Many companies are guilty of committing the seven deadly sins of customer value management (CVM). These outdated practices prevent companies from lowering customer acquisition costs, reducing customer churn, delivering more cost-effective customer service, strengthening customer loyalty and increasing long-term customer profitability. This article defines the seven costly CVM sins, outlines specific remedies and provides real-world success stories in a variety of industries.

Sin #1: Managing to the Averages

The idea of a huge market of "average customers" being satisfied with an "average product" is a myth. A "one size fits all" strategy often delivers high-cost customer service to the least profitable customers while under-serving the most valuable customers. There is, however, a more successful approach.

CapitalOne was founded in 1985, a time when the top 10 credit card companies were all charging 19.8 percent interest on card balances. The founders saw this as an opportunity and launched an information-based credit card company that could create a large number of product offerings targeted at specially defined segments. Critical to their model was the capability to precisely test offers in the marketplace. Remarkably, CapitalOne designed and tested more than 65,000 product configurations in 2002 alone.

CapitalOne enjoys revolving balances 50 to 100 percent higher than the industry average and impressive efficiency in their cross-sell efforts with more than 50 percent of their customers having signed up for at least one additional financial product or service. Charge-off rates are approximately 150 basis points below the industry average and net income, revenue and market capitalization growth rates exceed 30 percent compound annual growth rate (CAGR).

Avoiding the sin of "managing to the average" entails analyzing the customer base, identifying distinct micro-segments and developing specific offers that appeal to those micro-segments. Rapidly testing those offers in the marketplace will create an understanding about which micro-segments respond to specific offers. The process should be repeated until sustainable, profitable returns are achieved.

Sin #2: Ignoring the Customer Life Cycle

Savvy marketing executives recognize that customer preferences, behavior, lifestyle and buying habits change over time. However, many companies fail to create new values because organizational inertia prevents them from keeping pace with customers' changing needs.

There are, however, companies that have broken the mold. USAA, a premier insurance company whose credo is, "once a customer, always a customer," is passionate about managing the customer life cycle. They collaborate with customers to create new and relevant products that meet their evolving needs. Additionally, they build relationships with third-party providers that can deliver complementary products. As result, USAA customer retention rates rank among the highest in the industry.

Why do other companies continue to ignore the customer life cycle? Often, ingrained habits prevent companies from adopting new practices. Others fear increased service complexity and higher operational risks. This reluctance needs to be mitigated against the long-term benefits of improved customer relationships and actual customer lifetime value. As our client experience has shown, the financial and relationship benefits from the deployment of targeted, dynamic offers far outweigh the adoption risks.

One of the key observations from our experience is that "small is better." Organizations are best served by making a gradual transition from a static to a dynamic view of the customer, taking an approach that doesn't require major IT investments or process transformation. The cumulative benefits of a subset of limited market tests and process improvements can provide enough benefits to make these projects self-funding.

Sin #3: Single-Factor Optimization

Too many marketing investments are driven by analytical efforts that focus solely on a single component of a product's value proposition. Our experience suggests that three metrics that are often managed separately ­– acquisition, retention and cross-sell –­ should be integrated to provide a single view of the customer and to improve understanding of customer profitability.

Take the case of a national retailer running a highly visible national marketing campaign. Using traditional analytics to measure campaign performance, management was disappointed with what they viewed as an unacceptable average response rate of approximately one percent. However, several attractive micro-segments actually yielded response rates of approximately 10 percent. In addition, these customer segments were least likely to defect and more likely to respond favorably to other offers.

This example highlights the limitations of relying on "single-factor model" predictions. Executives need to quantify the joint probability of a variety of possible customer actions so that they can answer such questions as: How many customers are likely to respond to a campaign? What is the probability or rate of retention? How much are they expected to spend? Will these customers revolve their balances? Will payments be made on time? A "multifactor" approach that fosters a deeper understanding of the value inherent in a company's current and potential customers can yield dramatic benefits.

Sin #4: Costly Market Testing Techniques

Most marketing departments still rely on test-and-control methods, holding a small sample of customers as a control group for measuring performance. Although certainly appropriate in some cases, this approach fails to address the fact that a multitude of factors influence even the simplest of customer decisions. Traditional methods are not efficient in recognizing the complex interdependencies and trade-offs at play during the purchase decision. As a result, products come to market either over- or under-engineered. Product trial rates are disappointing, and the single-factor test results provide extremely limited information, which, it often turns out, are not a significant feature underlying many customers' decisions.

The goal of field tests should be greater understanding of what combination of factors yields the desired customer behavior and business results. A simple financial services example illustrates our point. When conducting a field test of a new credit card, it would be most beneficial to understand which among several product features or combination of features are those that differentiate responders from nonresponders. Variables could include pricing, billing cycle, customer service channel, targeting channel, message and preapproved charge limits.

Even a simple test such as this example with six factors at two levels yields a total of 64 combinations or possible response cells. Reliable field tests often involve the simultaneous assessment of many more factors. Extending this example to a situation involving 10 factors to test with two levels per factor yields a test matrix with 1,024 combinations. Clearly, it would be cost prohibitive, expensive and impractical to carry out such a test unless justified by the economics of the results.

Optimization theory makes it possible to efficiently test thousands of combinations quickly. Indeed, in our example involving 10 factors at two levels, the 1,024 combinations can be tested with a high degree of reliability with specially designed tests that involve only 10 unique (or orthogonal) combinations. With proper planning and design, these results can be attained in a single field test.

Results from this type of testing enable marketers to determine if an offer is successful and also identify which factors, such as customer characteristics, product features, pricing, channel preferences and geographies, contribute to the observed differences in response rates and profitability. In short, companies could maximize the return on their marketing testing efforts by leveraging recent developments in optimization theory and statistical modeling to conduct multivariable, statistically significant market testing that recognizes customer decision-making patterns.

Sin #5: Uniform Multichannel Delivery

While channel functionality is an increasingly important factor in customer purchasing decisions, often little effort is made to differentiate channels in terms of cost effectiveness, customer preference or relationship-building potential. This invariably leads to a misallocation of channel resources, eroding cost structures while undermining the customer experience.

The telecommunications industry provides a host of examples that demonstrate the benefits of supporting each channel differently on the basis of actual customer behavior and needs.

A major independent local exchange carrier (ILEC) diverted five percent of its traffic to lower-cost channels through predictive modeling and the delivery of targeted, compelling marketing messages. This ILEC's channel diversion plan generated $15 million in cost savings and $40 million in increased revenues. AT&T added a "click-to-chat" function to its Web site. This function is reportedly responsible for tripling online sales in only six months. ADC Telecom's Web-based self-service functions provided significant savings and improved customer satisfaction while decreasing call center volumes 25 percent. Bell Canada has seen 37 percent of its customer contact initiated online after revamping its Web site with additional customer-focused functionality. The savings have been significant.

Underlying these successful decisions was a belief that the companies could create win/win situations by basing channel investment decisions on customer behaviors, needs, preferences and perceived value.

Sin #6: Uniform Intrachannel Delivery

Only by integrating customer economics with customer behavior within a particular channel will enterprises be able both to serve customers better and maximize the return on their marketing and customer service investments. Failing to do so will inevitably lead to marked increases in delivery costs and customer dissatisfaction.

The experience of the elite salon, Frederic Fekkai, underscores this point. The high-end New York salon prided itself on personalized service and invested significantly in building a premium brand. However, an under-performing reservation process undercut that effort. Appointment conversations were rushed, mistakes were made and the "New York minute" pace of harried customer service reps offended clients who were really seeking a Paris-like experience. Salon management knew something had to be done and made three fundamental changes to align the reservation process with customer expectations.

Fekkai redesigned the call center process and call mapping to meet much higher performance metrics: 100 percent of the calls had to be answered by a receptionist within two rings and 90 percent of future bookings had to be made within 45 seconds.

They conducted analyses to determine how call volumes varied by season, day and intra-day, and concluded that that peak staffing levels needed to be 500 percent of previous peak levels. Staffing levels were subsequently aligned with varying call volumes. They hired receptionists with Southern French accents, including off-duty Air France flight attendants. Their French accents conform to the image of the salon, and by answering all calls within two rings, they delivered service consistent with client expectations.

Our clients have learned that finding the "optimal channel-service mix" and matching it to the proper customer segment is critical in ensuring sustainable and profitable growth. Given limited resources, the challenge is allocating marketing and customer service dollars across customer segments and channels to optimize profitability. The solution requires the integration of customer analytics with advanced concepts of mathematical optimization and, quite often, a spark of creativity.

Sin #7: Call Center as Cost Center

Using the call center only to service inbound inquiries is an opportunity squandered. By empowering call center personnel with the right information at the right time, companies can create win/win situations during each customer interaction, increasing both customer satisfaction and company profitability.

Integrating customer analytics with the real-time opportunity present at time of contact with a customer service representative (CSR) can yield rich dividends. Consider the example of a retailer that adds a code to each record in its customer information file (CIF) –­ "A" for top customers, "B" for high-potential value customers. By integrating this information at the point of sale or on customer service screens, CSRs can improve cross-selling efforts.

The integration of cross-selling scores with the appropriate product recommendations creates a tremendously cost effective cross-selling opportunity. The key to success is having a valid, analytically derived product basket recommendation that meets customers' needs and preferences available at the point of contact.

Underlying the success of these efforts must be timely information and the integration of product or service recommendations at the point of contact. Concurrent with this effort, of course, is the requisite training of customer service personnel to ensure that answers are provided and offers presented efficiently during the course of the customer interaction.

Every company aspires to bring the right product to the right customer, at the right price, through the right channel, at the right time. This is easy to say, but difficult to accomplish. Department silos, centralized customer decision rights, unwieldy technology infrastructure, misguided incentives and incomplete customer views are all serious impediments. There is no silver bullet to address all those issues. A big bang strategy rarely works and carries unnecessary risk. Our experience has shown that phased, iterative initiatives focused on curbing the seven deadly sins of customer value management can, however, yield immediate, measurable results that lead to greater profitability.

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