Customers who pay little or nothing and are subsidized by another set of customers are essential to a vast array of businesses, including shopping malls, real estate brokerages, information technology providers, auction houses, print and online media, and employment and dating services. According to one estimate, this business model accounts for a majority of the revenues of 60 of the world’s 100 largest companies.1 With the explosion in the number of free services offered on the internet, the prevalence of so-called two-sided markets is likely to grow.
What Is a Free Customer Worth?
Reprint: R0811G
Free customers who are subsidized by paying customers are essential to a vast array of businesses, such as media companies, employment services, and even IT providers. But because they generate revenue only indirectly, figuring out the true value of those customers—and how much attention to devote to them—has always been a challenge.
Traditional customer-valuation models don’t help; they focus exclusively on paying customers and largely ignore network effects, or how customers help draw other customers to a business. Now a new model, devised by professors Gupta, of Harvard Business School, and Mela, of Fuqua School of Business, takes into account not only direct network effects (where buyers attract more buyers or sellers more sellers) but also indirect network effects (where buyers attract more sellers or vice versa). The model calculates the precise long-term impact of each additional free customer on a company’s profits, factoring in the degree to which he or she brings in other customers—whether free or paying—and the ripple effect of those customers.
The model helped an online auction house make several critical decisions. The business made its money on fees charged to sellers but recognized that its free customers—its buyers—were valuable, too. As competition heated up, the company worried that it wasn’t wooing enough buyers. Using the model, the business discovered that the network effects of buyers were indeed large and that those customers were worth over $1,000 each—much more than had been assumed. Armed with that information, the firm increased its research on buyers, invested more in targeting them with ads, and improved their experience. The model also helped the company identify the effects of various pricing strategies on sellers, showing that they became less price-sensitive over time. As a result, the company raised the fees it charged them as well.