| 6.9°C Dublin

Facebook must learn to balance its commercial and customer interests


Facebook float: Subsequent share plunge raises doubts about the validity of the business model

Facebook float: Subsequent share plunge raises doubts about the validity of the business model

Facebook float: Subsequent share plunge raises doubts about the validity of the business model

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 monetising 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 customised ads.

Yet the pillars of Facebook's business model -- monetising 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, customisation 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. Although there are people who oppose data sharing and advertising of any kind, most consumers benefit from good advertising.

Every transaction, whether social or commercial, involves search costs. The monetary price of a good 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 in the right place, 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 can use customer- purchase data to design customised advertising of other products. It still doesn't have access to data on purchases on other sites or offline, and 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 between 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 on the matching process 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 funnelling 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' behaviour 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 customisation, 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 inputs such as labour 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 only 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 are likely to enjoy or find useful. Most people would be willing to pay to view advertising if they knew the ads were tailored to their needs and desires.

Some have criticised Facebook for moving too slowly to monetise 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.

Finally, much of the concern about user-data privacy is irrational in ways that economists would recognise. For instance, there is widespread worry that the availability of medical histories or driving-style information would increase insurance rates, even though rates would go down for at least half the population.

As consumers become aware of these benefits -- and learn when and what to share -- they will be increasingly less concerned about privacy.

Gregory La Blanc is a lecturer at the Haas School of Business and Boalt Hall School of Law at the University of California, Berkeley.

Indo Business