Do You Know What Your Customers Value?

Idea in Brief The Problem Most executives think they understand what customers value because they spend significant time gathering feedback, monitoring competitors, and tracking market trends. Yet they often rely on intuition to interpret that information, leading them to prioritize the wrong customer needs. Why It Happens Behavioral biases cause leaders to overweight salient information—recent customer complaints, competitors’ actions, industry trends, or personal experience—while underestimating the factors that actually drive customer value. The Solution Use statistical models to identify the small number of customer value drivers that have the greatest impact on revenue and profitability. Then align strategy, employee activities, and investments around those priorities; eliminate low-value initiatives; and communicate the strategy externally only after successful execution. Most companies work hard to get close to customers. Managers also regularly compare how their product offerings stack up against the competition, so it’s not surprising that executives are confident about their knowledge of customer needs and whether they’re satisfying those needs better than their rivals do. Take the CEO of one $320 million software services company who told us, “Our sales team meets with key accounts monthly and responds immediately to their needs. The COO monitors competitors, and we’re at the forefront of almost every industry association. Last year we started more than 50 initiatives to stay ahead of the game.” Another case in point is the chief operating officer of a $12 billion oil-field-services company who declared, “I have more than 23 years of industry experience as a client and vendor, in the field and in purchasing. With all due humility, I know where customers and competitors stand.” But is such confidence justified? To find out, we undertook a seven-year study of 72 companies in a variety of industries (including retail, food services, manufacturing, distribution, industrial services, software, education consulting, and fundraising), whose annual revenue ranged from $10 million to $20 billion. We interviewed the CEOs of the companies and 187 of their senior executives, observed more than 3,000 hours of strategy meetings (including 83 strategy retreats), surveyed 24,000 customers, and examined the financial statements and regulatory filings of an additional set of public companies. What we saw was that executives did indeed spend a great deal of time listening to customers, monitoring competitors, and looking to spot industry trends. But we found that rather than using a scientific approach to interpret the information they gathered, they routinely took cognitive shortcuts. As new factors surfaced and different executives focused on different ones, companies’ strategies for winning customers shifted from year to year, confusing customers about the underlying value propositions the firms were offering. As customers switched to competitors, sales dwindled. Meanwhile, the costs of pivoting caused margins to shrink, customers didn’t get what they wanted, employees were burdened by the need to work on multiple initiatives that added little value, and shareholders earned average or below-average returns. In this article we present the findings from our research and offer an explanation rooted in behavioral science for the phenomenon we describe. We’ll then outline a five-step framework that will help executives sharpen their focus on what customers really value, using examples from companies we’ve studied or worked with to demonstrate how it works. What Executives Get Wrong If companies don’t know what their customers really want, it’s not because they lack data. At 93% of the companies we studied, executives spent four to 12 hours a week, on average, gathering direct customer feedback, monitoring competitors, and analyzing trends. As we’ve noted, nearly all of them felt confident that these activities ensured that they were focused on customer needs. Unfortunately, it turned out that most of them also relied on intuition and personal experience to interpret that data. Only 2% of executives and employees in our surveys said their companies had formally identified the features in their value proposition that customers most appreciated (such as product quality, purchasing experience, and after-sales service) and had assessed their relative importance to customers. None had quantified how much each of these “value drivers” actually affected revenue or margins. Even when companies did identify and compare value drivers, there was little internal agreement about which were the most important. When we asked executives in each company to rank its drivers of customer value, fewer than 10% of their responses agreed. When the employees of each company were asked what customers valued most about their firm’s offerings, virtually all listed the same things: quality (100%), service (100%), sustainability (100%), competitive price (98%), AI leadership (98%), customer experience (96%), communication (91%), innovation (91%), safety (88%), and project execution (87%). (Note that many of the firms we studied were B2B businesses, which explains the high rankings of AI leadership and project execution.) When asked which was their company’s priority, 96% of the employees responded “all of the above.” Only 4% provided a rank ordering. Gabriele Galimberti’s project Toy Stories examines childhood through portraits of children from more than 50 countries with their favorite possessions. We also surveyed the customers of the companies in our study, asking them to rank eight common value drivers we’d identified. That allowed us to estimate a lift potential for each driver, or the extent to which it statistically improved overall customer value. Next we obtained the actual revenue and margin data on each customer from company accounting records so that we could examine the link between overall customer value and actual sales. We could then see which drivers contributed the most to financial performance. The results were striking. The executives at the companies we studied were making the same two mistakes routinely: They prioritized the wrong drivers. Across all companies we found a negative or zero correlation between lift potential and the executives’ rankings of value drivers. For example, executives at one education services company rated all eight drivers as equally valuable to customers. When we surveyed its customers, however, one driver, acknowledging and resolving customer issues within 24 hours, had a lift potential of 85%, and another, on-site training, had one of 11%, while the rest had little or none. We also found that executives typically underestimated how much improving a single driver could increase overall customer value. At one industrial services company, for example, executives predicted that improving employees’ compliance with safety protocols on clients’ job sites would increase overall customer value by 2.3%. Data from customer polls, however, suggested it would create a 19.5% lift. To confirm our findings, we did a large-scale study involving surveys of 18,840 customers across 104 publicly traded B2B companies. In it we compared what customers actually valued to what executives thought customers valued (which we gleaned from analyzing the companies’ 10-K statements). We found a striking disconnect: In 72% of cases, executives’ beliefs had low, no, or a negative correlation with actual customer priorities. That was worrying because our analysis also showed that the more company executives and customers agreed on what drove customer value, the higher the company’s revenue, gross margins, free cash flow, and market value were. In fact, each 12.5-point improvement on a scale from -100 (a complete mismatch between what the company thinks customers value and what they really do) to +100 (a perfect correlation) increased revenue by 9.2%, gross margins by 5.2%, free cash flow by 8.8%, and market value by 11.1%. They switched priorities. At 36 companies we asked executives to rank their value drivers by importance for four consecutive years. We found that their ordering changed drastically from year to year, something we also saw in a separate study of 10-K statements filed by 4,540 publicly traded companies. A natural-language analysis of the statements over a 21-year period (1999–2019) revealed that 74.6% of companies changed their customer value priorities, with 85.5% of that group switching every two years. For example, in 2015 executives at Acxiom, a customer- data platform company, ranked safety as the second most important of eight value drivers, but in 2016 they ranked it seventh, while corporate social responsibility went from eighth place to second. Similarly, from 2015 to 2016 at the U.S. medical technology company Becton Dickinson, quality shifted from the top-ranked driver to the eighth, and after-sales service went from seventh place to first. Of course, a company’s priorities should evolve as markets and customer needs change. But over time customers’ rankings of value drivers are much more stable than executives’, making it hard to read the rotating priorities as rational adaptation. In our 36-company study, executives’ rankings showed near-zero correlation with what their own customers actually said they valued—meaning executives didn’t even grasp customers’ reality in the first place. Swings of the kind just described—quality from first to eighth in one year, CSR from eighth to second—look more like reversals of managerial attention than reversals in the market. The conclusion is inescapable: Executives aren’t processing information on customers properly. This results in frequent pivoting that burdens employees, confuses customers, and delivers poor investment returns. Why It Happens In 1979 the psychologist Robyn Dawes published a landmark paper titled “The Robust Beauty of Improper Linear Models in Decision Making.” Daniel Kahneman, the Nobel Prize–winning author of Thinking, Fast and Slow, hailed it as “an instant classic” and noted, “Social science has yet to catch up with his original insight.” The paper upended the prevailing wisdom that the best way to make important decisions was to rely on experienced experts: Let them identify key variables, consider the data on them, and arrive at a judgment. Dawes showed that statistical linear models, which mathematically weight inputs to predict an outcome, consistently outperformed expert judgment. This finding held across multiple domains, including graduate admissions committees evaluating applicants, businesses predicting risks, and doctors assessing disease severity. In every case the statistical models were superior—not because experts lacked knowledge about the input variables that mattered but because they were unable to correctly rank the variables’ impact on outcomes. Our research uncovered two systematic tendencies driving such missteps. Reliance on salience. People have a propensity to focus on top-of-mind information—the customer complaint from last week, a major competitor’s announcement, what worked at an executive’s previous job, or a board member’s pet concern. In all 83 strategy retreats we observed, executives prioritized factors that were salient over factors that were statistically consequential in driving customer value. No company used a statistical model to assess the factors. Since different factors were salient to different executives, there was little agreement among them, and they tended to include more and more factors in the strategy process as a way to accommodate one another. The strategic frameworks executives commonly reached for—SWOT, the 4P’s, the balanced scorecard—were of little help: They organized the factors but offered no way to rank them. During the retreats, two sources of salience became clear: Listening to customers. Executives set great store by the customer feedback they obtain directly. A classic example is Burger King’s U.S. president, Tom Curtis, who posted his cell phone number online and fielded more than 20,000 calls and texts from people complaining about soggy nuggets, smushed Whoppers, the chain’s app, and even his haircut. Curtis told The Wall Street Journal that “those one-on-one interactions will give you more insight than any spreadsheet or PowerPoint”—a near-perfect rejection of Dawes’s insight. Each complaint is maximally salient in the moment, but without a statistical model, there’s no way to know whether or not addressing it would be likely to increase customer value. The executives we surveyed likewise routinely relied on notes from customer meetings, key account sessions, feedback from the sales team, and word clouds from social media to support their recommendations. Competitive benchmarking. An analysis of competitors, including their offerings, pricing, and activities, was discussed at more than 80% of the retreats, and 20% to 50% of all initiatives proposed arose from executives’ desire to combat rivals. In most cases executives sought to match competitors point by point, producing strategic convergence rather than differentiation. Unsupported assumptions. Executives frequently drew conclusions about chains of cause and effect without any empirical evidence. For instance, an HR executive at a $200 million software company asserted, “If we invest in employee engagement, employees will serve customers better, customers will be more satisfied, and sales will increase.” Given that evidence suggests that employee engagement is positively associated with increased sales, the argument was certainly plausible. So the company decided to spend more than $10 million on employee engagement initiatives. Gabriele Galimberti Unfortunately, the hoped-for sales improvement didn’t materialize. This could have happened because the initiatives were poorly executed, but when we surveyed the company’s employees and customers, we found no link between employee engagement and customer satisfaction. Fewer than 12% of the employees interacted with customers. The leading factors in customer satisfaction were pricing and billing (cited by 43% of customers) and product upgrades (26%). When the company shifted its focus from employee engagement to pricing and billing and upgrades, customer satisfaction, employee engagement, and sales increased by double digits. This suggests that executives would be well advised to scientifically verify even very plausible hypotheses before acting on them. The Fix: Achieve More by Doing Less If the problem is that human judgment fails at information integration, the solution isn’t to think harder or apply more judgment. It’s to retool the customer strategy process so that executives use statistical models to understand what they’re doing wrong and how to address it. Through trial and error with multiple firms, we have developed a five-step process that will improve companies’ returns. 1. Surface the misalignment. The first step is to confront executives with hard evidence that customers don’t value the things leaders think they do—and that, as a result, employees spend too much time on work that doesn’t add customer value. Take ITI Manufacturing, a $12 million offshore manufacturer we advised. When we met with its executives in 2020, the company was grappling with stalled sales. An initial survey found that 97% of employees reported alignment on customer strategy. But when we asked them detailed questions, actual agreement was low (23%). They described the company’s strategy using more than 65 phrases, such as “low pricing,” “meeting quality specifications,” “on-time delivery,” “customer support,” “industry experience,” and “global footprint.” The survey revealed that ITI’s strategy was driven by intuitive leaps from customer feedback sessions, salespeople’s salient beliefs, industry trends, and the desire to copy competitors. The result: Employees were spending just 24% of their time on customer-facing work, the remainder being consumed by firefighting, strategy initiatives, and corporate management tasks. A surplus of initiatives is a good indicator that a company lacks focus. Take Swagelok Southeast Texas (S-SET), a fluid and assembled systems distributor in Houston affiliated with the $2 billion privately held Swagelok Company. (We worked with S-SET as advisers.) Before 2022 the company had a declared strategy of focusing on the customer experience. But because there was no real alignment over what factors drove the customer experience, the implementation involved 42 initiatives, a large number for a company with roughly $50 million in sales. While S-SET targeted multiple competing value drivers, sales remained stubbornly within 1% of the industry average. “It was eye-opening to see the gaps in our strategy process and the preconceived notions we had about them. We are a good company, but we could become great if we could align on our customers’ top priorities, let go of unproductive initiatives, and help employees focus,” observed Chris Jones, the CEO. 2. Determine value drivers’ lift potential. Once executives agree that they’re not focused enough, we find, they more readily accept the idea that lift potential should determine the company’s top two or three priorities. In the fall of 2021, ITI carried out a consumer study that radically mobilized executives. In the study customers rated ITI on overall value and on how it delivered on eight performance drivers (sales process, pricing, quality, communication, sustainability, safety, project management, and ongoing support). A statistical model showed that overall customer value was primarily created by two factors: communication (keeping customers updated weekly about their project status) and ongoing support (resolving issues), with the remaining factors providing nearly zero lift. A second linear model examined the correlation between overall value and actual sales. It predicted that the company could increase sales 9.8% if it improved on those two value drivers. Product quality, low pricing, and sustainability—factors the legacy strategy had emphasized—provided very little additional lift in customer value and, by extension, overall sales. Those factors were seen merely as table stakes by customers in ITI’s sector, and differences between companies on them were marginal. Based on those insights, many initiatives and internal activities were paused or eliminated, freeing up more than 30% of employees’ time. S-SET likewise conducted a customer study to construct a linear model to predict increases in overall customer value. It showed that two factors—sales process and ongoing support—had the most potential to improve it and thus generate an estimated 18.6% increase in sales. Within sales, the largest increase in value came from providing customers with a timely quote. Despite skepticism among some executives, Jones created a strategy for earning customer confidence through efficient quoting. “We’re pretty good at many things, but now we will be excellent at the one thing that matters most to our customer—rapid quoting,” he declared. 3. Incorporate value drivers into daily work. The next step is to slowly reconfigure employees’ daily activities around the drivers that provide the most lift in customer value. At ITI the CEO, Joshua Robinson, examined every employee’s job to identify where it intersected with customer updates, in which information from China, Vietnam, and South Korea was translated into English, sent to the U.S. office, verified for accuracy, and summarized in friendly emails. Over the next two quarters, those updates, sent every Wednesday, were integrated into everyone’s job description. “Previously, if a customer called and wanted an update, we’d give one. But proactively providing them with an update every week was new,” Robinson said. While customers received fewer than 30 updates in 2021, they received 2,384 in 2022, 3,073 in 2023, and 3,524 in 2024. “Customers love weekly updates—they have the visibility and predictability they need,” the company’s chief sales officer told us. “The repeat business and referrals have grown our customer base and increased our pricing power.” Gabriele Galimberti S-SET applied the same principle. Jones deconstructed rapid quoting into its component tasks to understand how employees’ daily work contributed to it and how each executive could help employees excel at it. The director of IT and finance, Peter Hory, ensured that all 22 service reps had fast computers and top-notch quoting software. The VP of human resources designed 12 training programs to enhance quoting skills. The chief sales officer had the internal database of more than 22,000 SKUs updated to eliminate duplicates, and the director of customer experience spent hours on the floor troubleshooting quoting glitches. Within two quarters, quoting time decreased from an average of 18 hours (roughly three workdays) to fewer than five hours. Now, four years later, 90% of quotes are made in three hours or less. Today key clients have an app providing instant quotes, which they can accept to create a purchase order, and an AI-driven bot answers service reps’ queries to reduce quoting time. “Our customer service reps are totally focused on excelling at only one thing—rapid quoting. We are no longer trying to copy competitors or fish for more things to do,” said Jones. 4. Cut non-value-adding activities. All executives know they should stop doing unnecessary things. But without a valid mechanism for determining what’s extraneous, the not-to-do list becomes a political football. “Yes, let’s cut—but not my program,” executives say. This is where science changes the game. Once a value driver’s lift potential is measured at near zero, it becomes clear that initiatives, meetings, and work connected to it should be redirected to higher-value-adding activities. In the four years after ITI narrowed its focus to weekly updates, its overall sales grew to be 19.3% higher than its industry peers’, its margins improved by 43%, and its sales per employee increased 17%. Before the reset in 2021, ITI’s stock price basically tracked the S&P and small-cap Russell 2000. But by 2025 the share price had increased by 162%, while the S&P 500 had risen 34% and the Russell 2000 had risen 8%. S-SET had a similar experience: When quoting times improved, sales reps stopped chasing quotes down, which allowed them to spend 35% more time on selling and solving customer problems. Since then, inventory turnover has improved dramatically, and over the past four years sales increases have exceeded the industry average by 12%, while sales per employee have risen by 52%. 5. Don’t market the strategy until you’re actually executing it. Most companies communicate their strategy externally before they’ve delivered on it—they make a promise and hope that execution catches up. But premature messaging to the market, before a company has achieved excellence on its selected drivers, disheartens employees and trains customers to discount promises. S-SET deliberately waited to communicate its new focus until its quoting time had decreased to an average of fewer than five hours. Only then did the marketing team brand the strategy and retrain the sales team around it. “We used to reflect back customers’ desires in our sales talk. But now we discuss the value they get from rapid quoting—lower project downtime, greater savings, and fewer headaches. It’s been a winner,” explained a salesperson. Today, S-SET uses its “Ensuring Customer Confidence with Rapid Quoting” strategy on all fronts. Employee bonuses are linked to overall quoting time. “Excellence on rapid quoting is a focus we live and breathe now. It’s not a strategy; it’s our company’s DNA,” explained Jones. ITI sharpened its marketing message to “Visibility, Predictability, and Accountability” after it had achieved implementation excellence. “The visibility and predictability come from weekly updates, and the no-hassle issue-resolution policy holds us accountable to customers,” Robinson explained. “For years everything customers wanted became strategy. Every idea pushed by executives became an initiative. We were overburdened and cluttered. The discipline of a linear model clarified what mattered. By excelling on two things, we increased pricing power by 20% to 30% while eliminating wasteful strategic initiatives and cutting costs.” Impressive returns aren’t confined to small operations like ITI and S-SET. We’ve seen far larger organizations get similar results. One bank with an $80 billion market cap that we worked with saw customer satisfaction rise by 18% over a six-year period, which drove revenue growth of 33% and a margin improvement of 16%. Those numbers translated into a stock price increase of 200% (versus 140% for the Dow Jones) in the same period. The bank had focused heavily on two value drivers that surveys showed had significant lift potential: short waiting times in the lobbies and secure online transactions. Its CEO noted: “Strategy planning had always been guesswork based on intuition and gut feel. The science embedded in developing the strategy, testing different implementation pathways using randomized experiments, and measuring success with statistical precision was groundbreaking. We won’t go back to the legacy ways.” . . . Executives don’t lack information. They have too much of it. What they lack is a valid way to prioritize it—and the discipline to act on those priorities rather than on instinct. The tools to do so are not exotic. A statistical model that predicts customer value from survey data is, in principle, no different from the algorithms Netflix uses to recommend content or the models insurers use to price risk. The difference is that Netflix doesn’t convene a committee of experts to override its algorithm every quarter. Yet this is how too many companies approach customer strategies—and it’s why they cycle through resets, pivots, and clutter while competitors, sometimes with fewer resources and less talent, focus more clearly and grow. While all executives aim to have a clear focus, without a science-based mechanism for determining it, that goal is just an aspirational platitude. A statistical approach replaces the platitude with a testable answer.

Do You Know What Your Customers Value?

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