
In its simplest form, a price-benefit positioning map shows the relationship between the primary benefit that a product provides to customers and the prices of all the products in a given market. Creating such a map involves three steps.
Define the market.
To draw a meaningful map, you must specify the boundaries of the market in which you’re interested. First, identify the consumer needs you wish to understand. You should cast a wide net for products and services that satisfy those needs, so you aren’t blindsided by fresh entrants, new technologies, or unusual offerings that take care of those needs. Second, choose the country or region you wish to study. It’s best to limit the geographic scope of the analysis if customers, competitors, or the way products are used differ widely across borders. Finally, decide if you want to track the entire market for a product or only a specific segment, if you wish to explore the retail or wholesale market, and if you’re going to track products or brands. You can create different maps by changing these frames of analysis.
Choose the price and determine the primary benefit.
Once you’ve defined the market, you need to specify the scope of your analysis of prices. You have implicitly decided whether to study retail or wholesale prices when you chose which market to focus on, but you must also consider other pricing parameters. You must choose whether to compare initial prices or prices that include life cycle costs, prices with transaction costs or without them, and the prices of unbundled or bundled offers. These choices depend on the yardstick that customers use in making purchasing decisions in the market under study. Remember to be consistent about the price definition you use while gathering data.
Identifying the primary benefit—the benefit that explains the largest amount of variance in prices—can be complicated. A product offers several benefits: basic functions, additional features, durability, serviceability, aesthetics, ease of use, and so on. Besides, companies usually differentiate products by focusing on a different benefit than competitors do. However, the success of strategies depends on the value that customers, not companies, place on features. To determine that value, you must first draw up a list of the benefits offered by all the different products or brands in the market and gather data on how customers perceive those benefits.
You should use unbiased data, rather than rely on gut instinct or top managers’ opinions, so that you estimate the benefits’ value correctly. There are more sources of hard data today than ever before. You can draw on the product ratings of independent organizations, such as Consumers Union, J.D. Power, and Edmunds, as well as on government agencies, like the U.S. Environmental Protection Agency and the U.S. National Highway Traffic Safety Administration. Consumer guides, such as Zagat and Michelin; websites, such as TripAdvisor and the Tire Rack; and trade publications, like Ward’s AutoWorld, also provide information on products and services. Industrial catalogs publish detailed product specifications, especially for high-tech and industrial goods. Distributors often collect details about product benefits. For example, vehicle dealers gather warranty information to track how reliable automobiles are. Your own R&D department probably tracks scientific data: Consumer electronics manufacturers, for instance, collect information on audio and video systems’ reproduction quality.
Once you’ve gathered data on products’ benefits and prices, employ regression analysis to find out which benefit explains most of the variance in products’ prices. Using regression analysis is more reliable than asking people how much they are willing to pay for each feature because consumers often can’t explain how they make their choices and they often don’t do what they say.
Regression analysis examines the relationship between a dependent variable (in this case, price) and several independent variables (product benefits) and creates a mathematical model of that relationship called the regression equation (in this case, the price-benefit equation). Many software packages—Excel, SAS Analytics, and SPSS 15.0 for Windows, for instance—allow executives to perform regression analyses. When the software finds the regression equation, it will also yield an incremental r-square statistic for each independent variable. That statistic shows the extent to which each benefit contributes to the differences in the prices of competing offerings while controlling for the impact of all other benefits. The benefit with the highest incremental r-square accounts for more of the variation in prices than the other benefits, so it’s the most important driver of price. If several benefits correlate with one another, that suggests they jointly influence price differences. In such cases, you can combine them into a single benefit by creating an index or a scale—a common practice in marketing research.
Plot positions and draw the expected-price line.
When you have identified the primary benefit, you are ready to draw a positioning map by plotting the position of every company’s product (or brand) in the marketplace according to its price and its level of primary benefit. Such positioning maps may be an oversimplification, but they show the relative positions of competitors on a common scale.
Finally, you must draw the expected-price line—that is, the line that best fits the points on the map. The line shows how much customers expect to pay on average to get different levels of the primary benefit. In addition, the line’s slope tells us how much more a customer is likely to pay for a higher level of the primary benefit. You can find the line that best fits the data by taking the slope associated with the portion of the price-benefit equation that links the primary benefit to prices. Or you can look at the map and draw a line that runs roughly through the middle of the cloud of points; in other words, half the points should lie above the line and half should lie below. Research shows that in almost all industries, a straight line that rises to the right fits the data best. Curved lines and negatively sloped lines are possibilities in theory, but they describe short-lived phenomena. Markets tend to converge on the same price for each benefit, and people tend to pay more for a higher level of benefit, so those trends create a straight line with a positive slope.
Products lie on either side of the line not by accident but because of companies’ strategies. Enterprises position a product or brand above the line to maximize profits, which they can do by simply raising the price in the short run. They can also do so by enticing customers to pay a higher price for desirable secondary benefits. Companies can slot their offerings below the line to maximize market share by simply charging less than expected, or they may drop some secondary benefits to attract price-sensitive customers. Sometimes, a product’s secondary attributes may actually reduce its price below what people would usually pay for that level of benefit. For example, if a calorie-free sweetener leaves an aftertaste, people will pay less for the same level of dieting benefit the sweetener gives them. Thus, deviations in price above or below the line are caused by the added or reduced value associated with secondary benefits or pricing strategies designed to milk or build market share.
Let me illustrate the process and purposes of drawing a positioning map by returning for a moment to the challenges that Motorola faced in launching the Razr2. In early June 2007, my research assistant and I spent a week collecting data from public sources on 40 “unlocked” cellular telephones, which work with the calling plans of many U.S. cellular service providers. We also gathered all the data we could find on the iPhone. We drew up a list of the phones’ features, consumer ratings of those features, and retail prices. A regression analysis showed that advanced functionality accounted for most of the difference in the prices of cellular telephones. By advanced functionality, I mean high-tech features like the ability to play music in the MP3 format and to snap high-resolution photographs, the presence of sophisticated e-mail software, and a QWERTY keyboard. Advanced functionality accounted for 68% of the variation in prices, and according to my analysis customers paid on average $28 more for each advanced feature in a cellular telephone.
Two other benefits contributed to price differences, albeit to a lesser degree: display quality (color, high-resolution screens, and touch screens) and advanced connectivity (Bluetooth, 3G, and Wi-Fi technologies). These three benefits together accounted for 80.5% of the difference in the prices of handsets. Contrary to the popular perception that battery life and the clarity of sound while making and receiving calls matter to consumers, I found that competition had reduced those to hygiene factors (indicated by the fact that their r-square values were extremely low). Although Motorola has patented a technology that filters out background noise from conversations, the results suggested the company should think twice before emphasizing that as one of the Razr2’s main benefits.
When I mapped the competitive positions that various products occupied in the marketplace and drew the expected-price line, I found five clusters of mobile phones (see the exhibit “Mapping the Cell Phone Market”). Motorola had wisely spread its bets, positioning products in four of the five groups. Like all the other cellular telephone manufacturers, it had no product in the ultrapremium segment that the iPhone seems to be pioneering, but it had positioned products on both sides of the expected-price line. For example, in the midrange group, the Razr V3c was almost exactly on the line, whereas the Razr SLVR L7 and Razr V360 were below it. Sony Ericsson, Samsung, and LG had also positioned devices below the line, which suggested that the segment was becoming crowded and prices would soon go into freefall. The LG VX9800 had positioned itself above the line, because of the added pricing power of its superb color display.
Clearly, the iPhone will have a major impact on the superpremium segment; Motorola’s Q, for example, will be outclassed. While some customers are likely to postpone purchases of cellular telephones until they can afford the iPhone, it is unlikely to have an impact on the rest of the market—initially. However, Motorola will face a stiff challenge because Apple is deploying its iPod strategy in the cellular telephone market.
In the market for downloadable-music players, Apple started in a high-price, high-benefits position but rapidly moved down and to the right by lowering the price for the same primary benefit (see the exhibit “How Apple Set the Pace with the iPod”). In like vein, the company slashed the price of the iPhone by 33% in early September, two months after its launch. If Apple continues to use the same strategy, the iPhone will move quickly from the ultrapremium to a midrange position. The Razr2 will then become a basic phone because it doesn’t offer the iPhone’s advanced functions.
Apple also created a full line of iPod products, making it tough for rivals to find uncontested spaces. If it does the same with the iPhone, Motorola will soon have to contend with a line of iPhones that will match Motorola’s full line of Razrs. Motorola would do well, in that case, to push those of the Razr2’s advanced functions that consumers value most, rather than add more secondary features. For instance, having a haptic touch screen on the Razr2 is a novel benefit. Do customers want it? Perhaps—but it comes second to the advanced functionality they are more willing to pay for.
Interpreting Positioning Maps
Positioning maps help companies penetrate the fog that shrouds the competitive landscape. They can pinpoint the benefits that customers value, locate unoccupied or less competitive spaces, identify opportunities created by changes in the relationship between the primary benefit and prices, and allow companies to anticipate rivals’ strategies. When interpreted within the context of industry and customer knowledge, they help explain why some enterprises’ products and brands perform better than others do.
Valuing intangible benefits.
Many companies, especially in industrial markets, seek to retain customers by offering intangible benefits. To that end, they spend a great deal of money to offer supplementary services without knowing if customers want them enough to pay for them. This often proves to be a drain on corporate resources. Companies can avoid the problem by calculating the premiums they earn for intangible secondary benefits.
That was driven home to me when my colleagues and I conducted an analysis of the U.S. motorcycle market. According to a regression analysis, in the early 2000s, variations in engine power, as measured by displacement, explained much of the difference in motorcycle prices. Yet a positioning map showed that, in 2002, most of Harley-Davidson’s models earned large premiums compared with rival products. Customers paid 38% more, on average, for Harleys than they did for motorbikes from Honda, Yamaha, Kawasaki, and Suzuki, even though the Japanese Big Four offered 8% to 12% more engine power. Because we had accounted for the impact on prices of all physical features and attributes, we concluded that the premium was most probably the result of the intangible secondary benefits the company offered, such as the image created by membership in the Harley Owners Group (HOG) and apparel from Harley-Davidson’s MotorClothes. These benefits had helped Harley-Davidson create the impression that its customers were rebels, that they enjoyed an adventurous lifestyle, and that they belonged to a macho club. Harleys had attained cult status, especially among the baby boomer generation.
However, the 2004 positioning map revealed a different picture. The price of a Harley was still higher than that of equivalent Japanese motorbikes, but it no longer commanded the highest premiums in the market. New American rivals, such as Victory and Big Dog, earned a 41% premium over Harley-Davidson for the same level of engine capacity. The market leader was leaving money on the table, possibly because its image no longer appealed to customers. We hypothesized that both Generation X and Generation Y consumers were seeing the Harley as their father’s motorbike and that many women hated its bad-boy image. Victory and Big Dog had capitalized on the desire for a “New American Bike” as opposed to Harley-Davidson’s “Easy Rider” image, which the Harley Owners Group and Harley’s MotorClothes helped maintain. The newcomers’ highly customized products were trumping Harleys because riding a motorcycle had changed from being an act of rebellion to one of self-expression.
The 2004 analysis was an early indicator that Harley-Davidson was in trouble, despite the fact that industry experts insisted it would remain dominant owing to its history and market share. As it turned out, by 2006, Harley-Davidson recognized the need to create a new image for its products, saying in its annual report: “We’ve embarked on a full range of marketing outreach activities, new events, and new strategies to connect with emerging customer segments. Through these efforts, we welcome more and more African-Americans, Hispanics, women, and younger riders into the family every year.” These initiatives included ladies-only “garage parties”; a line of women’s jackets in pink, blue, red, and other bright colors; and motorbikes with lower seats to accommodate customers with smaller builds. Harley-Davidson is also using its new Buell line to reach out to younger riders who want to have fun rather than portray a macho image. Still, Harley-Davidson’s stock price floundered between 2005 and 2007, rising only recently on rumors that Honda is trying to acquire it!
Anticipating shifts in the value of benefits.
Companies can employ the price-benefit equation to get ahead of rivals in markets where consumers keep demanding different benefits. Once they have identified what benefits appeal to customers, executives can use the equation to decide which features to develop, at what cost, and how soon they must create the next differentiator.
Take the case of a major U.S. hotel chain that in 2000 wanted to know what new restaurants it should open in its New York City hotels, which ones it should reformat, and how it could earn more from them all. The food business is notoriously fickle, so I decided to conduct a three-year historical analysis of the 1,700 restaurants in the city on which Zagat, the restaurant guide, had data. The eateries served every possible cuisine, from pizza to French haute cuisine, and they were located in all the city’s boroughs. The restaurants in the analysis ranged from Gray’s Papaya, which featured a $2 two-dogs-and-a-tropical-drink special, to Le Bernardin’s seafood, which set a customer back $75, on average, for dinner and a drink in 1998.
The analysis revealed that from the beginning of 1998 through the end of 2000, the primary driver of variations in food prices wasn’t restaurants’ locations or the type of cuisine, as one might expect. It was a composite factor I called “customer experience”—the extent to which the decor, the taste of the food, and the service satisfied customers. That explained 73% of the variation in prices, whereas cuisine accounted for a mere 3.5% and location just 2.5%. Other features, such as outdoor tables and dancing, were each responsible for only 1% of the differences in price.
The longitudinal study helped identify several trends and strategies. Initially, locating a restaurant in a hotel added between $2 and $3.60 to the price that could be charged for each meal, but that amount declined significantly between 1998 and 2000. This suggested the hotel chain would do better if it placed restaurants outside its properties, with an entrance from the lobby. Restaurants with dance floors charged $4.50 to $7.25 more for a meal and saw their pricing power rise over the three years. That was a convincing argument for adding dancing to the menu—something the W Hotels chain, which turns its lobbies into clubs, has successfully done. The premium on seafood and Russian food rose during the period while it declined for French and Japanese cuisines, indicating that the hotel chain could earn more by repositioning its sushi bars as seafood restaurants and setting up restaurants that served Russian food.
Interestingly, the expected-price line became steeper over the three years of the study, an indication of a more intense demand for the primary benefit. So it wasn’t surprising that high-end restaurants were enjoying a rising premium for the customer experience they offered while the pricing power of low-end restaurants was eroding. It seemed plausible that as incomes rose in the city over the period, more people frequented upscale restaurants. Declining demand at the low end meant that such restaurants had to offer better deals to hold market share or to grow: For instance, a meal’s average price in restaurants with the lowest ratings in our sample fell from $7.20 to $5.80. The tilt in the line was good news for restaurants in the hotel chain’s high-end properties, but it created a dilemma for the middle-tier properties. The chain decided that instead of reducing prices in the restaurants in those hotels, it would enhance the customer experience or change the restaurants’ cuisines. In its budget hotels, the chain lowered the price of the food to match or undercut local rivals because those restaurants needed traffic to make money.
Finding paths of least resistance.
To extend the use of price-benefit maps, companies can throw more data into the mix. A map that includes unit sales and sales growth, for instance, can help companies identify areas with low competitive intensity. In the 1990s, when I worked with a major U.S. automobile manufacturer, we created positioning maps to spot fresh opportunities in the American midsize-car market (see the exhibit, “Finding Opportunity in the Crowded Midsize-Car Market”). A regression analysis showed that the most important driver of price in that segment was a measure that combined several automobile characteristics such as engine power, chassis size, passenger capacity, gasoline tank capacity, trunk capacity, and crashworthiness. We called this primary benefit, the “platform,” for lack of a better word.
When we created a price-benefit positioning map for 1993, we found some subsegments with few big sellers or products whose sales were growing markedly, an indication of low competitive intensity. In niches like the pricey low-end (where the low-end versions of luxury brands like Mercedes and Volvo reside), companies were withdrawing models from the market. This suggested that a manufacturer with the right price-platform mix and some desirable secondary benefits could find untapped customers by offering products in those spaces. Auto aficionados will remember that in the mid-1990s, many experts criticized BMW for trying to enter the pricey low-end subsegment of the U.S. market by repositioning the 3 Series. The map indicated that there was an opportunity—and history tells us that BMW capitalized on it.
Fast-forward to 1999, and you will see that there were few open segments left (that is, segments with fewer than a couple of big sellers or fast-growing models). Most companies had moved from intensely competitive positions in 1993 into less competitive positions. For example, there was an exodus from the basic and bargain midrange positions. The three big sellers in the 1993 basic subsegment—the Buick Century, the Honda Accord, and the Nissan Altima—all moved to new positions by 1999. The Honda Accord moved to a bargain low-end position, the Century shifted to a bargain midrange position, and the Altima created an ultralow position in the basic niche. At the same time, the 1999 map indicated some opportunities. The pricey midrange—the white space between the pricey low-end and pricey high-end segments—was still virgin territory, while the Saab’s 9-3 was exploring the white space below the premium end of the expected-price line.
When customers’ priorities shift radically, the benefits they desire also change. Careful price-benefit analysis can provide an early warning of such a shift. For example, the slope of the expected-price line in the midsize-car market declined throughout the 1990s, implying that customers were becoming less willing to pay for a larger platform. Instead, our regression analyses showed, customers were starting to pay more for safety. In 1993, customers weren’t willing to pay very much for new safety features, but by 1999 they were paying an extra $1,800 for each increment of improvement in air bags and crash test performance, and an additional $1,500 for antilock-braking systems. The rate of change in the expected-price line’s slope suggested that the basis of competition among midsize cars would shift by the 2000s. Sure enough, by 2001, safety features overtook the platform as the primary benefit that customers looked for in midsize cars. Due to the advance warning provided by this analysis, the car manufacturer I worked with was able to anticipate the shift, rather than play catch-up.
Companies can use price-benefit maps to predict the strategic intent of rivals and to find ways of preempting them. One method of doing that is to draw maps based on projections of market trends. That’s what a division of a U.S. Fortune 500 company did. The $1 billion unit, which I’ll call Primo (the company requested anonymity), manufactures advanced materials for high-tech component makers in the electronics industry. When its senior managers and I teased out the impact of each feature, we found that the product’s primary customer benefit was performance. At that stage, Primo sold a high-priced product that delivered better results than the offerings of its three major rivals, an American company I’ll call Neutryno, and two Japanese competitors I’ll label Tokyo Tech and Samur-Ion. In 1997, Primo had the biggest market share, as indicated by the size of its circle in the exhibit “Capturing an Evolving Strategy.” But its rivals were improving quality and reducing prices. We projected and mapped their possible trajectories, based on the firms’ historic rate of improvement.
When Primo’s senior executives saw the map, they were shocked. According to the scenario, Primo’s competitors in this highly price-sensitive market would dominate the market by 1999 because they would be able to offer more for less. Primo’s executives decided to seize the initiative. They increased R&D investment to come up with product improvements and process changes that would lower manufacturing costs. Primo first moved at the high end, pushing the expected-price line to a higher level of the primary benefit even as it lowered prices. It also split its high-end product into three, so that customers interested in middle-level performance would stop buying low-end products, while high-end customers might stick with its premium product longer. More and more people began to use the products, and to use them in additional applications. Primo gained market share, which more than made up for the loss in margins. The strategy hurt Neutryno so much that it quit the market.
Having outpaced its competitors, Primo then decided to outflank them. In 2000, Primo moved one of its products down the new expected price line to a low-cost position in the basic segment. The same year it also introduced a high-end product for a new generation of electronic devices. Between 2001 and 2004, the company reduced this product’s price as Primo gained experience and economies of scale, moving it from a high-end niche to the mass market. Primo also sold its old product at a discount to keep its Japanese competitors pinned down at the market’s low end. This cut deep into its rivals’ profit margins, which left them without the money to invest in new product development. Had it not been for their parents’ deep pockets, the Japanese companies would have left the market. Not only did Primo escape the vicious cycle of declining market share and profit margins but it also turned the tables on rivals by shaping the emerging competitive landscape. By forecasting the movements of prices and benefits, Primo stayed ahead of shifts in the expected-price line—and its rivals.• • •
A price-benefit map sounds early warnings, suggests responses to competitive threats, and opens executives’ minds to many possibilities. Like all strategy frameworks, it isn’t a silver bullet. Every map suggests several hypotheses about the reasons behind changes in competitive positions, and executives must use their knowledge of the industry to interpret them and arrive at the right strategies. Ultimately, though, price-benefit maps allow executives to make decisions based on fact and to avoid the fatal allure of wishful thinking.
A version of this article appeared in the November 2007 issue of Harvard Business Review.
Whenever I’ve asked senior executives to map the positions of their company’s brands and those of key rivals, we end up confused and dismayed.
“Customer experience”—a combination of decor, taste of food, and service—accounted for 73% of the price variation at NYC restaurants; cuisine accounted for 3.5%, location just 2.5%.
Many experts criticized BMW for repositioning the 3 Series. The map indicated there was an opportunity at the pricey low end—and history tells us that BMW capitalized on it.
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