The Loyalty Economy
Managing for customer value
Vanguard, the mutual fund company known for its low-cost index funds, frequently shows up on lists of organizations with the most-loyal customers—and that’s no accident. During his tenure as CEO, from 1996 to 2008, Jack Brennan emphasized what he calls the virtuous circle of attracting loyal clients who stick around and create new ones through word of mouth. Now Vanguard’s chairman emeritus, he is a leading voice on corporate disclosure issues and has held positions at the Financial Accounting Foundation, the Financial Industry Regulatory Authority, and the Investment Company Institute. Brennan spoke with HBR about why companies should want to tell investors more about their customers—and how soon they may be required to. Edited excerpts follow.
HBR: How did you become interested in customer value?
Brennan: In our business, the highest-cost thing we do is attract and onboard new clients. So why wouldn’t we be driven to increase the loyalty of those clients? This isn’t differential calculus. When customers leave, you have to replace them, and we’d prefer to avoid that expense. So we have followed Bain & Company’s loyalty research very closely for many years. In the years since I became Vanguard’s CEO, managing for loyalty has gone from an intuitive idea to a conceptual goal to an operational practice. Across businesses in general, this is still underexposed and undervalued as a concept. Rob Markey’s new work on using loyalty metrics to better understand and manage the value of a firm is the next evolution of this idea.
Where do you see these new techniques being used?
The place where I’ve seen this play out most aggressively is in private equity. If you talk to private equity firms about the due diligence they engage in when they’re buying a company, the customer base is a critical part of what they’re looking at. It’s intense. They’re asking senior management: What’s the nature of your customer base? How are you acquiring customers? How are you losing them? Which ones are profitable? They’re interested in individual customer accounts and transaction data. A debate is currently going on about whether investors who are buying not an entire company but, say, 1,000 shares should have access to some of the same information about the core value of the customer base that private-market investors see in their due diligence process. I think they should.
Are Vanguard’s portfolio managers using customer valuation tools?
I’m not close enough to their work to know, but I do see other public-market investors using them. One portfolio manager I know runs a very concentrated fund—it holds eight to 10 stocks at a time, with essentially zero turnover. Because he’s holding very few stocks for a very long time, he thinks more like an owner. He approaches each investment as if he’s buying the whole company. Among the first things he does is conduct a deep study of the customer base—its breadth, its depth, its growth. He even hires third parties to help with the analysis. That’s an example of how investors don’t simply rely on the customer data that the company discloses—they actively seek out data on their own. If you walk into a Walmart, there’s usually somebody in there counting something for an analyst. Investors sometimes even hire investigative reporters to dig up information. They’re trying to learn as much as they can about a company’s customers.
How do regulators decide whether or not to require more disclosure on customer metrics?
I’ve been working on issues around financial disclosure for many years, and it’s a fascinating process. The Financial Accounting Standards Board (FASB) is always balancing what’s valuable to investors against what’s overly burdensome or competitively disadvantageous to companies. Do shareholders have access to enough material information to judge the company’s risks and performance? How much is too much disclosure? What’s verifiable? Regulators are leery of being presented with non-GAAP measures—metrics that don’t conform with generally accepted accounting practices. They worry about clutter risk—the distraction created by too much data that’s not very meaningful to investors. Companies worry about being forced to reveal information that could help their competitors. There’s always tension and stress around the prospect of new reporting requirements, and it’s not irrational. But the debate that goes into standard setting is healthy and valuable.
Amazon has millions of Prime subscribers, but it won’t say exactly how many, so analysts are left to guess. What’s the harm in disclosing that number?
Prime members are obviously a critical part of Amazon’s business model. But executives may choose not to disclose the number because they don’t want investors to fixate on any one metric. Think about the way investors watch Netflix subscriber counts. Amazon probably wants to avoid investors’ reacting every time Prime subscriber numbers go up or down. Top management might also argue that disclosing the number puts the company at a competitive disadvantage—even though it doesn’t really have a head-to-head competitor.
What does the timeline for more disclosure look like?
If shareholders demand disclosure, it will get the attention of the Securities and Exchange Commission, and FASB will weigh in on whether it can be done well. I do think regulation will happen; the question is at what pace? It always feels too slow to me. I think it is still years away, but over time, the market will demand it. I don’t think you’ll see standardized, fine-tuned Net Promoter Scores as part of corporate financial statements any time soon, but some information about customers will probably be required in the not-too-distant future in the management disclosure and analysis (MD&A) section of the annual report or in the footnotes. That’s how regulators have treated disclosures about executive compensation and environmental, social, and governance data. Requirements could begin with something as simple as “We had X number of customers on December 31 of last year and Y number on December 31 of this year,” with a little bit more granularity. Companies that are proud of their customer base and loyalty have an incentive to disclose more, of course. Creating a virtuous circle of loyal customers is one of those self-evident ideas that you can’t emphasize enough.
Leaders recognize that they should manage their businesses to maximize the value of the customer base. But too often, earnings pressure results in cost-cutting measures that hurt customers.
Smart companies use new models, technologies, and marketing metrics to increase the number of profitable customers, boost retention, and maximize purchases.
Given the importance of customer value, leaders should track it as rigorously as they track other key assets. And they must report on it in formats that allow investors to make informed judgements.
The true purpose of a business, Peter Drucker said, is to create and keep customers. Most managers understand this, but few behave as if they do. Under relentless earnings pressure, they often feel cornered, obliged to produce quick profits by compromising product quality, trimming services, imposing onerous fees, and otherwise shortchanging their customers. This short-termism erodes loyalty, reducing the value customers create for the firm.
It should not be this way. Earning customer loyalty is firmly in the interest of both shareholders and management. My research shows that loyalty leaders—companies at the top of their industries in Net Promoter Scores or satisfaction rankings for three or more years—grow revenues roughly 2.5 times as fast as their industry peers and deliver two to five times the shareholder returns over the next 10 years. Yet companies and investors continue to prioritize quarterly earnings over customer relationships, for three main reasons: Public-company financial disclosure rules and corporate accounting practices require little to no reporting on customer value; most firms lack the capabilities needed for managing it; and organizations’ traditional structure puts functional priorities ahead of customer needs.
The roots of the problem can be traced to the 1890s and the birth of modern financial accounting, but the situation worsened in 1970, when Milton Friedman introduced the age of shareholder primacy, which held that companies exist to maximize shareholder value. Since then, companies have perfected sophisticated systems and practices for delivering on that promise. A decade ago, Roger Martin, then dean of the University of Toronto’s Rotman School of Management, inverted this notion. He espoused a new “age of customer capitalism” in which companies that put customers first would create even greater value for shareholders. He was not taking issue with Friedman’s basic assertion but pointing out that its practical application had gone awry. The blind pursuit of shareholder value had devolved primarily into managing investor earnings expectations.
Few acted on Martin’s vision. Even if leaders agreed with his premise, they reasonably worried that prioritizing customers could threaten short-term earnings, causing investors to rebel. Further, the technologies, operational skills, and performance measurement systems needed were nascent at best. Pursuing such a strategy was generally a risky proposition a decade ago. The time was not right.
Now, though, the missing pieces are falling into place: the emergence of new accounting tools and technologies, a fundamental shift in the way companies organize work, and, perhaps most critically, the realization among at least some investors that customers are the ultimate source of corporate value. CEOs themselves are beginning to acknowledge this idea. In August 2019, the Business Roundtable, representing many of the largest U.S. firms, issued a statement on the purpose of the corporation in which members put delivering value to customers, among other goals, on equal ground with creating shareholder value.
In working with hundreds of companies in a range of industries over 30 years, I have identified four broad strategies that loyalty leaders rely on for superior performance. Those leaders create systems for measuring customer value and invest in the necessary enabling technology, use design thinking methods to build customer loyalty, organize the business around customer needs, and engage the organization and stakeholders—employees, board members, investors—in the transformation. Before we examine each one, let’s take a closer look at customer value.
“Customer value” has several definitions. I use the term to mean the total lifetime value of a company’s customer base. Companies can increase this value by acquiring more customers, earning more business from existing ones, retaining them longer, making their experience simpler (and often less expensive to deliver) through digital improvements, and so on. Visionary, customer-focused leaders such as Amazon’s Jeff Bezos, Costco’s Jim Sinegal, and Vanguard’s Jack Brennan have long understood the importance of concentrating on customer value as an asset rather than pursuing short-term profits or quarterly earnings, and they’ve become enduring customer loyalty leaders in the process. It’s worth noting that a disproportionate number of loyalty-leading companies are able to resist shareholder pressure, or avoid it altogether, because they are founder-led, customer-owned, or not publicly traded.
Companies can destroy customer value in a variety of ways: To boost revenue, enterprise software companies sometimes charge corporate customers change fees that can raise the total cost of ownership to as much as three times the original bid. To cut labor costs, call centers often give agents incentives to minimize call-handling times. To reduce operating costs, restaurant chains sometimes substitute frozen and precooked ingredients in place of fresh and made-to-order food. The resulting profits may look good on the income statement. Such tactics may even lead to short-term earnings growth. But they also scare off potential customers, encourage defection, and make the company vulnerable to poaching by customer-centric competitors.
Loyalty leaders grow revenues roughly 2.5 times as fast as their industry peers.
Given the importance of customer value, leaders should track it as rigorously as they track other key assets, such as buildings, machinery, inventory, and marketable securities. They also should disclose it in their quarterly and annual earnings releases in consistent formats so that investors can make informed judgments about company performance and how it compares with that of industry peers. But most companies wrongly believe that measuring customer value is too difficult or costly. They continue to rely on a centuries-old accounting tradition that emphasizes physical and financial assets, and neither income statements nor balance sheets offer much visibility into the value of a company’s customers.
As investors wake up to the importance of customer value, however, many growth-stage companies preparing for an IPO—most so focused on acquiring customers that they’re unprofitable—now explicitly direct investors’ attention to success in growing the value of their customer base. My team at Bain examined the SEC S-1 registration filings of 309 companies that were preparing for public stock offerings in 2018. Nearly one-quarter of them included non-GAAP metrics such as active customer count, new customers acquired, purchases per customer, and revenue per new-customer cohort.
Some public companies, such as Costco, AMC Entertainment Holdings, Humana, and American Express, increasingly report various types of customer value metrics. Most telecommunications companies—including Verizon, AT&T, and T-Mobile—do as well. The utility company E.ON reports year-over-year customer counts in its audited financials. Its 2018 annual report noted a decline of 200,000 customers in the UK and an increase of 100,000 in Germany, while other regions were flat. “As a customer-focused company,” E.ON noted, “we see our ability to acquire new customers and retain existing ones as crucial to our success.” E.ON began tracking loyalty metrics in 2013 and discloses its performance relative to competitors. Insurance giant Allianz has been doing that even longer.
This is a start, but because there are no customer-value reporting standards or requirements, investors still have an incomplete picture. The minority of companies that do provide customer value information decide for themselves what to disclose. Further, firms may calculate customer metrics differently or tweak them to tell a desired story, or simply stop reporting them if they fail to align with the company’s preferred narrative.
We won’t truly enter the age of customer capitalism until financial-accounting standards bodies enact rules that require reliable, auditable disclosure of customer-relationship health. This has long been a topic of debate in the accounting world. Over the years the Financial Accounting Standards Board, the International Accounting Standards Board, and others have attempted to improve reporting on intangible assets including customer value. Those efforts have consistently run into challenges related to valuation methodology, differences in industry practices, and the cost of compliance.
I propose a straightforward approach to disclosure that simplifies the accounting task for companies and places the burden of valuation onto investors.
While we await clear standards and rules, companies should take the lead, disclosing reliable and consistent information about the progress they are making growing customer value as part of their earnings releases. Only then can investors systematically reward those investments. Three new, auditable metrics would suffice in most instances:
Using just these metrics, investors could readily estimate the changing value of a company’s customer assets.
The value of a firm’s customer base is the sum of the value of existing and future customers. In practice, some investors now incorporate the components of customer value—along with their assumptions and projections about the future competitive and regulatory environment—into their traditional valuation models. For an interactive look at how to calculate customer value, go to bain.com/customer-value.
Gathering the data shouldn’t be difficult; nearly every company already tracks these metrics. Methods for calculating customer value will differ slightly between subscription-based businesses (think retail banking, cable companies, and software-as-a-service providers) and nonsubscription ones (grocery stores, for example, or parts suppliers), but the basic principles are the same. For subscription businesses in which customers also make discretionary purchases, one additional metric is required: the number of orders placed by new and existing customers during the period.
To help investors develop more-nuanced valuations, companies could disclose what it costs them to acquire and serve customers in various segments, and provide a breakdown of customer counts and revenue by cohort. Likewise, disclosing the volume of purchases and retention rates among the top 20% of customers relative to the remaining 80% would materially improve investors’ ability to value a company’s customer base. Many companies may consider this information proprietary, but it is so important to corporate valuation that I believe investors should have it. (For more on customer cohorts, see Daniel McCarthy and Peter Fader’s article “How to Value a Company by Analyzing Its Customers.”)
Qualitative measures such as Net Promoter and customer satisfaction scores are also of use to investors in assessing customer loyalty. Companies should source such measures from independent third parties that publish their methodology and present them in consistent formats. Short of that, firms should provide auditable evidence that their metrics are accurate and can be reliably compared with metrics reported by other companies.
Disclosure is an essential element in bringing customer value to center stage, but what generates the outcomes to be reported on? Let’s turn now to the four strategies used inside a company to achieve consistent and sustained growth in customer value.
To engage employees in the work ahead and to sell investors on the necessary investments, leadership first needs a clear understanding of the size of the prize: the current total lifetime value of the customer base and the potential financial value that lies in increasing customer loyalty. New accounting tools and technologies enable managers to model customer value and report regularly on the impact of their actions. (Providing tools will typically be the responsibility of the finance organization.)
For example, to improve the loyalty and profitability of new customers, managers need periodic reports on the performance of each new-customer cohort. How much did it cost to acquire new customers in each cohort? What percent of customers in each remains active? How frequent are their purchases? How much does it cost to serve them? What is the revenue per customer? By comparing the performance of different cohorts, managers can monitor real-time improvements or declines in lifetime value.
Each department managed its metrics and celebrated its wins. Only the customers lost.
Managers can also use analytics and reporting to track how experiments and changes in products, pricing, customer policies, processes, promotions, and services affect each cohort’s performance over time. Using time-series analytics, for example, they can monitor customers who have been exposed to specific initiatives—say, a service personalization effort—to determine how that experience will affect lifetime value. Operational measures, such as the number of abandoned calls or the first-time success rate in a digital self-service experience, can be combined with qualitative data, such as customer feedback scores and comments, to sharpen the picture.
This just scratches the surface, of course, but it conveys the type of robust analytics and reporting managers could have at their disposal to compete for customer loyalty.
Companies earn loyalty when they anticipate and meet fundamental, often unexpressed, customer needs. Doing this depends on two sets of capabilities: design thinking and careful application of cutting-edge technologies.
Design thinking is about seeing the world through customers’ eyes and learning through direct observation. Managers, frontline employees, and even C-level executives should engage in the exploration and design process. Design thinking combined with a constant flow of customer feedback helps product groups create highly personalized offerings. It also informs loyalty-driven sales and marketing efforts. Messaging can be tailored and targeted to put the right offering in front of the right customer in the right way at the right moment. The goal is not simply to induce customers to buy. It is to improve their lives so effectively that the company earns their trust and continued business.
Data, analytics, and AI capabilities are key to human-centered design. Consider how an insurance company might use AI to enrich service interactions. A customer, Mary, calls with a question related to a recent claim. Before she even speaks to a live rep, the AI-enhanced routing system predicts what her need is on the basis of her profile data, latest mobile and web interactions, and recent purchases. The system uses this context to route Mary not to the next available agent but to the one whose interaction style and technical proficiency are best suited to the issue at hand. Once the call is connected, an AI-enabled coaching system analyzes Mary’s tone of voice and rate of speech during the call and provides guidance to the agent in real time about ways to improve her experience. Instead of trying to prevent customers from ever reaching a live human—so often the default cost-cutting strategy—such systems focus on speeding calls to the right human.
Examples of such intelligent personalization are growing in number and variety. The best of them share a focus on using technology to enhance the customer experience, which often also reduces the company’s delivery cost. Beginning in the early 2000s, companies such as Amazon, Netflix, and Google have given us a taste of what the future could bring. The question today is not whether to make investments in data and technology but how best to leverage those that have been made. Big companies often face complex legacy IT system and data challenges that digital-native firms do not, but they also have a significant advantage: They typically have amassed vast customer databases over decades and have the resources to take full advantage of them, including by conducting many simultaneous customer experiments that can speed innovation.
Rich customer-value data and design-thinking practices will remain locked in silos unless companies embrace new operating models that push decision-making down to frontline employees, reduce cross-functional friction, and focus the organization on customers.
Since the early 1900s, large companies have employed operating models built around functional and product expertise and accountability. Finance, legal, marketing, sales, operations, compliance, and other functional departments or product teams form the “strong arms” of the company matrix, generally controlling resource allocation, goal setting, and decision-making. This structure fosters localized accountability, expertise, and efficiency, all of which are critical for competitive performance. However, the model also gives rise to silos, each of which seeks to optimize its own performance. Even when functional goals are more or less aligned, in-group bias—the tendency to favor one’s own group and view others with suspicion—leads to conflicts among silos and even among members of a team drawn from different silos.
Consider how this played out at one large logistics company, where a cross-functional initiative to tackle the problem of shipping damage—a big cost for the company and perhaps the largest frustration for customers—foundered in a sea of misalignment and noncooperation. The issue appeared to be simple: Large, heavy packages often crushed smaller ones in the company’s trucks. But the sales department, with an eye toward meeting or exceeding its targets, refused to stop accepting orders for large packages or to charge more for them. The shipping department, mindful of its cost goals, resisted setting up a separate handling process for large items. Customer service, to minimize costly time on the phone taking claims, made it more difficult to reach reps to file a complaint. And risk managers did their best to cut payouts by rejecting most claims and reducing payment on claims that were accepted. Each department aggressively managed its own metrics. The results were impressive: Shipping costs were kept in line, revenue grew, phone center costs held steady, and damage payouts went down. Each functional team celebrated its wins. It seemed that only the customers lost.
It would be irresponsible to ignore customer value as a source of profitable growth.
Instead of fighting or ignoring in-group bias, some companies now harness it for the benefit of customers by aligning cross-functional teams around a specific customer need. Although members are drawn from different functions, they are fully dedicated to the team, with authority for decision-making and accountability for outcomes. Many digital-native firms, such as Warby Parker and Stitch Fix, are organized around teams whose “products” are better described as customer experiences, including try-on programs in which eyeglass frame options or personalized clothing selections are shipped to customers’ homes for consideration. No purchase is required, and easy returns are guaranteed. The teams are composed of representatives from each discipline necessary to deliver the experience—IT, marketing, fulfillment, and finance, for example—and each team focuses on meeting a defined need. Team members, whatever their functional provenance, view addressing the customer need as their primary goal, with individual performance measured and rewarded through their contributions to the team’s results.
Legacy businesses are now following suit. Consider the insurer and bank USAA. It historically assigned separate product groups to manage its various offerings. For example, when a customer purchased a car, one group would help secure financing while another helped with insurance. The process worked, but USAA’s leaders believed the company could do a lot better. Following the digital natives’ lead, USAA now organizes around customers, with employees from different product lines and functional groups working as a team to address an overarching customer need. People seeking to buy a car can choose and locate the best model, negotiate its purchase, and finance and insure it as a seamless experience. Customer-needs-based objectives sit alongside product and operational goals; success is measured across key outcomes such as customer satisfaction, loyalty, and product sales.
When teams are organized around the customer, the functional and product expertise that often worked at cross-purposes when employees were locked inside silos can act as powerful accelerants to innovation and competitiveness, particularly when backed by huge storehouses of data and the capabilities required to mine it.
Reorganizing around customer needs requires rewiring the organization and its decision-making pathways. Agile ways of working can dramatically speed up team processes, but leaders must accept that this involves letting go and allowing the frontline employees closest to the customer to make decisions that once came from the top. That can make traditional leaders uncomfortable, because it depends on experimentation, struggle, occasional failure—and relinquishing some control. But the shift is inevitable. At the current rate of transformation, I estimate that within 20 years more companies will organize around customer needs than around traditional functional models.
The job of leadership in any major organizational shift is to articulate an inspiring vision, lay out a path, and engage every employee in the work ahead. The first thing leaders must do is get everybody on board. Building the case for customer value should be easy: When a company focuses on loyalty, it makes customers’ lives so much better that they keep coming back, and they bring their friends. Employees become inspired by the satisfaction that comes from making customers’ lives better. And don’t forget the superior performance of the companies that lead their industries in Net Promoter Score or satisfaction. Their revenue growth and shareholder returns far surpass those of their peers. Companies that don’t pursue customer value risk being put out of business by those that do.
Loyalty leadership demands persistent attention. Although the new customer focus is in part about pushing decision-making down the ranks, that doesn’t mean that leadership focus can be fleeting or insincere. Look at the case of Telstra, an Australian telecommunications company. CEO David Thodey recognized that providing a far better customer experience was necessary for achieving and sustaining growth. He set out a clear vision for the company and its employees: Telstra would lead its industry in customer advocacy as gauged by Net Promoter Scores. He declared that customers would be his top priority. He demonstrated his commitment by beginning every business-unit review meeting with a discussion of progress on customer advocacy. He regularly made calls to customers. He insisted that his own leadership team devote time in standing meetings to knocking down barriers to delivering a great customer experience. He supported changes in policies and pricing to improve the customer experience, often at the expense of short-term business performance.
Thodey couldn’t have done this without support from Telstra’s investors. He worked hard from day one to educate them about the company’s efforts to strengthen customer relationships, and they supported him. During his six years leading Telstra, the company improved customer loyalty in every major product, customer segment, service process, and point of contact with customers. It gained 10 points of market share in the lucrative mobile business, and its stock price increased by more than 70%. Yet soon after Thodey departed, customers figured less prominently in Telstra’s strategy. Competitive pressures forced the company to focus on improving its cost position rather than continuing to invest more in initiatives that had earned customers’ trust. Since Thodey’s retirement, in 2015, Telstra has slipped to the middle of the industry loyalty rankings.
As Telstra’s experience shows, loyalty leadership requires ongoing attention to the actions of employees across the organization—changing decision criteria, supporting policy changes, and celebrating customer loyalty wins. This signals commitment to customers and gives employees confidence that the loyalty strategy is not an empty promise.
Loyalty leadership also calls for managing up and out. Top managers must gain and maintain the support of board members and investors by educating them about the loyalty-based strategy and how its progress should be evaluated. This is particularly important early in a customer value transformation, because management will be making decisions (such as investing in technology) that may depress short-term earnings. Leaders need to demonstrate to investors and board members that those decisions will yield larger payoffs down the road, in the form of increased customer acquisition or retention, growing revenues, lower cost to serve, or other measures of improved customer value.
It’s easy to blame companies’ short- termism on shareholder pressure and a bias toward quarterly financial reporting. But managers share the blame when they fail to educate investors about the customer value their company creates or when they resort to quick profits instead of investing in long-term customer loyalty. Several iconic founder-led companies have paved the way for decades. A handful of independent public companies are doing so too. And they deliver outsize growth, profitability, and returns to shareholders.
It would be irresponsible for any leader to ignore such a proven source of profitable growth. Boards and shareholders should demand that companies grow customer value, support the necessary investments, and push for new accounting standards that make the returns on these investments visible. All stakeholders will benefit: Customers will experience products and services that make their lives easier, richer, and more enjoyable. Employees will reap the benefits of making customers’ lives better. Management and investors will see increasing profits and shareholder value. And society will enjoy the economic growth that derives from innovation and investment. With transparency and reliable disclosure, investors and management teams can strike at the heart of short-termism and run their businesses for sustainable value.
Rob Markey is a partner and director at Bain & Company and the founder of the firm’s Global Customer Strategy and Marketing practice. He is a coauthor of the book The Ultimate Question 2.0: How Net Promoter Companies Thrive in a Customer-Driven World (HBR Press) and is the host of the Net Promoter System podcast. He is based in New York.
In the weeks leading up to the initial public offering of apparel retailer Revolve Group, in June 2019, investors struggled to come up with a fair valuation. Several recent IPOs—most notably those of the ride-hailing firms Uber and Lyft—had been disappointing. Revolve had delayed its IPO for months because of a downturn in the stock market. Despite the headwinds, its IPO was priced at $1.2 billion—and it exploded by an additional 89% on its first day of trading, making it one of the best first-day IPO performances of 2019. The spike brought the company’s valuation to roughly 4.5 times its revenue over the previous 12 months—five times the multiple of its apparel-retailing peers and more akin to that of a technology company. What happened, and why did investors originally fail to see just how strong a firm Revolve was?
Revolve’s premium valuation was not a fluke. It stemmed from the firm’s strong underlying fundamentals, which were not fully appreciated by the underwriters who set the IPO price. This strength was less about top-line revenue growth and more about strong customer-unit economics: Simply put, Revolve not only acquired its customers profitably but retained them for many years, and that meant its longer-term profit potential was larger than its revenue growth to date had implied.
Revolve’s IPO success illustrates the movement toward customer-driven investment methodologies. Using customer metrics to assess a firm’s underlying value, a process our research has popularized, is called customer-based corporate valuation (CBCV). This approach is driving a meaningful shift away from the common but dangerous mindset of “growth at all costs” toward revenue durability and unit economics—and bringing a much higher degree of precision, accountability, and diagnostic value to the new loyalty economy.
In this article, we explain how executives and investors can use the principles of CBCV to better understand and measure the value of a firm. The methodology works whether the company features a predictable, subscription-driven revenue stream (think of Netflix and Verizon) or a base of active customers who place discretionary orders every so often (think of Uber and Walmart). We also discuss how companies can benefit from providing investors with more of the right kinds of customer data—and how investors can avoid being fooled by vanity metrics that appear to be useful indicators of customer behavior but aren’t as meaningful as they might think.
The premise behind CBCV is simple. Most traditional financial-valuation methods require quarterly financial projections, most notably of revenue. Recognizing that every dollar of revenue comes from a customer who makes a purchase, CBCV exploits basic accounting principles to make revenue projections from the bottom up instead of from the top down. Although this may seem like a radical departure from traditional frameworks, that’s not the case: CBCV simply brings more focus to how individual customer behavior drives the top line.
What do we need to implement CBCV? In addition to the usual financial statement data, two things are required: a model for customer behavior (what we call the customer-base model), and customer data that we feed into it. The model consists of four interlocking submodels governing how each customer of a firm will behave. They are:
Bringing these models together enables us to understand the critical behaviors of every customer at a firm—who will be acquired when, how much they’ll spend over time, and so on. Summing up all the projected spends across customers gives us our quarterly revenue forecasts. Together, these models can produce much more precise estimates of future revenues streams—and from that, one can make much better estimates of what a company is really worth.
This basic model is universal, no matter what kind of business a company is in. Exactly how it is specified, however, depends on the company’s business model—in particular, on whether the company is subscription-based or not. At a subscription-based business, such as a gym or a telecommunications firm, managers generally know how much customers will spend each month, and they are able to directly observe when customers churn out, because they literally cancel their contracts and close their accounts. This simplifies how the retention and purchasing submodels are built.
Most companies, however, are characterized by discretionary (that is, nonsubscription) purchasing and unobservable customer churn. If you have an Amazon account but decide never to buy from the company again, for example, it’s difficult for anyone inside or outside Amazon to immediately recognize that. Marketers call this latent attrition. Accounting for it requires more-complicated submodels, but marketers have developed methods for predicting it extremely well.
Although this methodology may seem daunting, it’s relatively simple to get going, and it can be refined and extended as appropriate for particular business contexts.
Let’s peek inside the black box through an example. Imagine that you’re the founder of a young, fast-growing, subscription-based meal-kit company. In its first four months of operation, your company generated $1,000, $2,500, $4,500, and $7,000 in total revenues respectively. You would like to understand what this means for future revenues and the overall viability of your business. As a start, you want to forecast revenue in month five.
Let’s suppose that active customers pay a flat fee of $100 per month for meal kits delivered over the course of the month, and that the company acquired 10, 20, 30, and 40 customers, respectively, in its first four months of operation (100 in total). Half the acquired customers churned out in their first month; all customers who did not churn out in the first month have remained.
The first step in forecasting month five revenue is to figure out how much revenue will come from retained customers. Of the 100 customers acquired over the first four months, half, or 50, will still be with the company in month five if historical retention trends persist. Thus, the portion of month five revenue from retained customers is $5,000 (50 x $100). The next step is to forecast how much revenue will come from new customers. Assuming that acquisition trends continue, you can expect an additional 50 customers, representing $5,000 of revenue. By adding up the two forecasts, you arrive at a total monthly revenue of $10,000.
Using the CBCV approach, revenue numbers no longer exist in a vacuum. Instead, they are a direct function of a small set of behavioral drivers—in this example, total customers acquired, retention dynamics, and average revenue per user (ARPU). This framework makes revenue forecasting easier and serves as a diagnostic, helping managers and investors understand where the value creation is coming from (and what questions to ask when results are out of line with expectations).
Teenie Harris Archive/Getty Images
Duke Ellington signing autographs in Pittsburgh, 1946
Of course, few companies will have such simple models and neat patterns as our meal-kit example. Our purpose here is to outline the general mechanics of the approach, as extensions of it follow naturally. Suppose, for example, that your firm has tiered pricing (it also offers a second plan that delivers twice as many meals a month for $189). In that case, you would need to account for variable ARPU from period to period. If the firm allows customers to skip deliveries or make discretionary purchases, you would need to track order frequency and average spend per order. If the firm pivots to sell meals à la carte instead of on a subscription basis, you’ll need to use a model that predicts how often customers will place orders. These extensions add complexity to the model, but the basic process to incorporate them would be the same as in the example above. If you want to extend the time horizon beyond month five, you can repeat the calculation for multiple months. That gives you a long-term revenue forecast, which is vital for corporate valuation.
For an in-depth discussion of the CBCV methodology in complex scenarios, see our academic papers “Valuing Subscription-Based Businesses Using Publicly Disclosed Customer Data” (Journal of Marketing, October 2016) and “Customer-Based Corporate Valuation for Publicly Traded Non-Contractual Firms” (Journal of Marketing Research, March 2018).
The richness of the insights that can be derived from CBCV depend on how much access the person performing the analysis has to internal company data. A corporate executive would have full visibility of all customer data. A private equity investor assessing an acquisition target would typically have access to transactional and CRM data. For subscription firms, that would include the length of contracts, periodic payments, and observable churn; for nonsubscription firms, it would include the timing and size of each individual purchase. Access to other behavioral data, demographics, marketing touchpoints, service interactions, and the like would further enrich the CBCV analysis.
For those on the outside looking in—hedge funds, Wall Street analysts, regulators, and others—detailed customer data might be impossible to obtain on a regular basis. They may, however, have access to the firm’s customer cohort chart, or C3, which tracks revenue by acquisition cohort over time and shows how total customer spending changes as each cohort ages. (For an example, see the exhibit “C3: A New Tool for Corporate Valuation.”) Many large, reputable firms (both subscription and nonsubscription) have begun to disclose their C3, among them Slack Technologies, Dropbox, Lyft, and luxury marketplaces the RealReal and Farfetch. A firm’s C3, along with the number of active customers and the total number of orders, is sufficient to give investors a good understanding of customer behavior.
The customer cohort chart is straightfoward: total revenue, period by period, broken down by customer acquisition cohort. Though its format may vary, the C3 is increasingly finding its way into companies’ public filings, giving investors a powerful tool for gauging what a company is really worth. This example of a C3 comes from Revolve Clothing’s 2019 SEC filing.
If a firm can’t or won’t release its C3, investors should press it to reveal four key metrics: the number of active customers (in total and the percentage from tenured customers, or customers who have been with the firm for over 12 months); gross acquired customers over the most recent period; revenue (total and percentage from tenured customers); and the number of orders (total and percentage from tenured customers).
While we would strongly encourage firms to disclose more, having three or four years’ worth of these disclosures (from past filings) is enough to run a CBCV model and assess the overall health of a company’s customer base, albeit with greater uncertainty about future revenues.
Few companies currently provide all the data outsiders need to perform CBCV, for a variety of reasons. First, disclosure of customer metrics is voluntary, and companies feel little to no pressure to make them available. Second, there is little consensus about which customer metrics are the most informative and how those metrics should be calculated and reported. And finally, policy makers and regulators have been largely silent about these issues, leaving disclosure to companies’ discretion.
Unfortunately, executives often have a “less is more” mentality regarding disclosure. They fear that additional disclosure, however aggregated the numbers may be, could put them at a competitive disadvantage or open them up to potential litigation or regulatory scrutiny. Successful firms worry about how investors will react if the metrics they’re disclosing start going in the wrong direction. And customer-level forecasting often remains siloed in the marketing department; managers in finance and related functions are unaccustomed to incorporating customer behaviors in their revenue forecasts and are more comfortable using traditional methods.
In the absence of investor pressure and regulatory standards, firms can arbitrarily choose which metrics to disclose, generally selecting those that paint an overly rosy picture for the investment community. The metrics are often defined improperly, based on faulty assumptions, or framed incorrectly.
Think about the story your customer metrics would tell if disclosure were required.
Consider Peloton, which sells high-end home-exercise equipment and monthly subscriptions to streaming-video fitness classes. When it filed its pre-IPO S-1, in August 2019, it chose to disclose its customer lifetime value (CLV) per subscriber, boasting a CLV of $3,593 in its most recent fiscal year. To its credit, Peloton also disclosed the underlying formula it used to compute its CLV, but that formula left much to be desired. The most glaring problem was that it did not account for the time value of money, and instead simply added more than 13 years’ worth of future cash flows without discounting them. Applying even a modest discount rate would slash its CLV by more than 50%—a drop with significant implications for the health of the customer base. As more firms voluntarily disclose customer metrics, analysts must be vigilant about vetting data that may be misleading or is mostly window dressing.
Although Peloton’s metrics are far from perfect, they nevertheless represent an encouraging shift toward transparency around customers that will be good for shareholders, companies, and customers. Shareholders will increasingly rely on customer data to evaluate potential investments as more purchases are made online and traditional brick-and-mortar metrics, such as same-store sales, decline in relevance. Executives can use customer data to build the case for investing in activities that will generate long-term value for the firm and to communicate to shareholders the impact of those investments on CLV and other long-term metrics. Customers will be treated as strategic assets whose value should be cultivated over the long term. This mindset will be a welcome change from the status quo, in which shareholders, lacking the information needed to assess long-term customer profitability, compensate by pushing firms to hit short-term performance measures.
Until the CBCV revolution fully takes hold, what does all this mean for you? If you are an investor, don’t ignore the customer-related metrics that may be tucked away in financial reports; actively seek them out. If the data you need isn’t disclosed, demand it, or find alternative sources that can serve as effective proxies. Focusing on unit economics will almost certainly reveal opportunities you can exploit.
If you’re an executive and you aren’t currently disclosing your customer metrics, start thinking about the story they would tell if disclosure were required. If you would not be proud of your metrics as they stand, this is your golden opportunity to refocus on and improve the health of your customer base in the dark. It may not be long before market participants demand sunlight.
Daniel McCarthy is an assistant professor of marketing at Emory University’s Goizueta Business School and a cofounder of Theta Equity Partners, a customer-based corporate valuation solutions provider.
Peter Fader is the Frances and Pei-Yuan Chia Professor of Marketing at the Wharton School of the University of Pennsylvania, a coauthor
of The Customer Centricity Playbook, and a cofounder of Theta Equity Partners.
Vanguard, the mutual fund company known for its low-cost index funds, frequently shows up on lists of organizations with the most-loyal customers—and that’s no accident. During his tenure as CEO, from 1996 to 2008, Jack Brennan emphasized what he calls the virtuous circle of attracting loyal clients who stick around and create new ones through word of mouth. Now Vanguard’s chairman emeritus, he is a leading voice on corporate disclosure issues and has held positions at the Financial Accounting Foundation, the Financial Industry Regulatory Authority, and the Investment Company Institute. Brennan spoke with HBR about why companies should want to tell investors more about their customers—and how soon they may be required to. Edited excerpts follow.
HBR: How did you become interested in customer value?
Brennan: In our business, the highest-cost thing we do is attract and onboard new clients. So why wouldn’t we be driven to increase the loyalty of those clients? This isn’t differential calculus. When customers leave, you have to replace them, and we’d prefer to avoid that expense. So we have followed Bain & Company’s loyalty research very closely for many years. In the years since I became Vanguard’s CEO, managing for loyalty has gone from an intuitive idea to a conceptual goal to an operational practice. Across businesses in general, this is still underexposed and undervalued as a concept. Rob Markey’s new work on using loyalty metrics to better understand and manage the value of a firm is the next evolution of this idea.
Where do you see these new techniques being used?
The place where I’ve seen this play out most aggressively is in private equity. If you talk to private equity firms about the due diligence they engage in when they’re buying a company, the customer base is a critical part of what they’re looking at. It’s intense. They’re asking senior management: What’s the nature of your customer base? How are you acquiring customers? How are you losing them? Which ones are profitable? They’re interested in individual customer accounts and transaction data. A debate is currently going on about whether investors who are buying not an entire company but, say, 1,000 shares should have access to some of the same information about the core value of the customer base that private-market investors see in their due diligence process. I think they should.
Are Vanguard’s portfolio managers using customer valuation tools?
I’m not close enough to their work to know, but I do see other public-market investors using them. One portfolio manager I know runs a very concentrated fund—it holds eight to 10 stocks at a time, with essentially zero turnover. Because he’s holding very few stocks for a very long time, he thinks more like an owner. He approaches each investment as if he’s buying the whole company. Among the first things he does is conduct a deep study of the customer base—its breadth, its depth, its growth. He even hires third parties to help with the analysis. That’s an example of how investors don’t simply rely on the customer data that the company discloses—they actively seek out data on their own. If you walk into a Walmart, there’s usually somebody in there counting something for an analyst. Investors sometimes even hire investigative reporters to dig up information. They’re trying to learn as much as they can about a company’s customers.
How do regulators decide whether or not to require more disclosure on customer metrics?
I’ve been working on issues around financial disclosure for many years, and it’s a fascinating process. The Financial Accounting Standards Board (FASB) is always balancing what’s valuable to investors against what’s overly burdensome or competitively disadvantageous to companies. Do shareholders have access to enough material information to judge the company’s risks and performance? How much is too much disclosure? What’s verifiable? Regulators are leery of being presented with non-GAAP measures—metrics that don’t conform with generally accepted accounting practices. They worry about clutter risk—the distraction created by too much data that’s not very meaningful to investors. Companies worry about being forced to reveal information that could help their competitors. There’s always tension and stress around the prospect of new reporting requirements, and it’s not irrational. But the debate that goes into standard setting is healthy and valuable.
Amazon has millions of Prime subscribers, but it won’t say exactly how many, so analysts are left to guess. What’s the harm in disclosing that number?
Prime members are obviously a critical part of Amazon’s business model. But executives may choose not to disclose the number because they don’t want investors to fixate on any one metric. Think about the way investors watch Netflix subscriber counts. Amazon probably wants to avoid investors’ reacting every time Prime subscriber numbers go up or down. Top management might also argue that disclosing the number puts the company at a competitive disadvantage—even though it doesn’t really have a head-to-head competitor.
What does the timeline for more disclosure look like?
If shareholders demand disclosure, it will get the attention of the Securities and Exchange Commission, and FASB will weigh in on whether it can be done well. I do think regulation will happen; the question is at what pace? It always feels too slow to me. I think it is still years away, but over time, the market will demand it. I don’t think you’ll see standardized, fine-tuned Net Promoter Scores as part of corporate financial statements any time soon, but some information about customers will probably be required in the not-too-distant future in the management disclosure and analysis (MD&A) section of the annual report or in the footnotes. That’s how regulators have treated disclosures about executive compensation and environmental, social, and governance data. Requirements could begin with something as simple as “We had X number of customers on December 31 of last year and Y number on December 31 of this year,” with a little bit more granularity. Companies that are proud of their customer base and loyalty have an incentive to disclose more, of course. Creating a virtuous circle of loyal customers is one of those self-evident ideas that you can’t emphasize enough.
The Loyalty Economy
Research & References of The Loyalty Economy|A&C Accounting And Tax Services
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