Managing Customer Acquisition: Managing acquisition strategies and tactics is vital to creating,...

Companies must acquire assets before they can manage them. For this reason alone, customer acquisition merits our attention. But customer acquisition is also important for other reasons. The most obvious is that all firms--even those with high retention rates--lose customers and thus must continuously

acquire new customer assets. Second, the more efficient and effective a company's customer acquisition, the larger the pool of affordably acquired assets whose retention and add-on selling value can be captured.

Third, the customer-firm relationship developed during the acquisition stage strongly influences retention and add-on selling. Much depends on the kinds of customers a firm acquires and on the expectations that these customers have. Many firms behave as if the strategic elements of customer equity--acquisition, retention, and add-on selling--function independently.

For example, firms often analyze data about existing customers without considering response and interacting data about non-acquired prospects. This results in misleading conclusions and missed opportunities because it gives no insight into what prevented the non-acquired prospects from becoming customers.

Failing to link customer acquisition to retention also leads to other errors, including inaccurate forecasts about how long customers stay, the profitability of customers, and the impact of marketing efforts. (1) The usual result: a myopic, acquisition-fixated marketing strategy that leaves substantial customer equity on the table.

* What Is Customer Acquisition?

There are two ways to define customer acquisition. The acquisition transaction perspective says that customer acquisition ends with a customer's first purchase. The acquisition process perspective states that acquisition includes the first purchase as well as other non-purchase encounters that both precede and follow the purchase, up until the time the customer makes a repeat purchase.

The process perspective is better because it includes the initial bonding and development stage of the customer-firm relationship. This is a very important time, during which the customer forms attitudes about the firm's product and ancillary services. It includes interactions such as customer service encounters that affect the customer's decision whether to purchase again. Managers, for their part, face many difficult business decisions at this stage, such as how much to invest in courting prospects and what service levels to offer them.

Throughout the acquisition process, companies incur significant non-product costs. For instance, financial planners often meet with clients several times prior to first purchases, and direct marketers may send numerous mailings before prospects respond. Then, once a first purchase is made, a customer may request service or other activities that impose further costs. All this is part of customer acquisition. The retention phase of the relationship begins once the customer decides to make the first repeat purchase.

* Which Firms Should Emphasize Acquisition?

Although all firms need to direct some attention toward customer acquisition, the optimal amount of that effort depends on a business's ability to retain customers, its customers' repurchase frequency, and its relative opportunity to acquire versus retain customers.

Some industries simply have low retention rates. How many people, for example, go back to the same used car dealer to purchase a car? Used car sales has long been an acquisition business. Businesses whose products have low purchase frequencies also favor an acquisition-heavy approach. Consumer durable-goods firms focus on acquisition in response to the fact that many of their products have ten-year to fifteen-year lives, and in recognition that many uncontrollable factors affect retention rates for products with such long purchase cycles.

At the other extreme are firms with exceptionally high retention rates due to high switching costs. These rates raise the future equity of acquired customers. Switching banks, for example, can entail significant costs for individual customers and business clients alike. Once customers make a commitment, they want to stay put. As a result, banks can and should focus a larger share of their effort and expenditures on acquisition. (2)

Firms in new or underdeveloped markets should direct a higher percentage of their marketing investments toward customer acquisition, in order to generate awareness and penetration for their products. Internet-based companies frequently forsake short-term profits to build a customer base. (3)

* Developing a Customer Acquisition Strategy

Selective Acquisition

Historically, the pursuit of market share has driven the customer acquisition investment of the majority of companies. The attitude has been to acquire as many customers as possible, as AOL did in 1997 when it acquired 500,000 new customers in one month. (4) Fewer firms have adopted selective customer acquisition policies. This approach assumes that not every potential customer is worth the customer acquisition investment. For example, credit card companies use risk-based prospect management, which assesses a prospect's credit risk prior to a credit card solicitation. Based on this assessment, the company decides whether to pursue the prospect, and makes an offer appropriate to the prospect's risk level.

Computer manufacturers such as Dell and Compaq also employ selective customer acquisition strategies based on their marketing channel models. Dell relies on a direct-sales system with no intermediaries and limited pre- and post-purchase service. (Examples of pre-purchase service include providing information about product attributes, assembling the machine once purchased, and providing training that helps novices understand how to use the software.)

In contrast, Compaq has used higher-service retailers to distribute its product. As a result, Dell is more likely to attract experienced buyers, who need less sales and service support, whereas Compaq's service offerings are more likely to attract beginners. The lesson here: Channel choice has substantial customer equity implications.

Although potentially more difficult to manage, the selective customer acquisition approach creates customer equity. Because the profiles of the acquired customers are more likely to match the firm's ideal target market, retention rates and add-on buying rates are likely to be higher. These benefits are especially critical to firms for which (a) it often costs more to acquire a customer than to retain one, and (b) the majority of the potential customer base is not very profitable.

Customer Acquisition Rules

Four rules help companies to optimize acquisition.

Rule 1: Acquire any customer as long as the discounted future value of the customer exceeds the acquisition costs for that customer.

A firm should continue to invest until it no longer can cover its investment on the last incremental customer. Most firms apply this rule's logic to capital investment strategy but not to customer investment strategy. Instead of investing in customer acquisition until the net present value (NPV) of the marginal customer falls to zero, the typical firm will underinvest, stopping with prospects whose NPV is far greater than zero. By underinvesting, the firm fails to maximize its customer equity. Rule 1 can be difficult to put into practice because many firms do not know what it costs to acquire individual customers. These firms set initial acquisition budgets with little regard for future customer value; or worse, set overall marketing budgets without linking expenditures to acquisition, retention, and add-on selling goals.

Rule 2: When you broaden the acquisition effort, be prepared for lower response rates.

This is the corollary to rule 1, and assumes that firms target their best customers first, their second-best customers second, and so on. Given this process, a firm faces diminishing response rates as it tries to acquire more customers. Following rule 1 without recognizing this principle of diminishing returns will lead to significant overspending on acquisition. A typical acquisition curve looks like figure 3-1.

Rule 3: The greater its profits from retention, the greater a firm's customer acquisition investment should be.

This may seem counterintuitive: Why should high retention profits lead us to focus more strongly on acquisition? It can be shown mathematically that the greater its retention rate or the higher its add-on selling potential, the more a firm can invest in future customers. The logic is simple: If future profits from a customer are high, then the firm can afford to lose more on its initial investment to acquire the customer. The firm therefore can increase its acquisition effort, acquiring more customers whose retention and add-on selling value can be captured.

Rule 4: The higher the percentage of the initial acquisition investment that a firm recovers in the first period, the greater its acquisition investment should be. Early returns determine the risk level of the investment. Assuming the same economic return, why not choose a lower risk? Although a discount rate can he used to adjust for risk, most managers prefer faster payoff investments because of the uncertainty of the future.

Rules 3 and 4 lead to the four acquisition strategies shown in figure 3-2 and described in the following list.

* Full Throttle: High retention-profit potential combined with short-term investment recovery makes new customer acquisition a major opportunity. The firm invests as much as possible in acquisition until the NPV of the marginal customer is negative. The risk of this strategy is low, and its return is high.

* Slingshot: High retention-profit potential combined with a long investment recovery time calls for a slingshot strategy, so named because the more invested in acquisition, the greater the future payout. The long time until payout--initial investment is very high relative to first-year returns--makes the investment risky. The firm must bet on a high NPV driven by high retention profits. A slingshot strategy is typical of the customer-investment environment among Internet companies. Many e-tailers invested heavily in acquisition spending without recognizing the risk associated with lower-than-expected retention profits.

* Pay As You Go: This strategy is most appropriate when retention-profit potential is low and acquisition-investment recovery time is short. (Most of the investment recovery occurs during the first period.) The firm invests as though all profits will accrue in the current period. Short-term profit goals drive the firm's investment.

* Divest/Restructure: In this situation, a firm must restructure its marketing system. Customer acquisition will not pay out because the initial payback is low and retention and add-on sales are low. The firm will not be profitable in the long run, and it will have very low customer equity.

Targeting: The American Express (U.K.) Membership Rewards Program

The American Express Membership Rewards program provides points to American Express Cardmembers for money they spend using the card. These points can be used to buy products and services such as airline tickets, sporting equipment, and electronics. When the Rewards program attempts to acquire new customers it has an enormous asset at its disposal: intimate details of its target market. Only Cardmembers can join the Rewards program, so the target market is clearly defined and very well known. American Express maintains detailed records on its Cardmembers, keeping track of their financial status and spending habits.

In 1996, the U.K. Rewards program had 1.5 million customers. It had achieved a 35 percent penetration rate of the overall Cardmember base. However, that penetration level had peaked, and acquisition efforts were beginning to deliver diminishing returns. Attrition was increasing because members who had received their first year free were now being asked to pay a [pounds stealing]20 membership fee. The Rewards managers decided that they needed to embark on a new acquisition strategy, based on two approaches: profiling of existing customers to identify the characteristics of high-potential prospects, and research on non-acquired prospects to determine whether different acquisition products or approaches were needed.

To use existing customer profiling, they built a model that predicted two things. First, the model predicted which Cardmembers were most likely to agree to become Rewards members by looking at characteristics of the existing members and correlating these characteristics with those of the Cardmembers who were not yet Rewards members. Second, the model predicted which cardholders would also increase their use of the card if they became Rewards members. Those Cardmembers who fit both profiles became the targets of a telemarketing effort. In particular, the model segmented Cardmembers into deciles, analysis of which led to several conclusions:

* Acquiring prospects from the first three deciles would be the most profitable because they were the most likely to convert and to increase use of the card.

* Members from the next three deciles (4 through 6) would allow reasonable profitability.

* The program would break even or lose money over the life cycles of members from the members of the remainder of the deciles.

Based on the model, the team focused its marketing efforts on the first six deciles and did not invest in trying to convert the others.

In the second initiative, focus groups from among non-acquired prospects (American Express Cardmembers who were not also Rewards members) uncovered the following information:

* Although in general the prospects thought that the program was good, they felt it was not for them because its focus was on travel.

* They did not want to pay a membership fee.

* They found the rewards to be distant because too many points were required to qualify for awards.

* Based on these data, the team concluded that the Rewards program in its current state would never attract these customers.

To change this, program managers did the following:

* Targeted more local partners for the reward program. The local partnerships-- restaurants, theaters, and other retail establishments--would increase the accessibility of benefits, particularly for those who seldom traveled.

* Devised a tiered program, adding a new tier to the program that had no annual fee but paid out award points at a lower rate per pound spent. The new program, Rewards Essential, both served as an acquisition product for customers who could later trade up to the original program, and, with its lower cost to American Express, matched the cost of the Rewards program with the customer equity value of the acquired customers.

Both initiatives led to increases in customer equity for both American Express and the Rewards program. The Rewards program successfully segmented its market and developed separate products for each segment. In addition, the program carefully targeted only those members of the segment who would most enhance customer equity if they decided to join--that is, the members who were likely to (and had the financial wherewithal to) increase their overall card usage the most.

Customer Acquisition Tactics: The ACTMAN Model

Targeting, the most common focus of acquisition tactics, is only one part of managing acquisition. In this section we outline a model called ACTMAN, an acronym for acquisition tactical management. The ACTMAN model distills the acquisition process into six critical elements that a firm can manage for more efficient and effective customer acquisition. These elements are as follows:

1. Targeting

2. Awareness generation and product positioning

3. Acquisition pricing

4. Trial

5. Usage experience and satisfaction

6. Postintroductory pricing and the creation of long-term value for the product or service

Figure 3-3 illustrates the ACTMAN model, which is described briefly in the following subsections. A more detailed description of the model and its application, including example calculations, is available online at www.customerequity.com.

Targeting

A firm should target both those customers who recognize that they have a need or desire for the firm's offerings as well as those who have not yet identified their needs or desires but who could benefit from the firm's offerings. This latter group may be more difficult to acquire because the firm will have to aid their need recognition using vehicles such as suggestive advertising or sampling.

Three methods exist for targeting customers: individual-customer targeting (first-degree targeting); segmented targeting (second-degree targeting); and self-selection targeting (third-degree targeting), which relies on the customer to identify himself or herself by responding to the firm's offers. First-degree targeting is the most desirable, but in some industries it is difficult to employ cost-effectively.

First-Degree Targeting

The two commonly used first-degree targeting methods are profiling and regression scoring. Both methods depend on the availability of demographic, behavioral, or psychographic data on potential customers that a company then matches with prospects' likelihood to buy or with their potential customer equity value. Once the characteristics of high-value prospects have been identified, the most attractive prospective customers can then be targeted and solicited.

Second-Degree Targeting

Second-degree targeting utilizes segment data rather than individual data, and should be used when individual customer or prospect data are unavailable.

Sometimes a firm can classify prospects and customers into segments for which data (often readily available governmental data) already exist. Many consumer-product firms, for example, develop lifestyle clusters based on geodemographic census tract data from the U.S. Census Bureau. They then analyze these clusters to determine which best match current customer profiles.

Second-degree targeting, like first-degree targeting, uses statistical models. An example: General Seed, a direct marketer of floral seeds, had demographic data for each U.S. ZIP Code. It also knew the number of mailings and the response rate (the number of customers acquired each year) for each ZIP Code. Using standard regression techniques, the model predicted the ZIP Code response rates as a function of demographic and climatological variables. The firm then determined the economic cutoff level above which a ZIP Code--that is, all the people in it-- should receive a mailing.

Third-Degree Targeting

Even when customer data are not available at either the individual or segment level, a firm can use targeting techniques. In these cases, targeting must be accomplished through marketing programs. This is called self-selection or third-degree targeting.

In self-selection targeting, a firm makes a marketing offer, such as introductory pricing or a promotional incentive, designed to cause certain desirable types of customers to respond. For this approach to succeed, a firm must be able to determine whether a specific promotion, price, or product can attract the desired prospects. The channel chosen to convey the offer will also affect who responds.

Targeting Summary

The most efficient targeting method is individual scoring, which allows a firm to select customers to be targeted based on their economic payout to the firm. Segment-based models are less efficient, but are better than nondatabase (self-selection) targeting methods as long as the predictive power of the models is strong enough to differentiate between segments.

Whenever possible, companies should do their targeting at the level of individual customers. If in doubt, do a quick calculation of the cost of more focused solicitation versus the customer equity value of customers missed and gained as a result--you'll likely be convinced.

Awareness Generation and Positioning

Once a firm has identified its target customers, it must make sure that they are aware of its product or service. After all, a prospect cannot try a product until he or she knows it exists. There are many tactics a firm can use to generate awareness. Direct marketing communication can combine awareness generation with product offers for trial, and is the method of choice when first-degree targeting is used. Mass communication is a less expensive mechanism for generating broad awareness in second- and third-degree targeting environments, or where the value of an acquired customer is relatively low.

For example, many Internet companies use mass communications (television, radio, billboards, print) to generate awareness and to invite customers to log on to their Web sites to learn more about products and services. These companies have learned that awareness generation through direct communications, even through portals and other Web services such as AOL, tends to push acquisition costs too high. Instead, these companies use lower-cost vehicles for awareness generation and more targeted communications for customers once they have responded. This is where positioning comes in.

According to Philip Kotler, "Positioning is the act of designing the company's offering and image so that they occupy a meaningful and distinct competitive position in the target customers' minds." (5) Positioning is critical to new customer development because it defines customer expectations about the product experience, and it determines whether customers will try a product or not.

In order for a product or service to be included in the customer consideration set, the firm must manage the critical steps of proper awareness building and positioning while the customers are in the information-gathering stage of their purchase decision-making process. Firms also need to remember that if positioning and awareness-generation efforts promise too much, then customers may try the product, but retention rates will fall short as a result of customer dissatisfaction. A firm must carefully balance its initial positioning against the product's ability to deliver the promised benefits, or risk destroying the potential customer equity from retention and add-on selling.

Acquisition is an important part of marketing, but not the only part--linkages across acquisition, retention, and add-on selling are crucial for companies that want to maximize customer equity.

Acquisition Pricing

As customers accumulate product information and begin to evaluate their alternatives, pricing becomes a factor. The general trend in customer-oriented pricing is to price low to acquire customers and to raise prices later. This tactic, known as penetration pricing, works in many situations. The biggest challenge for a firm that chooses penetration pricing lies in determining the most effective introductory price level. Guidelines exist on how to set introductory prices under various circumstances, assuming that a firm can tailor its prices by customer segment. (6)

For example, introductory prices should decline as a segment's maximum retention potential goes up. As a corollary, the more responsive a group is to retention marketing expenditures, the lower its introductory price should be. Introductory prices should be higher for groups that become more price sensitive over time, because a firm ultimately will have to lower prices to retain them as customers. The higher introductory price will compensate for this future decrease in revenue. (Among the customers who fall into this category are those who typically buy only on promotion.) Higher introductory prices also make sense for many evolving markets, in which more purchase options will likely become available, leading to increased customer price sensitivity over time.

A special category of customer acquisition is reacquisition of lapsed or lost customers. In this instance, it is almost always possible to use existing purchase data to estimate customer asset value with confidence. As a result, firms can set "winback" prices that are below those offered to other acquisition targets in recognition of the high asset value of the reacquired customers. Companies should be cautious, though: It is very easy to get into a reacquisition war, as long-distance telephony providers did when they used teaser rates and other price-based promotions to acquire switching-prone customers from each other, over and over again, at tremendous cost. The flaw, of course, was in incorrect assumptions about how long reacquired customers would stay, and the risk of "re-loss."

Retention Pricing

It may seem strange that retention pricing is a consideration of acquisition management. However, if one recalls that customer acquisition is a process that continues beyond the actual purchase, and that post-purchase behavior is the final stage of the customer purchase-decision model, then the relevance of retention pricing to acquisition becomes clear. In order for customers to leave the acquisition phase and move into the repeat-purchase phase of the customer life cycle, they must reach an acceptable level of satisfaction with the product experience, and expectations about future experiences must be attractive. Assessing the attractiveness of future experiences involves some consideration of future pricing.

Acquisition pricing can greatly influence expectations about retention pricing. The acquisition price acts as a reference price for customers in their assessment of future prices. If the retention price is too high relative to this reference price, customers are less likely to repurchase the product or service. As a result, pricing strategy must include how a firm will manage the change in price between acquisition and retention. If a very low acquisition price attracts prospects who would not otherwise try the product, then charging a significantly higher retention price will cost the firm a large number of first-time buyers. That does not necessarily invalidate this strategy, but a firm must understand the complete financial implications of this pricing strategy and the fact that the quality of the product may not suffice in keeping these types of customers on board. In general, firms should avoid acquisition pricing tactics that create price expectations that retention pricing cannot meet.

One way to manage reference prices is to use special promotions that signal one-time price discounts off regular prices. Another way is to list long-run prices along with the special introductory prices in price communications. The danger remains, however, that once a price goes up from the low introductory price, the customer will not feel that the product provides a value above his or her threshold.

Trial

Many firms identify product trial as a key strategic objective. It marks the point at which customers move from evaluating alternatives to actually making purchases, and it is often the first signal of interest that customers communicate to the firm. From a firm's perspective, the goal of the trial stage, besides generating revenue, is to demonstrate to customers that the firm's product or service can meet their needs.

Firms commonly use price discounts or free offers as mechanisms to induce trial. Although such tactics may prove successful at initiating a first usage, it is important to manage them carefully, both because customer expectations still are being established during the trial stage and because at the time of first usage, the customer may not have committed to repurchasing the product. If product expectations are very high as a result of initial selling communications, and if the product fails to meet these expectations, the customer probably will not repeat-purchase, and the lifetime value of that customer will likely be low or even negative.

It is at this stage that product strategy begins to play a role in customer equity creation. Companies should manage their product portfolios to include acquisition products-those that are appealing to customers early in their buying life cycles. Sloan's brand ladder at GM from Chevrolet to Cadillac is one example; other examples of acquisition products include demand deposit accounts at banks and books at Amazon.com.

Usage Experience and Satisfaction

In addition to marketing communications, which play a key role in establishing customer expectations, two other critical activities significantly influence the customer's product usage experience and satisfaction:

* Product design and the provision of specified benefits

* Postpurchase servicing of the customer

The firm's ability to meet expectations depends on its research and development team, which manages product or service design; its operational staff, which controls production and delivery; and its customer service team, which manages postpurchase servicing. It is important that each of these teams be aware of its role in customer management and the development of customer equity. If any one of these areas of the firm does not deliver on its responsibilities, the customer is unlikely to be satisfied. Even if the product or service is clearly superior to any other on the market, if expectations go unfulfilled, then the customer will be disappointed and less likely to repeat-purchase.

The U.S. Armed Forces and Acquisition

For the U.S. Armed Forces (Army, Navy, Air Force, Coast Guard, and Marines), the job of acquiring "customers"--the men and women who enlist for active duty--has become increasingly challenging over the past few years. Because of the robust economy and absence of a compelling, specific military mission such as defeating communism, fewer young people are choosing to enlist in the military. Yet, to survive at its current size, the military must recruit 200,000 new members each year.

To replace (recruit, train, and equip) an Armed Forces' member who leaves prematurely costs taxpayers more than $35,000. Given the high replacement cost, military recruiters concluded that the retention potential of a recruit is a substantial consideration in their acquisition strategy.

Although the Armed Forces is a somewhat atypical "customer" setting, many ACTMAN elements still apply.

Targeting

According to the Department of Defense, marketing research and experience indicate that the most successful recruits-those who are best able to adapt to military life and become long-term service people--are high school graduates who score at or above the fiftieth percentile of the Armed Forces Qualification Test.

Currently, 93 percent of the active duty enlisted personnel (not including officers) are high school graduates with no college degrees (figure 3-4). Based on these findings, along with the age limit and physical requirements, the Armed Forces identified their first-tier targets as people aged seventeen to twenty-four years who are soon-to-be or recent high school graduates.

Awareness Generation

Given the increased options for their potential recruits, the Armed Forces have initiated aggressive campaigns to increase awareness among its target audience. Campaign efforts include billboard advertisements, direct mailing, and cold calls to identified candidates.

The Air Force launched a $28 million ad campaign that is being broadcast on movie screens and during prime time programs such as Monday Night Football, NBA games, and television dramas popular with the targeted age group, such as Buffy the Vampire Slayer and Dawson's Creek.

As a joint recruitment effort, the Armed Services created eight new television ads, with spots on ESPN, MTV, TNN, and other stations frequently viewed by young adults. The new ads utilized MTV-style special effects, with live-action footage shot at various U.S. military installations.

Recruiting offices are also on the move, away from downtown storefronts and into malls with high youth foot traffic. And "acquisition pricing" is being used, with inducements such as double signing bonuses and shorter mandatory commitments being offered to spur enlistment of members of the targeted prospect audience.

Trial

In selected high schools throughout the country, students are able to participate in the Junior Reserve Officer Training Corps (JROTC). JROTC is a set of noncompulsory high school classes that teach military principles. Service men and women teach these classes. Student participants are required to go through simulated basic training, wear uniforms, and are given military-like ranks. Based on their experience, some JROTC students sign up for active duty after graduation, whereas others attend college on ROTC scholarships. Scholarship winners promise to serve in active duty after graduation. Participants in the JROTC are able to exit the program, without consequences, at any time.

Usage Experience and Satisfaction

For the military, as with companies, meeting "customer" expectations is important to retention and thus key to the acquisition process. The branches of the Armed Forces are designed with several customer service and operational divisions in order to facilitate the transition to military life and increase personnel satisfaction. These divisions handle issues ranging from day care to career counseling to religious concerns. Personnel satisfaction is high in areas such as career opportunities (including tuition reimbursement) and benefits (travel, medical, and housing). Finally, in most cases the military is able to satisfactorily meet and manage expectations because of its clear guidelines.

In the last 10 years each branch of the Armed Forces has had a difficult time meeting recruitment numbers. However, in 2000 the Department of Defense reported that enlistment is increasing among its target group. In fact, by mid 2000, the Air Force had already met its recruitment target and others were expected to follow.

* Methods and Tools for Acquisition

In this chapter on retention, add-on selling, and optimizing the customer equity strategy, we will provide brief descriptions of the tools and tactics that companies can use. We will discuss:

* Databases and data sources

* Metrics and accounting

* Data analysis tools

A detailed examination of these areas is beyond the scope of this book and its intended audience; however, detailed descriptions, including formulas, example calculations, and data displays, are available online at www.customerequity.com.

Prospect Databases

Databases and Data Sources for Acquisition

Prospects are not customers, and the firm needs to use different marketing tactics to affect their behavior. Therefore, companies should separate prospect databases from customer databases. Prospect data fall into two categories: historical marketing data and profile data.

Historical marketing data track marketing activity by individual prospect. These data include the prospect source, each marketing contact, and the response to each marketing contact. Table 3-1 gives examples of recommended historical marketing data.

Customer Profile Databases

Profiling customers (or prospects) is the process of obtaining detailed information about them. This information can range from demographic data (such as family size) to personal data (such as hobbies). The results of profiling help a firm to determine the best messages to convey, products to target, and communications to avoid. They can reduce costs by helping a firm to target new or existing customers for add-on selling more efficiently. In short, they are an important part of customer equity management.

There are six main categories of profile data:

1. Customer sales potential

2. Customer characteristics (such as demographic, lifestyle, and industry classification data)

3. Summary customer equity measures

4. Organizational charts and key personnel (business-to-business)

5. Influencers and specifiers

6. Customer attitudes

Table 3-2 lists types of profile data with their sources.

Sales potential is one of the most valuable elements of the customer or prospect profile. This data element includes the customer's potential sales volume, not just actual purchases. Analysts compute potential in different ways, depending on the market under consideration. For example, credit card companies often use information about outstanding balances from all the credit cards of a cardholder. (They obtain these data from credit bureaus.) This information provides insight into the customer's profit potential. Industrial or business-to-business firms often use firm size and industry type as surrogates for sales potential. Firms can obtain estimates of customer potential from industry trade associations or third parties.

A profile database also must contain demographic data. For consumer products, these data usually also include lifestyle information. Industrial firms typically include firm size and industry classification in their demographic data. They may also include personal information about customers, organizational charts, and other pertinent details.

Attitudinal data are important because they indicate how a customer evaluates the firm. For example, retained customers (such as airline passengers) may nonetheless have negative attitudes about the products or services that they use. These vulnerable customers are more likely to defect, so firms need to take steps to affect their attitudes. Databases that contain attitudinal data help firms to identify these customers and to design marketing programs aimed at affecting their attitudes. Historically, few firms tracked attitudinal data because of the cost and difficulty of collecting such data. However, with the advent of the Internet, the cost of customer surveys has declined and will continue to do so.

Causal Marketing Databases

Causal marketing databases capture data on the marketing programs offered to individual prospects and customers. They are extremely complex to create, because firms rarely track marketing activities at the individual-customer level. However, they are also extremely valuable, because the information they contain can significantly improve marketing efficiency and effectiveness. By knowing the cost of and responses to various marketing activities, companies can determine which pay out and which are unprofitable.

For example, companies can use targeting models developed from causal data to identify which customers should receive specific marketing communications. Years ago, Time Life Books sent mailings for a book series to its entire customer base. The company then realized that it could target its mailings, which greatly reduced overall mailing costs without significantly reducing overall response. To do this, Time Life developed sophisticated targeting models. It sent sample mailings to the customer base, tracked marketing offers and responses by customer, and then scored customers according to their responses. In subsequent mailings, Time Life targeted those customers whose scores indicated they were likely buyers.

A business-to-business firm applied a similar approach. It tracked all sales force activity and found that it should greatly reduce direct sales calls on a large set of its prospect and customer base because the expected revenue from these customers could not cover the cost of the calls. The firm put in place a sophisticated two-tiered marketing system, which substituted phone calls for a large number of the sales calls. The company found that response did not drop; in many circumstances the customer actually preferred the phone call to an hour spent with a salesperson.

Table 3-3 lists recommended elements of a causal marketing database. To track these data, companies need the ability to match marketing activities to customers (or prospects, as the case may be), and in many cases must have disciplined sales forces that are willing to complete sales call reports. Firms unwilling to commit to tracking information about marketing activities are at a disadvantage. Savvier firms recognize that investments in these efforts pay off in improved efficiency.

Measuring and Accounting for Acquisition

A simple way of thinking about customer equity is that it is the sum of acquisition equity (the value of the customer up to the point of repeat purchase), retention equity, and add-on selling equity. This chapter discusses acquisition equity.

Computing Acquisition Equity

Computing acquisition equity is usually straightforward (the difficulty arises in obtaining the data to make the computations), and consists of six steps:

1. Determine the number of prospects contacted over a fixed time period from a completed acquisition campaign.

2. Measure the marketing and servicing costs associated with contacting and selling to the prospects.

3. Determine the number of prospects who became customers.

4. Compute the sales revenue and gross margin for the new customers' first set of purchases.

5. Compute the acquisition equity of the entire pool of customers by subtracting the costs calculated in step 2 from the revenues calculated in step 4. Note that this equity number can be negative.

6. Divide the total acquisition equity by the number of customers to determine the average acquisition equity per customer.

Computing acquisition equity sets the stage for using customer equity data in a company's accounting system.

Acquisition Metrics

Top management is often surprised by the high cost of customer acquisition. How can companies determine what acquisition expenditures make sense? Basic knowledge of acquisition costs, initial profit-to-cost ratios, and new-customer investment statistics provides management with a better understanding. As these measures become more widely used, firms can benchmark against other firms in similar industries. Ultimately, these and other customer equity metrics can, and we believe should, become part of firms' financial reporting as companies truly begin to manage customers as they manage other valuable financial assets.

Critical summary statistics for acquisition include the following:

* Number of customers acquired, which can be tracked over time and matched to a company's acquisition goals.

* Acquisition rate, which is the ratio of acquired customers to targeted prospects. This statistic measures both targeting and solicitation effectiveness. It can be broken down further to assess success rates with different groups of prospects.

* Cost of acquiring a customer, which can be matched to customers' retention and add-on selling values, and which also influences how aggressively companies should expand their acquisition expenses.

* Total new-customer investment, which allows a company to compare its investment in creating customer assets with its investments in capital equipment, product development, and research.

* The ratio of acquisition cost to acquisition equity, which shows how much of its acquisition investment a company recovers in the first period. High-recovery situations, as noted earlier, reduce the risk of increased spending on customer acquisition.

* Total new-customer investment as a percentage of sales and profits. These percentages are critical measures because they show whether a firm is investing in new-customer acquisition at the same level as in prior periods or simply is milking existing customers for profitability.

Another critical measure is the net present value of a new customer. Once acquired, a new customer has a future value, which equals the sum of all future purchases minus the cost of goods sold and future marketing expenses. Firms must understand the future value of acquired customers so that they can determine whether investing in new customers is profitable. If it is not profitable, the firm must change its acquisition approach.

To increase total customer equity when the NPV per customer declines, it is necessary to increase, not decrease, the investment in new customers. There is a limit to this increased investment, however. The per-customer acquisition cost must not exceed the marginal NPV for the "last" customer acquired. As long as the firm acquires customers with NPVs greater than acquisition costs, the firm should be willing to increase its customer acquisition investment. Otherwise, the long-term value of its customer base will decline.

Data Analysis Tools for Acquisition

In this chapter, we provide brief summaries of analysis tools for converting customer data into insights for acquisition, retention, and add-on selling.

Customer-focused data can be used, among other things, to do the following:

* Identify target customer segments

* Determine customer acquisition rates

* Determine customer retention and defection rates

* Identify opportunities for add-on selling

* Understand and evaluate consumer responsiveness to marketing programs

* Track and analyze customer buying patterns

* Measure the economic value of the customer

* Forecast and manage future customer behavior

* Develop more effective customer-focused strategies

In this section, we present two techniques that can be used to target new customers for acquisition: profiling and regression scoring. A comparison of the strengths and weaknesses of each of these techniques is shown in table 3-4.

Profiling

The simplest way to determine how to target new customers is to profile existing ones. In profiling, a firm identifies the characteristics of its best current customers and then targets noncustomers with similar characteristics. These "non-customers" can be first-time purchasers from the firm or individuals who have purchased from other divisions of the firm.

An Example of Profiling. To identify prospects for acquisition targeting, an analgesics retailer began by obtaining demographic data at the individual-customer level. The company compared heavy users and category purchasers with noncustomer users. Table 3-5 shows the distribution of its customers across various demographic variables; the first column reflects the percentage of the general population represented by that demographic type (drawn from government statistics and prior marketing studies).

The second column, the profiling index, represents the fraction of the firm's customers that fit into that demographic type relative to the total number of potential analgesic customers in the general population. An index of 100 is average; less than 100 means that the firm has fewer than the average number of customers who match that demographic category. With these data, the retailer now can target nonbuyers who fit the profile with mailings, coupons, and samples.

Business-to-business marketers can use the same targeting technique. (The profiling data likely will come from sources, such as Dun & Bradstreet, that are different from those tapped by consumer companies.)

How to Profile. A relatively simple form of profiling is "best customer" profiling. Steps include the following:

1. Collect demographic and profitability information about current customers.

2. Append this information to each customer's record in a profiling database.

3. Add behavioral data (such as sales histories) and psychographic data to each profile.

4. Determine which variables distinguish the best customers, worst customers, and non-responders.

5. Use these variables to identify the highest-potential prospects.

Indexing, another form of profiling, compares the general population of a product's consumers with the firm's existing customers for that product. To index:

1. Partition customers in the database using several demographic variables.

2. Determine the number of buyers that fall into each partition. (7)

The index for each partition reflects the ratio of the number of the firm's customers in that partition to the total number of the buyers in general population that fit that partition

In its simplest form, this index shows for which demographic categories a firm has more than the expected number of customers and for which it has fewer. Those partitions that have significantly higher indices indicate customer segments that the firm has effectively targeted and acquired. Partitions with lower indices represent those segments that the firm acquires less effectively.

Advantages and Disadvantages of Profiling. Almost any firm that has a customer database can easily profile. However, when profiling, analysts must remember that the firm's targeting strategy can influence the characteristics of its customer base. Put another way, it should not be surprising when a company that has been targeting a specific audience finds, through profiling, that its customers come from that audience. As a result, the firm's profiling risks overlooking other valuable segments of potential customers.

Analysts should also interpret profiling indices with caution. Some segments may have high targeting potential but not appear frequently in the database; therefore, profiling will not identify them as attractive targets. Also, a firm should assess the potential customer equity of each partition before using a profiling technique to target new customers. A segment with a low index may actually be a very high asset value segment that the firm's acquisition strategy underemphasizes. Finally, profiling does not include the statistical analyses needed to assess the strength of various characteristics as predictors. It tells analysts the characteristics of the firm's best customers, but not which characteristics are the most powerful identifiers of potential "best" customers.

Regression Scoring

Companies can also use regression scoring, a more difficult but more accurate technique than profiling, to target new customers.

An Example of Regression Scoring. Contract Stationers, Inc. (a disguised example) sells office supplies to businesses. Because making sales calls on every prospect costs too much, management decided to target specific prospects instead. The firm obtained a targeted prospect list of firm names and individuals from various publications and list sources, such as Dun & Bradstreet.

Using these data, the firm made a series of sales calls on a randomly selected set of prospects and then noted who responded, added customer characteristic data to each prospect's record, and ran a scoring model to determine which characteristics generated the highest likelihood of response. The resulting variables and weights appear in table 3-6, along with the scores computed for 10 prospects.

The firm aggregated the prospects' scores into decile groups. (Scores also can be grouped into smaller sets, such as 5 percent groupings, if researchers prefer.) The firm then calculated the likelihood of purchasing for each decile group. Table 3-7 shows a typical decile table, with score ranges and buying probabilities.

The firm determined the cutoff score by computing a break-even customer equity value, which was based on buying probabilities, marketing costs, and long-term expected sales to the customers.

By using regression scoring, this firm improved its acquisition efficiency and avoided sales calls on prospects with negative long-term value. It targeted only customers whose projected customer equity was positive and thereby increased its total customer equity by a substantial amount.

How to Perform Scoring. As suggested by the example, regression scoring steps include the following:

(1.) Draw a random sample from the overall population of prospective customers.

(2.) Obtain data from the sample that profile individual consumer characteristics.

(3.) Initiate a marketing campaign directed at the random sample, and record which individuals become customers.

(4.) With that information, develop a regression scoring model--a series of weighted variables that predicts which prospects are more likely to become customers based on their characteristics.

Once researchers have the model estimates, they can do the following:

* Calculate scores for prospects who were not in the random sample by plugging their individual characteristics into the regression equation

* Rank-order prospects from highest to lowest, according to their scores

* Target the firm's marketing campaign at those prospects with scores above a designated cutoff score, which is based on a combination of financial and marketing factors

Advantages and Disadvantages of Regression Scoring. The primary advantages of using regression scoring models for acquisition are that they measure the relative importance of variables in determining which prospects to target, and they provide a scientific method for selecting cutoff values. The result is significantly increased marketing efficiency.

The primary disadvantage of regression scoring is its complexity relative to profiling. However, we recommend that firms seriously investigate implementing regression scoring, even if it requires using outside resources. Improved targeting efficiency and effectiveness usually justify the increased complexity and costs.

Summary

Managing acquisition strategies and tactics is vital to creating, sustaining, and enhancing customer equity. Acquisition should not be viewed as a secondary element in a customer equity marketing system, even in the most retention-oriented industries. Similarly, traditional marketing strategies that fail to consider acquisition's links to retention and add-on selling are also deeply flawed.

As the ACTMAN model shows us, all elements of the acquisition process--from the creation of customer expectations to postpurchase customer service--have long-term implications for the customer--firm relationship. A retention-focused firm that neglects its acquisition strategy will never maximize retention and add-on selling. By the same token, any acquisition strategy that fails to consider its long-term effects on retention and add-on selling is incomplete.

Robert C. Blattberg is a professor at Northwestern's Kellogg Graduate School of Management in Chicago, IL. Gary Getz is a managing principal at Integral, Inc. in northern California. Jacquelyn S. Thomas is a professor at Emory's Goizueta School of Business in Atlanta, GA.

(1.) Jacquelyn S. Thomas, "A Methodology Linking Customer Acquisition to Customer Retention," Journal of Marketing Research (forthcoming in 2001).

(2.) Robert Blattberg, John Deighton, and Jacquelyn Thomas, "Setting the Marketing Mix Maximizing Customer Equity," working paper, Kellog School of Management, Evanston, IL, 1998.

(3.) Sam Zuckerman, "E-Trade Loses $5.2 Million Despite Late Business Surge," San Francisco Chronicle, 20 January 2000, B2.

(4.) Tim Jackson, "AOL Merges with the Field," Financial Times, 22 December 1997,9.

(5.) Ibid.

(6.) Jacquelyn S. Thomas and Robert Blattberg, "Pricing Based on Customer Relationships," working paper, Stanford University Graduate School of Business, Stanford, CA, 1999.

(7.) If the firm does not construct completely orthogonal partitions, some buyers will be included in more than one partition. Ideally, the firm should divide the database so that a customer is a member of only one partition.

[Figure 3-1 omitted]

[Figure 3-2 omitted]

[Figure 3-3 omitted]

[Figure 3-4 Omitted]

Table 3-1

Example of Historical Marketing Data for Prospects

Data Element          Internal/External    Source
                           Source

Prospect source           Internal       Marketing
Marketing contacts        Internal       Sales force
Promotional offers        Internal       Marketing
Stage of sales cycle      Internal       Sales force
Table 3-2

Example of Customer (or Prospect) Profile Data

Data Element                Internal/External
                            Source

Customer sales              External/Internal
potential

Customer                    External/Internal
characteristics

Customer equity             Internal

Organization structure      Internal

Key influencers             Internal

Specifiers                  Internal

Competitors' products used  External/Internal

Customer's attitudes        External

Data Element                Source


Customer sales              Third party data, sales force,
potential                   marketing research

Customer                    Third party data, sales force,
characteristics             marketing research

Customer equity             Accounting, marketing research

Organization structure      Sales force, marketing research

Key influencers             Sales force, marketing research

Specifiers                  Sales force, marketing research

Competitors' products used  Sales force, marketing research

Customer's attitudes        Marketing research
Table 3-3

Example of Causal Data

Data Element               Internal/External Source  Source

Sales call per customer            Internal          Sales force
or prospect                                          call reports
Product or service offers          Internal          Marketing
Pricing to Customer                Internal          Accounting
Promotional offers                 Internal          Marketing
Table 3-4 Customer Acquisition Data Analysis Tools

Customer
Acquisition                  What It
Analysis Technique         Demonstrates

"Best customer" profiling  Characteristics of most profitable
                           customers




Profiling using indexing   Over- and underrepresentations of
                           customer types in acquired customer
                           set






Regression scoring         Drivers of acquisition value






Customer
Acquisition
Analysis Technique         Advantages

"Best customer" profiling  Simple and easy to understand

                           Almost any firm can use some form
                           of profiling, if it has a database


Profiling using indexing   Provides a comparison between the
                           general population of a product's
                           consumers and the firm's existing
                           customers for that product;
                           Identifies characteristics of
                           acquired customers



Regression scoring         Provides a scientific method for
                           selecting cutoff values

                           Measures the relative importance
                           of variables in determining which
                           prospects to target

Customer
Acquisition
Analysis Technique         Disadvantages

"Best customer" profiling  Dcpends on the firm's targeting
                           strategy
                           Has blind spots--only looks at
                           characteristics of today's
                           customers

Profiling using indexing   Slightly more complex than
                           profiling

                           Could overlook segments that have
                           higher targeting potential

                           Does not identify causal drivers of
                           customer acquisition

Regression scoring         More complicated than profiling;
                           could require outside resources
Table 3-5 Example of Profiling: Analgesics

                                          Percentage of     Profiling
Demographic Variable                    General Population    Index

Household size (HH): 1 member                   25             71
HH size: 2 members                              33             117
HH size: 3-4 members                            31             103
HH size: 5+ members                             11             105

Female HH head age: <35                         19             74
Female HH head age: 35-44                       19             97
Female HH head age: 45-54                       18             115
Female HH head age: 55+                         26             131
Female HH head age: No female HH head           18             69

HH income: <$20K                                23             96
HH income: $20-29.9K                            20             102
HH income: $30-39.9K                            14             95
HH income: $40-49.9K                            12             98
HH income: $5O-69.9K                            18             102
HH income: $70K+                                13             108

Female HH head educ: Not HS grad                6              128
Female HH head educ: HS grad                    33             120
Female HH head educ: Some college               27             101
Female HH head educ: College grad               17             84
Female HH head educ: No female HH head          18             69

HH head occupation: Professional                28             89
HH head occupation: White collar                11             89
HH head occupation: Blue collar                 28             100
HH head occupation: Not in work force           32             114
Table 3-6

Weights and Scores for Selected Prospects

                        Unweighted Values                   Weighted
                                                             Values
Customer                Firm Size   No. of    Service
Number    Constant        (000)    Employees  Sector    Constant

Weight       --              --        --       --         7
 1           1            2,438       153        0         7
 2           1               99         8        1         7
 3           1              208        27        0         7
 4           1              679        38        1         7
 5           1            1,431        45        0         7
 6           1              541        58        1         7
 7           1               65         7        0         7
 8           1              987       103        1         7
 9           1            2,431       305        1         7
10           1              354        31        0         7

                  Weighted Values
Customer  Firm Size   No. of    Service
Number      (000)    Employees  Sector    Score

Weight     0.0017      0.054      3.1      --
 1         4.1446      8.262        0     19.41
 2         0.1683      0.432      3.1     10.70
 3         0.3536      1.458        0      8.81
 4         1.1543      2.052      3.1     13.31
 5         2.4327       2.43        0     11.86
 6         0.9197      3.132      3.1     14.15
 7         0.1105      0.378        0      7.49
 8         1.6779      5.562      3.1     17.34
 9         4.1327      16.47      3.1     30.70
10         0.6018      1.674        0      9.28
Table 3-7 Decile Ranges and Probability Response

Decile               Number of  Percentage
Number  Score Range  Prospects  Responding

  10    >25.47          493       31.33
   9    20.39-25.47     493       27.42
   8    18.61-20.38     493       21.47
   7    15.18-18.60     493       18.36
   6    13.43-14.99     493       15.89
   5    12.87-13.42     493       14.11
   4    11.47-12.86     493       12.79
   3    10.51-11.46     493        9.30
   2    8.31-10.50      493        6.41
   1    <8.30           493        4.98