Editor's note: Madhav Srinivasan is with KPMG Peat Marwick's Economic Value Management Consulting Practice in New York.

Increasingly companies are discovering that classic customer satisfaction research does not provide a true understanding of customer behavior and market dynamics. Leading-edge organizations are evolving from surveying and reporting of customer satisfaction to the measurement of the generation and delivery of customer value. Dr. Bradley Gale, in his book Managing Customer Value, proposes a powerful and elegant framework for studying customer value. The customer value analysis approach focuses on the value perceived by customers on price and quality parameters relative to competition. Customers list the factors that influence their spending behavior, and accord relative importance to, and competitive ratings along, each factor. These factors are then collected under two headings - total quality and total price. By capturing the two key elements of customer value, this analysis provides a true comprehension of the customer behavior in a competitive marketplace.

The results of the analysis are presented in a two-dimensional plot, the customer value map, with perceived quality being the X axis and perceived price plotted on the Y axis. A fair value line passes through points where relative price and relative quality match, and has a slope equal to the relative importance of total quality divided by the relative importance of total price. The firm and its competitors are graphed on this plot based on their relative quality and price. Firms that land below the fair value line offer superior value as they provide higher quality at a lower price. Firms which lie above the fair value line offer inferior value as they provide lower quality at a higher price. The customer value analysis theory predicts that firms that provide superior value, and lie below the fair value line, will gain market share. Firms that provide inferior value, and lie above the fair value line, will lose market share. At the fair value line, market share remains constant as price and quality factors match equally.

The customer value map is a good graphical representation of the redistribution of future market share based on present customer value perceptions. However, it does not provide clear indication of what firms need to do to improve their value position and gain market share. In addition, the plot does not directly enable management to optimally allocate resources to achieve this objective.

Resource allocation matrix

The resource allocation matrix is a practical tool that facilitates this decision. It is based on the data that is collected in the customer value analysis, hence it's easy to generate and understand. The horizontal axis of the matrix is the relative importance of the factor, and the vertical axis is the numerical difference between the rating of the firm and its competitors along that factor. In this approach, price and quality factors are treated alike. The numerical difference between the rating of the firm and that of its competitors along each factor becomes a proxy for the firm's competitive advantage. The matrix thus elegantly captures the factors which drive customers' behavior, and the firm's competitive advantage. Plotting all the factors on the matrix leads to an efficient allocation of resources for maximum impact on customer behavior and competitors.

The four quadrants of the matrix are labeled attack, protect, withdraw and hold, indicating the type of strategy appropriate to the factors in that quadrant.

The factors in the attack quadrant are of highest importance to customers, and where the competition has a distinct advantage. These factors have the highest priority in resource allocation. Investments should be large and immediate. In the protect quadrant are factors which are of high importance to customers, and where the company has a competitive advantage. Investments should be made to protect these from competitive inroads.

The factors in the withdraw quadrant are considered of low importance by customers, but they perceive the company much higher than the competition. Focusing on these factors provides minimum benefit, and these have the lowest priority in resource allocation. Factors in the hold quadrant are regarded as low importance by customers, and they rate the company unfavorably versus competition. Resources presently allocated can continue at the present level, but no significant returns should be expected.

The actual demarcation between these quadrants is a matter of experience and judgment, and based on the circumstances in each analysis.

Since both the firm and its competition can perform customer value analyses, and arrive at similar results, the quadrants get reversed depending on the point of view. The firm's attack quadrant becomes the competition's protect quadrant; and the competition's hold quadrant becomes the firm's withdraw quadrant.

Using the resource allocation matrix

The utility of the resource allocation matrix is best illustrated by using it to comment on several customer value analysis examples in Gale's book.

AT&T's Universal Card versus American Express Card

The American Express card faced strong competition from the new AT&T Universal Visa card owing to a weaker customer value proposition both in relative quality and relative price. Based on the customer value analysis raw data, the Amex card falls above the fair value line and AT&T's Visa card falls below the fair value line. AT&T's Visa card would then be expected to gain market share from Amex. Constructing the resource allocation matrix, the competitive situation becomes much clearer. From AT&T's perspective, vendor acceptance is clearly a factor which is most important to customers and where it has the least competitive advantage - hence it's in the attack segment and a first priority for resource allocation. Phone calls and company logo are important to customers, but clearly here AT&T has a good competitive advantage, and where Amex would attack first. Protecting these features is key. Annual fees and vendor service fees are of low importance to customers, and here AT&T has a large competitive advantage, and their location in the withdraw segment indicates that there is nothing to worry about. Purchase protection is of low importance to customers and Amex has a competitive advantage, thus it's in the hold quadrant - here AT&T should continue with its current level of resource allocation.

Parke-Davis' Lopid cholesterol drug versus Merck's Mevacor cholesterol drug

The Lopid versus Mevacor story is interesting since there is comparable data for two points in time. Parke-Davis' Lopid was in competition against Merck's Mevacor drug for cholesterol treatment. Customer value analysis in this case predicted that Lopid would increasingly gain share against Mevacor. In 1989, the resource allocation matrix showed that lowering total cholesterol and lowering low density lipoproteins were of high importance to customers. For these factors, Lopid was perceived to lag Mevacor, and being in the attack quadrant, it's the first priority for Lopid's resource allocation. Reducing CHD risk and lowering triglycerides were of high importance too, but here Lopid had a good advantage. Raising high density lipoproteins is considered low importance by customers and Lopid is strongly positioned against Mevacor. Being in the withdraw quadrant, obviously not a concern for Lopid at this point.

Parke-Davis acted to change customer perceptions about Lopid by means of physician's education programs, a communications program, and working with blood-testing laboratories. In 1991, the impact was reflected in a changed resource allocation matrix. The major change was the increased importance given to raising high density lipoproteins by customers, and the marginally higher perception for Lopid on this factor. This feature jumps into the protect quadrant, and making it a point of potential attack from Mevacor. Lowering total cholesterol and lowering low density lipoproteins continued to be of high importance to customers, and Lopid still lagged Mevacor. Being in the attack quadrant, these two factors remained as first priority for Parke-Davis' resource allocation. Reducing CHD risk also increased in importance but here Lopid maintained its advantage. Mevacor would certainly be targeting to improve its advantage. Lowering triglycerides has fallen considerably in importance and Lopid is perceived better than Mevacor. Mevacor has been unable to improve its position on this factor.

Michelin's radial tires versus U.S. manufacturers' bias tires

When introduced into the U.S. market, Michelin's radial tires had an advantage against bias tires on relative quality but a relative disadvantage on relative price. When plotted on the customer value map, radial tires fell below the fair value line, and expected to gain market share. The resource allocation matrix shows that price satisfaction was clearly the factor that customers gave most importance, and here radial tires lagged the bias tires. Lying in the attack quadrant, reducing price should be the highest priority for Michelin. Factors like durability, safety and handling were of low importance and radial tires had a strong advantage, thus in the withdraw quadrant. On these factors, Michelin may consider withdrawing resources. The ride element was of low importance and the radial lagged the bias, placing it in the hold quadrant -- Michelin should continue allocating the same amount of resources on this issue.

Johnson and Johnson's endoscopic surgery for gall bladder versus traditional surgery

Johnson and Johnson's usage of customer value analysis allowed its endoscopic surgery instrument supply unit to gain large market share from traditional gall bladder surgeries. The resource allocation matrix shows that the cost of the operation is by far the most important single element for customers. And here, endoscopic surgery has a $3,000 cost advantage, putting this factor in the protect quadrant. In order to be competitive, traditional surgery would first look at reducing the cost of the operation. In comparison to price, all quality factors have a combined importance of 50 percent. Amongst these, hospital stay and at home recovery have high customer importance, and traditional surgery has relatively lower competitive advantage, thus also in the protect quadrant. These would be the quality factors on which traditional surgery would be focusing on, and the areas that endoscopic surgery has also to guard against. Endoscopic surgery has the least competitive advantage on complications rate and post-operative scar in the hold quadrant. This should continue to be in focus. Operation time is a factor in the withdraw quadrant that need not garner resources at this time. Interestingly, endoscopic surgery has such advantage over traditional surgery that no factor lies in the attack quadrant.

Robust technique

As these examples illustrate, customer value analysis is a robust technique applicable in a wide variety of situations. Understanding customer value drivers and relative competitive positioning along these drivers leads to accurate predictions of future customer purchasing behaviors. While the customer value plot remains an excellent graphical representation, the resource allocation matrix makes the analysis effective and actionable. Firms can make efficient allocation of their resources to impact customer buying behavior to their advantage, and thus achieve maximum marketing impact. And as the Lopid versus Mevacor example shows, customer perceptions of value change with time and through proactive intervention by firms. Periodic customer research then becomes essential to align resource allocation with market trends. Treating price and quality factors equally also ensures that firms make correct decisions on how much to change prices and affect quality. In management's quest for higher market share, loyal customers and profitability, the resource allocation matrix can become a powerful tool.