Gregory La Blanc
Facebook’s disastrous initial public offering has led to an increasing consensus that the social networking site was overpriced and that its business model is flawed.
Some attribute the debacle to issues raised in the company’s prospectus, such as the difficulty of monetizing mobile technology. Others have pointed to the slow growth in advertising revenue or questioned Facebook’s strategy of collecting vast quantities of data from its networked users to enable customized ads.
Yet the pillars of Facebook’s business model — monetizing customer data and social media — are here to stay, and the company is among the best positioned to take advantage of both.
Facebook’s strength relies on network effects, economies of scope, discrimination, customization and market power. Most people understand the business to work like this: Users derive the benefits of social sharing. The price they pay is to hand over personal data that is sold to advertisers.
The two major threats to this model are that users will increasingly become concerned about privacy and turned off by advertising, which will slow the growth of both the data and ad revenue.
This misrepresents the nature of the exchange. There are people who oppose data sharing and advertising of any kind, but most consumers benefit from good advertising.
The retailer John Wanamaker is often credited as saying, “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” He was optimistic. It is doubtful that traditional media advertising is even that effective, and the online variety doesn’t necessarily work any better. Advertising isn’t made more efficient by moving into cyberspace but by using data to identify the appropriate audience.
Every transaction, whether social or commercial, involves search costs. The monetary price of a product usually isn’t a measure of how much a customer has spent on it, nor does it accurately reflect what the producer received. The customer pays the monetary cost plus search costs, which can take the form of consumer research, product assessment and social validation. Sometimes these costs are monetary, but more often they involve time, effort and anxiety.
Similarly, you could say that the seller receives the price minus search costs. He must expend resources to ensure that there is an adequate supply of goods, educate the customer about the product and market and advertise it.
Whoever makes this matching process easier is in a position to charge for it. And whoever does it best is in a position to charge the most. This is where economies of scope kick in for Facebook. Most of the companies that have performed this matching process, whether they are brick-and-mortar or online retailers, have done so within a single domain.
These companies vertically integrate the advertising platform with the selling platform. For instance, Amazon.com can use customer-purchase data to design customized advertising of other products. It still doesn’t have access to data on purchases on other sites or offline, and it tries to drive all book purchases through its site.
This benefits not just Amazon but also the purchaser, who is often willing to pay a premium to reduce search costs and increase the likelihood of a better match of preferences and the item purchased.
Yet this form of matching is limited. Suppose purchasers of a particular book would like to know about a film? Or film lovers might be inclined to visit a new restaurant? Even if advertising contracts can be designed across domains, the matching is suboptimal without data sharing. These limitations that result from fragmented data are pushing companies toward greater scope, which explains the wider range of products offered through platforms such as Amazon and Apple. Still, they have trouble knowing what you do in your brick-and-mortar life.
Unlike the companies that integrate the selling and advertising functions, Google has been extremely successful at streamlining the matching process purely as an advertising platform. It does so by knowing specifically what people are looking for, but also by funneling as much as possible of the online activity through its own platform.
Facebook, like Google, aims to collect data on every aspect of its users’ behavior across numerous domains and not just online. These companies want to know what people purchase, what they like, what they read, where they’ve been and who their friends are. They have created applications that make it increasingly easy to aggregate personal data in a single location. They do so by ensuring that users are generating data even if they aren’t logged on to their sites. Ultimately, the more data that exists in one place, the better the matching process can work.
Facebook and Google now offer their services free and generate all their revenue from advertising. There are questions about the sustainability of this approach. After all, how many hugely valuable companies can rely entirely on advertising? Is there enough advertising to go around? And if advertising becomes more effective through targeting and customization, won’t advertisers be able to reduce their overall spending? Probably not.
By making every advertising dollar more effective, the marginal benefit of each dollar spent increases. When allocating resources, more will be spent on advertising relative to other input such as labor or materials. The more efficient the matching process becomes, the more resources will be devoted to matching. Products will derive more of their value from advertising, which will account for an increasingly large percentage of gross national product.
Facebook is beginning to figure out how to use the customer data it collects. If it succeeds, it will be able to weed through information, media and user-generated content, and advertising, and then deliver only the items individual consumers will enjoy or find useful.
Some have criticized Facebook for moving too slowly to monetize its data, but to keep its customers, it must continue to show that it has their interests at heart. The danger in going public too soon is that Facebook is trying to boost its numbers too quickly, before it has figured out the analytics.
Gregory La Blanc is a lecturer at the Haas School of Business and Boalt Hall School of Law at the University of California, Berkeley.