Archives For barrier to entry

Recent years have seen an increasing interest in incorporating privacy into antitrust analysis. The FTC and regulators in Europe have rejected these calls so far, but certain scholars and activists continue their attempts to breathe life into this novel concept. Elsewhere we have written at length on the scholarship addressing the issue and found the case for incorporation wanting. Among the errors proponents make is a persistent (and woefully unsubstantiated) assertion that online data can amount to a barrier to entry, insulating incumbent services from competition and ensuring that only the largest providers thrive. This data barrier to entry, it is alleged, can then allow firms with monopoly power to harm consumers, either directly through “bad acts” like price discrimination, or indirectly by raising the costs of advertising, which then get passed on to consumers.

A case in point was on display at last week’s George Mason Law & Economics Center Briefing on Big Data, Privacy, and Antitrust. Building on their growing body of advocacy work, Nathan Newman and Allen Grunes argued that this hypothesized data barrier to entry actually exists, and that it prevents effective competition from search engines and social networks that are interested in offering services with heightened privacy protections.

According to Newman and Grunes, network effects and economies of scale ensure that dominant companies in search and social networking (they specifically named Google and Facebook — implying that they are in separate markets) operate without effective competition. This results in antitrust harm, they assert, because it precludes competition on the non-price factor of privacy protection.

In other words, according to Newman and Grunes, even though Google and Facebook offer their services for a price of $0 and constantly innovate and upgrade their products, consumers are nevertheless harmed because the business models of less-privacy-invasive alternatives are foreclosed by insufficient access to data (an almost self-contradicting and silly narrative for many reasons, including the big question of whether consumers prefer greater privacy protection to free stuff). Without access to, and use of, copious amounts of data, Newman and Grunes argue, the algorithms underlying search and targeted advertising are necessarily less effective and thus the search product without such access is less useful to consumers. And even more importantly to Newman, the value to advertisers of the resulting consumer profiles is diminished.

Newman has put forth a number of other possible antitrust harms that purportedly result from this alleged data barrier to entry, as well. Among these is the increased cost of advertising to those who wish to reach consumers. Presumably this would harm end users who have to pay more for goods and services because the costs of advertising are passed on to them. On top of that, Newman argues that ad networks inherently facilitate price discrimination, an outcome that he asserts amounts to antitrust harm.

FTC Commissioner Maureen Ohlhausen (who also spoke at the George Mason event) recently made the case that antitrust law is not well-suited to handling privacy problems. She argues — convincingly — that competition policy and consumer protection should be kept separate to preserve doctrinal stability. Antitrust law deals with harms to competition through the lens of economic analysis. Consumer protection law is tailored to deal with broader societal harms and aims at protecting the “sanctity” of consumer transactions. Antitrust law can, in theory, deal with privacy as a non-price factor of competition, but this is an uneasy fit because of the difficulties of balancing quality over two dimensions: Privacy may be something some consumers want, but others would prefer a better algorithm for search and social networks, and targeted ads with free content, for instance.

In fact, there is general agreement with Commissioner Ohlhausen on her basic points, even among critics like Newman and Grunes. But, as mentioned above, views diverge over whether there are some privacy harms that should nevertheless factor into competition analysis, and on whether there is in fact  a data barrier to entry that makes these harms possible.

As we explain below, however, the notion of data as an antitrust-relevant barrier to entry is simply a myth. And, because all of the theories of “privacy as an antitrust harm” are essentially predicated on this, they are meritless.

First, data is useful to all industries — this is not some new phenomenon particular to online companies

It bears repeating (because critics seem to forget it in their rush to embrace “online exceptionalism”) that offline retailers also receive substantial benefit from, and greatly benefit consumers by, knowing more about what consumers want and when they want it. Through devices like coupons and loyalty cards (to say nothing of targeted mailing lists and the age-old practice of data mining check-out receipts), brick-and-mortar retailers can track purchase data and better serve consumers. Not only do consumers receive better deals for using them, but retailers know what products to stock and advertise and when and on what products to run sales. For instance:

  • Macy’s analyzes tens of millions of terabytes of data every day to gain insights from social media and store transactions. Over the past three years, the use of big data analytics alone has helped Macy’s boost its revenue growth by 4 percent annually.
  • Following its acquisition of Kosmix in 2011, Walmart established @WalmartLabs, which created its own product search engine for online shoppers. In the first year of its use alone, the number of customers buying a product on Walmart.com after researching a purchase increased by 20 percent. According to Ron Bensen, the vice president of engineering at @WalmartLabs, the combination of in-store and online data could give brick-and-mortar retailers like Walmart an advantage over strictly online stores.
  • Panera and a whole host of restaurants, grocery stores, drug stores and retailers use loyalty cards to advertise and learn about consumer preferences.

And of course there is a host of others uses for data, as well, including security, fraud prevention, product optimization, risk reduction to the insured, knowing what content is most interesting to readers, etc. The importance of data stretches far beyond the online world, and far beyond mere retail uses more generally. To describe even online giants like Amazon, Apple, Microsoft, Facebook and Google as having a monopoly on data is silly.

Second, it’s not the amount of data that leads to success but building a better mousetrap

The value of knowing someone’s birthday, for example, is not in that tidbit itself, but in the fact that you know this is a good day to give that person a present. Most of the data that supports the advertising networks underlying the Internet ecosphere is of this sort: Information is important to companies because of the value that can be drawn from it, not for the inherent value of the data itself. Companies don’t collect information about you to stalk you, but to better provide goods and services to you.

Moreover, data itself is not only less important than what can be drawn from it, but data is also less important than the underlying product it informs. For instance, Snapchat created a challenger to  Facebook so successfully (and in such short time) that Facebook attempted to buy it for $3 billion (Google offered $4 billion). But Facebook’s interest in Snapchat wasn’t about its data. Instead, Snapchat was valuable — and a competitive challenge to Facebook — because it cleverly incorporated the (apparently novel) insight that many people wanted to share information in a more private way.

Relatedly, Twitter, Instagram, LinkedIn, Yelp, Pinterest (and Facebook itself) all started with little (or no) data and they have had a lot of success. Meanwhile, despite its supposed data advantages, Google’s attempts at social networking — Google+ — have never caught up to Facebook in terms of popularity to users (and thus not to advertisers either). And scrappy social network Ello is starting to build a significant base without data collection for advertising at all.

At the same time it’s simply not the case that the alleged data giants — the ones supposedly insulating themselves behind data barriers to entry — actually have the type of data most relevant to startups anyway. As Andres Lerner has argued, if you wanted to start a travel business, the data from Kayak or Priceline would be far more relevant. Or if you wanted to start a ride-sharing business, data from cab companies would be more useful than the broad, market-cross-cutting profiles Google and Facebook have. Consider companies like Uber, Lyft and Sidecar that had no customer data when they began to challenge established cab companies that did possess such data. If data were really so significant, they could never have competed successfully. But Uber, Lyft and Sidecar have been able to effectively compete because they built products that users wanted to use — they came up with an idea for a better mousetrap.The data they have accrued came after they innovated, entered the market and mounted their successful challenges — not before.

In reality, those who complain about data facilitating unassailable competitive advantages have it exactly backwards. Companies need to innovate to attract consumer data, otherwise consumers will switch to competitors (including both new entrants and established incumbents). As a result, the desire to make use of more and better data drives competitive innovation, with manifestly impressive results: The continued explosion of new products, services and other apps is evidence that data is not a bottleneck to competition but a spur to drive it.

Third, competition online is one click or thumb swipe away; that is, barriers to entry and switching costs are low

Somehow, in the face of alleged data barriers to entry, competition online continues to soar, with newcomers constantly emerging and triumphing. This suggests that the barriers to entry are not so high as to prevent robust competition.

Again, despite the supposed data-based monopolies of Facebook, Google, Amazon, Apple and others, there exist powerful competitors in the marketplaces they compete in:

  • If consumers want to make a purchase, they are more likely to do their research on Amazon than Google.
  • Google flight search has failed to seriously challenge — let alone displace —  its competitors, as critics feared. Kayak, Expedia and the like remain the most prominent travel search sites — despite Google having literally purchased ITA’s trove of flight data and data-processing acumen.
  • People looking for local reviews go to Yelp and TripAdvisor (and, increasingly, Facebook) as often as Google.
  • Pinterest, one of the most highly valued startups today, is now a serious challenger to traditional search engines when people want to discover new products.
  • With its recent acquisition of the shopping search engine, TheFind, and test-run of a “buy” button, Facebook is also gearing up to become a major competitor in the realm of e-commerce, challenging Amazon.
  • Likewise, Amazon recently launched its own ad network, “Amazon Sponsored Links,” to challenge other advertising players.

Even assuming for the sake of argument that data creates a barrier to entry, there is little evidence that consumers cannot easily switch to a competitor. While there are sometimes network effects online, like with social networking, history still shows that people will switch. MySpace was considered a dominant network until it made a series of bad business decisions and everyone ended up on Facebook instead. Similarly, Internet users can and do use Bing, DuckDuckGo, Yahoo, and a plethora of more specialized search engines on top of and instead of Google. And don’t forget that Google itself was once an upstart new entrant that replaced once-household names like Yahoo and AltaVista.

Fourth, access to data is not exclusive

Critics like Newman have compared Google to Standard Oil and argued that government authorities need to step in to limit Google’s control over data. But to say data is like oil is a complete misnomer. If Exxon drills and extracts oil from the ground, that oil is no longer available to BP. Data is not finite in the same way. To use an earlier example, Google knowing my birthday doesn’t limit the ability of Facebook to know my birthday, as well. While databases may be proprietary, the underlying data is not. And what matters more than the data itself is how well it is analyzed.

This is especially important when discussing data online, where multi-homing is ubiquitous, meaning many competitors end up voluntarily sharing access to data. For instance, I can use the friend-finder feature on WordPress to find Facebook friends, Google connections, and people I’m following on Twitter who also use the site for blogging. Using this feature allows WordPress to access your contact list on these major online players.

Friend-Finder

Further, it is not apparent that Google’s competitors have less data available to them. Microsoft, for instance, has admitted that it may actually have more data. And, importantly for this discussion, Microsoft may have actually garnered some of its data for Bing from Google.

If Google has a high cost per click, then perhaps it’s because it is worth it to advertisers: There are more eyes on Google because of its superior search product. Contra Newman and Grunes, Google may just be more popular for consumers and advertisers alike because the algorithm makes it more useful, not because it has more data than everyone else.

Fifth, the data barrier to entry argument does not have workable antitrust remedies

The misguided logic of data barrier to entry arguments leaves a lot of questions unanswered. Perhaps most important among these is the question of remedies. What remedy would apply to a company found guilty of leveraging its market power with data?

It’s actually quite difficult to conceive of a practical means for a competition authority to craft remedies that would address the stated concerns without imposing enormous social costs. In the unilateral conduct context, the most obvious remedy would involve the forced sharing of data.

On the one hand, as we’ve noted, it’s not clear this would actually accomplish much. If competitors can’t actually make good use of data, simply having more of it isn’t going to change things. At the same time, such a result would reduce the incentive to build data networks to begin with. In their startup stage, companies like Uber and Facebook required several months and hundreds of thousands, if not millions, of dollars to design and develop just the first iteration of the products consumers love. Would any of them have done it if they had to share their insights? In fact, it may well be that access to these free insights is what competitors actually want; it’s not the data they’re lacking, but the vision or engineering acumen to use it.

Other remedies limiting collection and use of data are not only outside of the normal scope of antitrust remedies, they would also involve extremely costly court supervision and may entail problematic “collisions between new technologies and privacy rights,” as the last year’s White House Report on Big Data and Privacy put it.

It is equally unclear what an antitrust enforcer could do in the merger context. As Commissioner Ohlhausen has argued, blocking specific transactions does not necessarily stop data transfer or promote privacy interests. Parties could simply house data in a standalone entity and enter into licensing arrangements. And conditioning transactions with forced data sharing requirements would lead to the same problems described above.

If antitrust doesn’t provide a remedy, then it is not clear why it should apply at all. The absence of workable remedies is in fact a strong indication that data and privacy issues are not suitable for antitrust. Instead, such concerns would be better dealt with under consumer protection law or by targeted legislation.