Net Promoter Economics: The Impact of Word of Mouth

Transcription

1 Net Promoter Economics: The Impact of Word of Mouth Exploring the Relationship Between Net Promoter and Word of Mouth in the Credit Card Industry By Vince Nowinski

2 Introduction To achieve financial success, companies must have a clear and effective growth strategy that is well executed and improved upon over time. While simply stated, long term sustainable growth is difficult to achieve. Many factors can impact financial performance, including the overall health of the economy and the competitive landscape within a particular industry factors which are often unpredictable and nearly impossible to control. What companies can control and manage are their internal strategies and processes. These factors include the quality of their goods and services, the effectiveness and efficiency of their sales and marketing efforts, and the investment they make to understand and increase the loyalty of their most strategic customers. Many businesses embrace the concept of customer loyalty. However, most struggle to find an easy, understandable way to measure loyalty and link it to meaningful financial outcomes, which can impede efforts to invest in and optimize customer experience. The promise of customer loyalty that happy customers reward companies in ways that fuel growth has been successfully established at the industry level (e.g., Heskett, Sasser & Schlesinger, 1997; Ittner & Larcker, 1998; Marsden & Upton, 2005; Reichheld, 2003). However, to date there has been little investigation of how specific customer behaviors contribute to larger financial outcomes like profitability and growth at the company level. In this paper, we will look at a specific industry segment financial services, business-to-consumer credit cards in an effort to better understand the link between customer loyalty and customer behaviors which contribute to financial success. Specifically, we will examine customer word of mouth (WOM) behaviors the naturally occurring tendency to share exceptionally positive (or negative) brand experiences with others and quantify its place in the larger economic picture that links loyalty with growth. Measuring Customer Loyalty Using Net Promoter Co-developed by Satmetrix and Fred Reichheld, Net Promoter is a discipline that provides companies a proven approach for measuring and improving customer loyalty. The Net Promoter Score compares the number of Promoters (those who are highly likely to recommend a company and/or its products) to the number of Detractors (those who are unlikely to recommend a company and/or products) within an organization s customer universe, resulting in a single metric that serves as an accurate indicator of customer loyalty and long-term growth. 1 With its elegant simplicity and its growing body of supporting research, Net Promoter is quickly gaining widespread industry adoption. Companies like Apple, General Electric, Charles Schwab, Intuit and other world-class firms are embracing the concept of Net Promoter and have successfully implemented Net Promoter programs within their organizations. This swell of industry uptake is clearly articulated by Forrester Chairman and CEO, George F. Colony, who observes that Net Promoter is becoming a driving force within organizations. (Forrester Marketing Forum, 2007) The Economics of Net Promoter Through ongoing research and application, the link between Net Promoter and financial success continues to garner acceptance and credibility. But acknowledging this link and explaining it are two different matters. To better understand the relationship between Net Promoter and financial outcomes, Satmetrix has undertaken its own independent research examining the link between customer loyalty and specific customer behaviors. Through this research, we are able to gain a better understanding of just how Net Promoter functions as a predictor and driver of economic success.

3 The Net Promoter WOM Economic Framework presented in Figure 1-1 suggests why Net Promoter has proven to be such a powerful indicator of financial success. While it is based on a customer s stated likelihood to recommend a company to friends or colleagues, Net Promoter is not solely a measure of referral behavior alone. Figure 1-1. Net Promoter WOM Economic Framework The foundation for the Net Promoter Score starts with the very first interaction a customer has with a particular company and builds with each subsequent encounter. Collectively, these experiences shape the degree of loyalty a customer feels towards the company. If a customer enjoys highly positive experiences, he or she will feel more loyal the most loyal customers are identified as Promoters, the least, Detractors, and those in between as Passives. Customer loyalty can manifest itself in multiple ways. For the purpose of our research, we focused on the two behaviors most commonly linked with profitability and growth: buying and referral behaviors. Buyer economics capture the value of individual purchase behaviors how much a customer spends with the company over a given period of time. Referral economics capture the amount of new business that is gained or lost as a function of the messages that individual customers share via word of mouth. When customer experiences are positive and loyalty is high we expect customers to spend more on average and to generate new business via positive word of mouth. Conversely, when customer experience is poor and loyalty is low, we expect lower purchasing value (perhaps even defection), as well as the potential loss of new business through negative word of mouth. The Net Promoter WOM Economic Framework helps to illustrate the utility of the Net Promoter Score as an indicator of customer behaviors which have a critical impact on a company s current and future business performance. While identifying Promoters and Detractors is useful in its own right, it is important to understand how these customers impact the bottom line through their buying and referral behaviors. The remainder of this paper quantifies the relationship between Net Promoter and these customer behaviors. We applied the Net Promoter WOM Economic Framework to the business-to-consumer (B2C) credit card industry, linking Net Promoter to financial worth through the buying and referral economics of Promoters and Detractors. As an illustration of the benefits of loyalty leadership, we will highlight a significant success story within the industry, as well as offer a detailed discussion of results and implications for real-life application.

4 Methodology Data Collection The data used for this study was drawn from the Satmetrix Net Promoter Benchmark Database an ongoing, opt-in benchmarking effort that collects primarily U.S.-based data for 2 markets, 4 industries and 14 segments as shown in the list below: Net Promoter Benchmark Database: Markets o o Business to Business Business to Consumer Industries o Financial Services o High Technology o Internet o Telecommunications Segments o Financial Services Banking, Brokerage/Equities, Credit Card o High Technology Hardware, Software/ASP, Networking and Peripherals o Internet Ecommerce, Web Information Services, ISP o Telecommunications General, Cable, Cell Phone, Local/Long Distance Phone, Telecom Equipment Providers Opt-in respondents self-select the industry and company they wish to rate. For example, a customer might first elect to rate a company that provides Financial Services, further specify the credit card segment, and then choose to rate their American Express card (or another card they hold) specifically. Key metrics include Net Promoter, other industry standard loyalty measures, selfreported spend and referral behaviors, as well as various company performance attributes, such as satisfaction with overall product, value, reputation, and ease of doing business. Consisting of almost 285,000 responses collected over a period of seven years, the Net Promoter Benchmark Database is a rich data source that provides industry reporting and analysis within a competitive context.

5 Analysis Using the Net Promoter methodology, we first identified and segmented respondents into Promoter and Detractor categories based on their likelihood to recommend. We then set out to quantify the worth of Promoters and Detractors alike by isolating the contribution of buyer and referral economics to total customer worth for each. Using self-reported data, we calculated the buyer economics of Promoters and Detractors based on their average annual spend amounts. As shown in Figure 2-1, our first hypothesis is that Promoters will tend to spend more, whereas Detractors will tend to spend less relative to the average customer. While this may not be universally true the nature of the business and pricing structure may constrain incremental purchasing differences in some businesses we would expect a difference where customers are freer to express their loyalty with their wallet. Figure 2-1. Calculating Total Customer Worth We also hypothesize that the total customer worth of Promoters will be augmented by new business generated through their positive referral behaviors an indirect, but nonetheless real impact of strong customer loyalty. Conversely, we expect that the total worth of Detractors will drop due to lost opportunity costs resulting from their negative referral behaviors. To estimate the referral economics of Promoters, we first multiplied the percentage of Promoters who had made a positive referral in the past 12 months by the average number of positive referrals issued by Promoters. We then multiplied this product by an overall conversion rate to arrive at the number of customers generated per Promoter. 2 Once we calculated the number of customers acquired per Promoter, we multiplied this estimate by the average spend across all customers to arrive at the dollar impact of positive referrals.

6 Figure 2-2. Calculating Referral Economics for Promoters Figure 2-3. Calculating Referral Economics for Detractors We used a similar approach for calculating the referral economics of Detractors. Obtaining the conversion rate for Detractors, however, required an additional inference, as it is not possible to determine the actual number of customers who would be current customers of a vendor save for the impact of negative word of mouth. To estimate that conversion rate, i.e., the number of potential customers exposed to negative word of mouth who seek other providers as a result, we reviewed the limited available literature regarding the impact of negative word of mouth. Based on this literature review and the findings of several industry studies, we operationalized the negative conversion rate as 4 times that of our calculated positive conversion rate. 3

7 Results: Credit Card Providers Industry Overview The credit card industry is one segment within the larger financial services industry. It is dominated by six players (American Express, Bank of America, Capital One, Citigroup, Discover & JPMorgan Chase) who collectively own about 80 percent of the market. The overall growth rate of the credit card industry has slowed in recent years. Its growth is impacted by the state of the overall economy (which in turn impacts the willingness of consumers to purchase goods on credit and their ability to repay), domestic legislation (such as that impacting financial procedures like bankruptcy), as well as variations of the Federal Funds Rate and London Interbank Offered Rate (Wang, 2006). Given that all companies in this space must deal with these macroeconomic forces, the extent to which a credit card issuing organization is successful relative to its competitors depends on how successfully it can maximize customer spending, repayment, and tenure. This last factor cannot be understated; credit card companies must retain a customer for at least 6 years to insure a profitable relationship given acquisition and support costs (Heskett et al., 1994). Many credit card issuers use promotional offers to motivate customers to bring more business to them. For instance, customers are typically enticed by the ability to transfer balances from one provider to the next under a better interest rate; this segment of customers typically view their credit card options from a cost or commodity perspective. Another segment of customers is less "transaction-oriented" and more relationship oriented, choosing to do more business with their preferred provider. Particularly for the latter group of customers, loyalty may be obtained through superior value and service. Net Promoter Performance The Net Promoter Score (NPS) for the overall consumer credit card industry in 2007 was 15%, with 43% Promoters, 28% Passives, and 29% Detractors (percentages rounded to nearest whole number). While this trails the larger financial services industry score in the Satmetrix benchmark (comprised of credit card, as well as retail banking and brokerage/equities firms) at 18% overall, it represents a steady and meaningful improvement for the credit card segment, particularly relative to its historic low NPS of 8.5% in Overall, the pattern of change in NPS within the credit card industry closely mirrors trends for the larger financial services industry. Figure B2C Credit Card Providers Net Promoter Performance and 5 Year Trend vs. Overall B2C Financial Services

8 Net Promoter and Buyer Economics The Net Promoter segments for credit card holders map in expected fashion to their self-reported spend; average spend amounts were highest among Promoters, and lowest among Detractors. Across all respondents, the average amount spent reported for the prior year was $17,319. By comparison, Promoters spent nearly $2,500 more, while Detractors spent approximately $3,400 less. Figure 3-2. Buyer Economics for Promoters and Detractors for B2C Credit Card Providers What contributes to these differences in spend? Unlike other products and services categories, it is unlikely that customers are spending on the basis of the credit card experience itself credit cards are a means to an end, not the end itself. While some providers may provide a simpler, more straightforward, or otherwise superior customer experience (in obtaining the card, in transacting with it, in the bill process, support, or rewards domains), these are unlikely to spur consumers to actively seek out additional opportunities to spend. The key to these robust differences in spend likely lies elsewhere. One possibility is that the results are confounded with income; more affluent respondents spend more, and are less likely to have negative interactions which may impact their loyalty to their credit card provider. The supposition would be that affluent respondents have less reason to carry a balance, to incur finance charges, to be exposed to written and/or verbal reminders to pay bills, or to be denied approval for credit or a credit increase. Those less well-off financially would be more likely to encounter those aspects of a card issuer s policies and services which can have an adverse impact on the customer relationship. The Net Promoter database used in the present analysis does not include respondent income, so it does not permit a direct test of this hypothesis. What data is available suggests that while socioeconomic status may influence both NPS score (through type of service encountered) and average amount spent (those with more money have the ability to spend more), it is not the sole contributor to this relationship. If financial status were the primary driver of NPS within the industry, we might expect to see provider NPS arrayed according to the relative affluence and credit rating of the corresponding core customers for each provider. This is not the case; there is significant variability in NPS scores even among those providers with quite similar target consumers, and

9 significant variability year-to-year within these providers despite relatively little change in their customer base (see figure 4-1). We also found no relationship between NPS and education level for customers rating their credit card companies. As there is a significant relationship between educational level and financial affluence (e.g., Durlauf, 1996; Galor, & Zeira, 1993; Psacharopoulos, & Patrinos, 2002), this would indicate that customer affluence is unlikely to be driving our results. Our analysis revealed no significant relationship between educational level and likelihood to recommend (r = -.04, p>.05). As presented in figure 3-3 below, the relative distribution of Promoters, Passives, and Detractors within each education level is quite similar. Figure 3-3. Promoter, Passive, and Detractor distributions by Education Level for B2C Credit Card Providers Rather than being driven by consumer characteristics, it is more likely that the spend differential is an expression of preference. According to research by the Federal Reserve Bank, 92 percent of U.S. households with income over $30,000 hold at least one credit card, with an average for all households of 6.3 cards (Wang, 2006). Because so many Americans have the ability to choose among several cards every time they make a purchase, the differences in spend we see here are most likely reflections of individual preference. For example, a Promoter of American Express would most likely use American Express as his/her primary card, utilizing it at all merchants who accept the card, driving up their annual spending. A Detractor of American Express, on the other hand, is likely to use another card as their primary credit option, driving down their spending with the American Express card. When a consumer is loyal to their credit card, they will be more likely to keep that card at the top of their wallet and choose to use it on a regular basis, with the corresponding impact on spend that we observe.

10 Net Promoter and Customer Retention As seen in Figure 3-4 below, the Net Promoter Score is also a strong indicator of customer tenure, creating the likelihood that our observed differences in customer spend are compounded over time. Given that the break even point for most credit card issuers occurs once the customer has held the card for six years, the differences we observe offer further evidence of the positive impact that Promoters exert on profitability. By extension, understanding the drivers of NPS becomes an important tool in prolonging customer tenure. Figure 3-4 Customer tenure segmented by NPS. Net Promoter and Referral Economics In addition to the robust relationship between Net Promoter, reported spend, and customer tenure, Net Promoter is also a clear predictor of referral behaviors. Just over one half of Promoters reported having positively referred their credit card provider to a friend or colleague in the previous 12 months. Promoters share these positive sentiments with approximately three other individuals on average during that time.. Detractors, by contrast, are less forthcoming about their experiences. Less than one fifth of these unhappy customers actively attempt to dissuade others from doing business with their credit card provider. On the other hand, when they do negatively refer, they are likely to cast a wider net than their Promoter counterparts sharing their negative experiences with 4.66 others compared to Promoters 3.08 referrals 3.

11 Based on these results, we were able to calculate an average referral value for both Promoters and Detractors, which then enabled us to compute the total customer worth for each loyalty segment. As seen in Figure 3-5 below, the referral value garnered for each Promoter s positive word of mouth amounts to just under one fourth of an additional customer. In other words, given the rate and frequency with which Promoters spread positive word-of-mouth, for every five Promoters, credit card providers can expect to gain one additional customer. Figure 3-5. Referral Economics for Promoters across B2C Credit Card Providers As seen in Figure 3-6, the referral value for each Detractor amounts to a loss of $7,690 in revenue. Given the rate and frequency with which Detractors spread negative word-of-mouth, a single Detractor will negate almost half of the revenue generated by their own spending. While relatively less frequent than positive referrals, the potency of negative referrals helps to underscore the damage that Detractors can inflict. Figure 3-6. Referral Economics for Detractors across B2C Credit Card Providers Interestingly, the findings for both Promoters and Detractors suggest that Credit Cards are not as frequent a topic of WOM as other product categories. For instance, in both the cellular service and computer hardware industries, roughly three quarters of Promoters will positively refer their provider of choice to others, compared to only 50% for credit card providers. Likewise, over 30% of Detractors in both industry categories share their negative experiences with others, as compared to 17% here. These differences do tend to dampen the contribution of referral economics to

12 calculations of total customer worth within the industry relative to other industries where WOM plays a larger, more active role. Net Promoter and Total Customer Worth Combining the buyer and referral economics associated with Promoters and Detractors allows us to create a much clearer picture of their financial impact on credit card providers. In this industry, Promoters primary economic value is both direct owing to the additional revenues gained from their higher spend rates and extended customer tenure and indirect, securing additional revenue through positive word of mouth. Based on the reported average spend across customers, we estimate the actual worth of Promoters to be over $23,000. In addition to the impact that reduced spend and higher churn among Detractors brings to the revenue picture, negative word of mouth from these customers presents a significant hidden cost. Lost business associated with their negative referrals subtracts a significant proportion of the value of their purchase behavior, creating a value for Detractors of just over $6,200. This results in a difference in customer worth of over $17,000 relative to their Promoter counterparts a disparity that far outstrips the difference between the two in reported annual spend (approximately $5,800). Note that this picture is likely to worsen once acquisition and support costs are factored in, further separating the two groups. Figure 3-7. Buyer Economics + Referral Economics = Total Customer Worth for B2C Credit Card Providers

13 Spotlight: American Express vs. Capital One Longitudinal data from credit card customers reveals noteworthy differences between the major card issuing organizations. American Express is and has been the loyalty leader within the segment, with Discover as its most recent challenger. Interestingly, Discover is similar to American Express in that it offers and emphasizes tangible rewards to customers for card usage. Recent research from JD Powers corroborates our findings, identifying American Express and Discover as leaders in customer satisfaction within their industry (Jalili, 2007). Figure 4-1. Trended NPS Scores for American Express and other B2C Credit Card Providers MBNA, Citigroup, Chase, and Washington Mutual represent the second tier in terms of customer experience, with positive Net Promoter Scores in It is interesting to note that there is a good deal of volatility for most providers other than American Express and Capital One. These two companies in terms of their business philosophy, target customers, and revenue strategies represent an interesting contrast to one another, with corresponding differences in customer sentiment and behavior. In the ensuing sections, we will explore these differences and the factors that contribute to them.

14 American Express vs. Capital One: Net Promoter Performance With a score of 47% compared to that of -3%, American Express leads Capital One by a huge margin on Net Promoter performance. As displayed in figure 4-2, the difference in scores is consistent across time. This suggests that American Express is consistently addressing the drivers of customer loyalty while Capitol One has substantial room for improvement in this area. Given that the percentage of Passives within each company is fairly similar (averaging 25.5%); the real performance differentiation between the two results from the ratio of Promoters to Detractors. With about double the proportion of Promoters and about half the proportion of Detractors, American Express leadership relative to Capital One and the overall industry is clear. Figure 4-2. American Express and Capital One 2007 Net Promoter Performance and 5 Year Trend vs. Overall B2C Credit Card Providers

15 American Express vs. Capital One: Buyer Economics White Paper As we ve seen, the NPS categories are reliable predictors of average spend within the credit card industry. We observe the same pattern for both American Express and Capital One, who are separated primarily by the average amount spent by their respective customer bases. American Express enjoys a substantial advantage in customer spend, where even Detractors spend more than the industry average; by contrast, even Capital One Promoters trail the industry average by a wide margin. Figure 4-3. American Express and Capital One 2007 Amount Spent Segmented by Net Promoter Category American Express vs. Capital One: Referral Economics As illustrated in Figure 4-4 below, the referral value garnered for each American Express Promoter s positive word of mouth amounts to just under one quarter of that spent by an average customer. In other words, given the frequency with which Promoters spread positive word-ofmouth, these individuals can be expected to generate an additional $5,467 in revenue. Figure 4-4. American Express: Promoter Referral Value

16 As seen in Figure 4-5 below, the referral value garnered for the positive word of mouth generated by each Capital One Promoter amounts to just over one fifth of that spent by an average customer. In other words, given the frequency with which Promoters spread positive word-of-mouth, on average, these individuals can be expected to generate an additional $1,983 in revenue. Relative to American Express customers, this figure is lower both because of the lower spend of Capital One customers, as well as the tendency of their Promoters to refer slightly fewer individuals (2.82 vs for American Express). Figure 4-5. Capital One: Promoter Referral Value American Express s ability to minimize its number of Detractors is a significant advantage relative to its competition. At 14%, American Express has less than half the number of Detractors as compared to Capital One s 39%. Furthermore, American Express Detractors are less likely to actively dissuade others from doing business with their provider-- a rate of 18% compared to Capital One s negative referral rate of 23%. When they do so, American Express Detractors also speak to fewer individuals 4.0 vs. 4.4 for Capital One. The cumulative effect of fewer Detractors and fewer Detractors who are actively disparaging their services constitutes a substantial financial advantage for American Express. As illustrated in Figure 4-6, the negative referral handicap for American Express translates into $9,620. Capital One, meanwhile, can expect a loss of $5,533 per Detractor (see Figure 4.7). Each Detractor for Capital One subtracts more than half (57%) of the value of an average customer through their negative word of mouth. This figure is significantly less (at 40%) for American Express. Figure 4-6. American Express: Detractor Referral Value

17 Figure 4-7. Capital One: Detractor Referral Value American Express vs. Capital One: Total Customer Worth Thus far, we ve reviewed evidence of the multiple advantages conferred upon American Express due to its loyalty leadership: a higher proportion of Promoters who are more active in generating new business for the company relative to its industry counterparts, a smaller proportion of Detractors, and less frequent damaging behaviors from these unhappy individuals. As illustrated in Figure 4-8, the cumulative impact of these behaviors lifts the total customer of worth Promoters for American Express to more than $30,000 per year 2.4 times the value of their counterparts at Capital One. While American Express Detractors lose approximately half their revenue value via negative word of mouth, this is nevertheless an improvement relative to Capital One Detractors, who subtract more than three quarters of their revenue value through negative word of mouth. Given the high cost of customer acquisition, the relationship between NPS and tenure, and the relatively high proportion of Detractors within its customer base, these figures suggest that Capital One needs to re-examine its customer strategy to improve its potential for revenue growth. Figure 4-8. Buyer Economics + Referral Economics = Total Customer Worth for American Express vs. Capital One

18 What Drives Loyalty in the Credit Card Industry? While it is certainly interesting to document the economic benefits conferred by loyalty leadership status, it is perhaps more interesting to understand how companies within the credit card segment are able to win the hearts and minds of their customers to achieve these outcomes. Within the Satmetrix Net Promoter benchmark database, there are a number of satisfaction questions relevant to the credit card industry that help us to clarify that issue. For the purposes of this analysis, we assessed strength of association correlating specific satisfaction attributes with likelihood to recommend to identify the top drivers. What we found is that the top loyalty drivers for the credit card industry (as defined by a correlation coefficient of.60 or above) are Overall Value, Overall Product, Customer Service/Support, Ease of Doing Business, and Company Reputation. In Figure 4-9, we compare the performance of American Express and Capital One along these critical dimensions. Figure 4-9. American Express vs. Capital One Performance on Top Industry Drivers Here, as with the overall NPS score, American Express outperforms Capital One in each of the categories. American Express s advantage is particularly noteworthy its customer satisfaction averages a full scale point higher than Capital One s average on all performance dimensions other than Ease of Doing Business.

19 Strategic differences between the two companies: White Paper What aspects of each company s business strategy help to explain this disparity in performance? One salient difference is the target customer sought by each company. American Express has a long tradition of providing service and rewards to customers with good to excellent credit history. In exchange for its generous rewards programs and responsiveness, the core of the American Express business has long been those consumers who can pay their bills on a timely basis and who can afford a substantial annual fee in exchange for the privilege of card membership. In 1987 that American Express first began to expand its product offerings to include credit cards with a revolving balance. By contrast, Capital One one of the largest providers of Visa and Master Card credit cards has a more diverse customer base and is newer to providing rewards, service, or additional features to reward card usage. While its offerings include platinum cards with low interest rates and tangible rewards to customers with good credit ratings, much of its business revolves around providing secured cards with annual fees and higher interest rates to customers with poor or limited credit history. These customers may be less well-informed about the implications and costs associated with obtaining credit as well as the costs and fees incurred for less-than-perfect credit behavior (e.g., exceeding one s limit, late or missed payments). This is not to suggest that customer characteristics drive the differences observed here. To the contrary, it is likely that the target customer sought by each company is an extension of the business strategy they employ, and the place of customer experience within it. As it happens, the key drivers of success identified above including value, service, and reputation align quite well with key features of the business philosophy followed by American Express, including: Top of wallet mentality. American Express tends to measure itself not according to outstanding balances but rather the level of card member spending. Unlike most credit card companies, which derive the majority of revenues from customer finance charges on revolving balances, American Express attains only about a third of its revenue from these charges. Its largest source of revenue comes instead from fees the company charges merchants for facilitating card member spending at their businesses. Through this model, elite privileges and purchase opportunities not only entice customers and motivate spending, they also translate into positive customer perceptions of the card. Exceptional customer experiences are just another way to spark spending and, consequently, growth. Likewise, American Express is interested in motivating card members to use their card for all of their purchases. Those card members using the American Express card for traditional categories of spend (i.e. travel and entertainment) are targeted with other category promotions such as retail. Customer segments are carefully selected for loyalty programs and are sent promotional offers designed to motivate stretch spending (i.e. spending more than in the past at the same establishment). American Express also partners with local companies to deliver compelling offers to card members based on their profile, including their spending behavior. Good vs. bad profits. American Express expends significant effort to provide customers with an informed choice and to match them to the appropriate product offerings. Different cards are tailored to meet the needs of specific customer segments. The company offers pay-in-full cards with no preset limits as well as cards with revolving balances; there are cards with exclusive benefits, a card with no fees of any kind and a card that deposits one percent of each purchase into a high-yield savings account. Transparency in the choices available helps to build trusting customer relationships from the beginning. The company ensures the clear and full disclosure of card terms and conditions and has initiated a number of programs, including a multiyear campaign in partnership with Consumer Action, to educate consumers on safe and effective credit practices. It is difficult for such interest and investment in customers to go unnoticed.

20 American Express policies are a stark contrast to those of Capital One, which routinely issues lowlimit cards to customers and collects high fees when customers exceed those limits. Customers also complain of hidden charges, such as those for telephone bill payments, which surprise customers when they open their monthly statements, and may even cause customers to exceed their credit limit. Where other card carriers charge a fee every time customers exceed their credit limits, American Express does not do so if customers are below their limit at the end of the billing period. They can exceed their limit and avoid a fee as long as they make a payment to bring them below the limit before the end of the cycle. American Express also avoids fees associated with bill payment, and does not assess fees no matter the payment method. The contrast between these two business strategies can be summed up, from the cardholder s perspective, as the difference between good and bad profits (i.e., profits that have a deleterious impact on customer loyalty). Customer trust and service. American Express has always emphasized customer service with its employees, striving to earn the trust of card members with its brand of uncommon service. Its commitment to partnership and service is in evidence in a number of ways: It maintains partnerships with elite merchants and organizations across the globe, enhancing card member benefits and rewards beyond those offered by competitors. Travel arrangements, special event access and personalized service differentiate its offerings. As a rule, American Express sides with the consumer when disputes arise. Disputed charges are immediately put on hold while American Express reaches out to the merchant to investigate the charge on the customer's behalf. American Express demonstrates trust through its policies including how it handles interest rate reductions. As the prime rate falls, card members experience automatic reductions to their variable rate accounts. This is notable because at times the company passes rate reductions on to customers even when its own cost of funds has not come down at an equivalent rate, due to uncertainty in the capital markets. American Express does not raise an individual s interest rate for any reason other than their performance on that particular account. Performance with other lenders or even on other American Express accounts is not brought to bear on a customer s rate. As a result, 94 percent of consumer lending accounts end the year with the same or a lower interest rate than at the year s start. Customers as their Compass. In addition to conducting extensive traditional marketing research, American Express leverages the Internet to stay connected with their customers. American Express has several private and public online communities to capture insight from different customer segments, guiding investments in products, programs and marketing efforts. Customer sentiment is so important to the American Express organization that significant capital and energy is invested into measuring and addressing customer sentiment. Indeed, American Express executives use the Net Promoter Score as a beacon to highlight and address customer concerns (BusinessWeek, 2006). In sum, American Express focus on providing uncommon customer service seems to be a goal that unites employees and its primary means for differentiating the company from its competition. Reflected in its practices and policies, it is also the likely reason that its customers perceive the company as trustworthy, easy to do business with, and a good value the sources of its industry leading NPS. It is in this context that we can better understand the competitive landscape of the credit card industry. While the customer promise tends to be the same customer rewards, differentiated service few companies deliver on it. Many of the companies have chosen to invest not in service but in targeted, information-based mass marketing, as a means to acquire greater market share. Profitability is predicated on acquisition maximizing acceptance rates on new cards and

21 generating revenue from interest rates on revolving balances and fees. Based on our data, we have to ask: to what end? It is clear that, in the long run, customers value and remain loyal to a company based on positive experiences rather than clever marketing campaigns. In turn, these loyal customers provide an efficient, low-cost acquisition engine through their own positive referrals. Adapting a stronger customer-centric focus, delivering value and service in exchange for customer loyalty, pays clear dividends in terms of customer spend, tenure, and word of mouth. How can Net Promoter Help Your Business? Our investigation of the relationship between the Net Promoter Score and customer worth within the B2C credit card industry reveals a robust relationship with purchasing and referral behaviors. On this basis, the Net Promoter WOM Framework can serve as a proxy and a predictor of how the mix of Promoters and Detractors within your customer base is impacting your business, and how successful strategies for increasing your customers loyalty can impact your bottom line. It is important to remember that knowing your Net Promoter Score is only the first step the metric itself is not the answer. To be successful, companies need to understand what actions they can take increase Promoters, decrease Detractors, and to move all customers up the loyalty chain. Once you determine what actions to put in place to effect this change and take the steps to empower employees across the enterprise to execute against these directives you will start to see an impact on loyalty and growth. And this is only the beginning of the journey. As companies learn to listen more effectively to their customers, and to act on their behalf, they will discover other opportunities to strengthen the bonds they share. The data reviewed here hints at one such opportunity in its examination of the power of word of mouth. Given the enormous influence that word of mouth messaging has on brand evaluation and purchase decisions, a company s Promoters represent a significant and often untapped asset. Identifying ways to leverage Promoters through reference programs, by providing tools that facilitate their naturally occurring word of mouth behaviors, by amplifying their messages through community and social media is a logical and promising next step in the evolution of how companies can benefit from Net Promoter.

22 Endnotes 1 The Net Promoter metric is based on one simple question: Would you recommend us to a friend or colleague? The scale employed is an 11 point (0-10) likelihood scale. To calculate the Net Promoter Score, take the percentage of customers who are Promoters (defined as scores of 9 or 10) and subtract the percentage who are Detractors (defined as scores of 0 through 6). 2 To obtain the conversion rate, we asked each respondent within the entire sample if they themselves had been referred to their provider by a friend or colleague. We summed the number of customers who had been referred to their provider and divided it by the total number of positive referrals issued. The resulting ratio estimates the impact of positive referrals. 3 There is a rich psychological and socioeconomic literature regarding the relative weight assigned to positive and negative information. The basic finding that negative information seems to exert a disproportionate influence relative to positive information has been replicated many times over both for interpersonal judgments (e.g., Anderson, 1965) as well as for how consumers evaluate brands and make purchase decisions (e.g., Arndt, 1967; Weinberger & Dillon, 1980; Weinberger, Allen, Dillon (1981); Mizerski, 1982; Wilson & Peterson (1989); Herr, Kardes, & Kim (1991); East, 2002). Unfortunately, while many studies support the notion that negative word of mouth is more influential than positive word of mouth, few have tried to quantify the difference. One seminal finding comes from Kroloff (1988), whose influential Merriam formula was derived from observations that individuals tend to give negative information approximately four times the weight of positive information. Other researchers have noted that a single negative behavior can neutralize as many as five positive behaviors (Richey, Koenigs, Richey and Forgin, 1975). In a study of Dell customers, Fred Reichheld and Satmetrix found that, on average, customers report that a single negative comment can offset five positive ones. Across these studies, it is reasonable to expect negative word of mouth to exert 4-5 times the influence of positive word of mouth. In the present study, we chose the more conservative weighting, assigning negative referrals four times the weight of positive ones. 4 To obtain the negative conversion rate, we multiplied the positive conversion rate of 14% by a magnitude of 4, yielding 56% (see endnote (3) for details). This estimate is corroborated external research on negative word of mouth on consumer decision making. The Verde Group, in conjunction with the Baker Retailing Initiative at the Wharton School of Business, found that 31% of dissatisfied customers tell others about their problems (compared to our 29%), and that they tell on average 4 other individuals about their negative experience (compared to our 4.2). Likewise, they found that roughly 64% (compared to our 68%) of customers who are recipients of negative word of mouth about a specific vendor will choose to shop elsewhere.

23 References Durlauf, S. J. (1996). A theory of persistent income inequality. Journal of Economic Growth, 1. Forrester (2007). Forrester's Marketing Forum: Reinventing Customer Centricity. April Maimi, FL. Galor, O. & Zeira, J. (1993). Income Distribution and Macroeconomics. The Review of Economic Studies, 60, Herr, P. M., Kardes, F. R., Kim J. (1991). Effects of Word-of-Mouth and Product-Attribute Information on Persuasion: An Accessibility-Diagnosticity Perspective, Journal of Consumer Research, 17. Heskett, JL Sasser,WE Schlesinger LA (1997). The Service Profit Chain: How Leading Companies Link Profit and Growth to Loyalty, Satisfaction, and Value. Simon and Schuster: New York. Ittner, C. D., & Larcker D. F., (1998) Are nonfinancial measures leading indicators of financial performance? An analysis of customer satisfaction, Journal of Accounting Research, 36, Jalili, H. M. (2007). Amex, Discover Top Cardholder Survey. American Banker, 172, 195. Kroloff, G., At home and abroad: weighing in. Public Relations Journal. 44. Marsden, P Samson, A, & Upton, N. (2005). Advocacy drives growth customer advocacy drives UK business growth, Brand Strategy (Dec 2005). McGregor, J. (2006). Would You Recommend Us? That simple query to customers is shaking up planning and executive pay. BusinessWeek article retrieved online at: on 8/4/2008. MizerskiAn, R. W. (1982). Attribution Explanation of the Disproportionate Influence of Unfavorable Information, Journal of Consumer Research, 9, Psacharopoulos, G., & Patrinos, H. A., (2002). Returns to Investment in education: A further update. World Bank Policy Research Working Paper No Available at SSRN: Reichheld, F. (2003). The one number you need to grow. Harvard Business Review, December, Richey, M. H., Koenigs, R. J., Richey, H. W., Fortin R. (1975). Negative salience in impressions of character: effects of unequal proportions of positive and negative information. Journal of Social Psychology, Dec; 97(Second Half): Weinberger, MG Allen, CT & Dillon WR (1981). Negative Information: Perspectives and Research Directions, Advances in Consumer Research, 8, START HERE Heskett, J. L., Jones, T. O., Loveman, G. W., Sasser, W. E. Jr., & Schlesinger L. A. (1994). Putting the service-profit chain to work. Harvard Business Review, March-April, Wang, Z. (2006). Market structure and credit card pricing: What drives the interchange? Federal Reserve Bank of Kansas City Working Paper 06-04, 1-50.

24 East, R. & `Olmo Riley, F., D. (2002). Positive and negative word-of-mouth influence. Kingston University paper presented at Australian and New Zealand Marketing Academy Conference. Kroloff G. (1988). At home and abroad: Weighing in, Public Relations Journal, 44, Wilson, W. R., & Peterson R. E. (1989). Some limits on the potency of word of mouth information Advances in Consumer Research, 16, Arndt, J. (1967). Perceived risk, sociometric integration, and word-of-mouth in the adoption of a new food product. In Cox, D. (Ed.) Risk Taking and Information Handling in Consumer Behavior (pp ). Boston: Graduate School of Business Administration, Harvard University. Weinberger, M. C., Allen, C. T., & Dillon W. R. (1981). Negative information: Perspectives and research directions," in Monroe, K. B. (Ed.) Advances in Consumer Research, Vol. 8, (pp ). Ann Arbor, MI: Association for Consumer Research. Anderson, N. H. (1965). Averaging Versus Adding as a Stimulus-Combination Rule in Impression Formation," Journal of Personality and Social Psychology, 2 (July), 1-9. Richey MH, Koenigs RJ, Richey HW, Fortin R. (1975). Negative salience in impressions of character: effects of unequal proportions of positive and negative information. Journal of Social Psychology, 97(Second Half): Paul M. Herr, Frank R. Kardes, and John Kim (1991), Effects of Word of mouth and Product- Attribute Information on Persuasion: An Accessibility-Diagnosticity Perspective, Journal of Consumer Research, 17 (March), An Attribution Explanation of the Disproportionate Influence of Unfavorable Information Richard W. Mizerski. The Journal of Consumer Research, Vol. 9, No. 3 (Dec., 1982), pp The Effects of Unfavorable Product Rating Information. MG Weinberger, WR Dillon - Advances in Consumer Research, 1980 Kroloff, George (1988), At Home and Abroad: Weighing in, Public Relations Journal, (October), 8.

25 This document is provided for informational purposes only and the information herein is subject to change without notice. Please report any errors to Satmetrix. Satmetrix does not provide any warranties covering and specifically disclaims any liability in connection with this document. About Satmetrix Satmetrix is the leading global provider of on-demand software applications and consulting services to measurably improve customer loyalty and link these results to financial benefits. As the co-developer of Net Promoter, the company s solutions enable companies to monitor the customer experience at key touch points, measure loyalty of customers, partners and employees, identify performance gaps, and engage customers in a continuous dialog through online communities. The company has deployed more than 700 enterprise solutions in 40 languages Satmetrix Systems, Inc. All rights reserved. Satmetrix and the Satmetrix logo are trademarks of Satmetrix Systems, Inc. Net Promoter, NPS, and Net Promoter Score are trademarks of Satmetrix Systems, Inc., Bain & Company, and Fred Reichheld.. Satmetrix Headquarters 2755 Campus Drive Suite 300 San Mateo, CA Phone: Toll Free: Fax: EMEA Office 3rd Floor, Colet Court 100 Hammersmith Rd. London W6 7JP Phone: Fax: Paris Office 112, avenue Kleber Paris cedex 16 France Phone: Fax: New York Office 450 Seventh Avenue Suite 1601 New York, NY Phone: Fax: India Development Center G1, Tejaswin Technopark Campus Trivandrum, Kerala India Phone: Fax: Web site: sales@satmetrix.com