Archives For Yahoo

After more than a year of complaining about Google and being met with responses from me (see also here, here, here, here, and here, among others) and many others that these complaints have yet to offer up a rigorous theory of antitrust injury — let alone any evidence — FairSearch yesterday offered up its preferred remedies aimed at addressing, in its own words, “the fundamental conflict of interest driving Google’s incentive and ability to engage in anti-competitive conduct. . . . [by putting an] end [to] Google’s preferencing of its own products ahead of natural search results.”  Nothing in the post addresses the weakness of the organization’s underlying claims, and its proposed remedies would be damaging to consumers.

FairSearch’s first and core “abuse” is “[d]iscriminatory treatment favoring Google’s own vertical products in a manner that may harm competing vertical products.”  To address this it proposes prohibiting Google from preferencing its own content in search results and suggests as additional, “structural remedies” “[r]equiring Google to license data” and “[r]equiring Google to divest its vertical products that have benefited from Google’s abuses.”

Tom Barnett, former AAG for antitrust, counsel to FairSearch member Expedia, and FairSearch’s de facto spokesman should be ashamed to be associated with claims and proposals like these.  He better than many others knows that harm to competitors is not the issue under US antitrust laws.  Rather, US antitrust law requires a demonstration that consumers — not just rivals — will be harmed by a challenged practice.  He also knows (as economists have known for a long time) that favoring one’s own content — i.e., “vertically integrating” to produce both inputs as well as finished products — is generally procompetitive.

In fact, Barnett has said as much before:

Because a Section 2 violation hurts competitors, they are often the focus of section 2 remedial efforts.  But competitor well-being, in itself, is not the purpose of our antitrust laws.

Access remedies also raise efficiency and innovation concerns.  By forcing a firm to share the benefits of its investments and relieving its rivals of the incentive to develop comparable assets of their own, access remedies can reduce the competitive vitality of an industry.

Not only has FairSearch not actually demonstrated that Google has preferenced its own products, the organization has also not demonstrated either harm to consumers arising from such conduct nor even antitrust-cognizable harm to competitors arising from it.

As an empirical study supported by the International Center for Law and Economics (itself, in turn, supported in part by Google, and of which I am the Executive Director) makes clear, search bias simply almost never occurs.  And when it does, it is the non-dominant Bing that more often practices it, not Google.  Moreover, and most important, the evidence marshaled in favor of the search bias claim (largely adduced by Harvard Business School professor, Ben Edelman (whose work is supported by Microsoft)) demonstrates that consumers do, indeed, have the ability to detect and counter allegedly biased results.

Recall what search bias means in this context.  According to Edelman, looking at the top three search results, Google links to its own content (think Gmail, Google Maps, etc.) in the first search result about twice as often as Yahoo! and Bing link to Google content in this position.  While the ICLE paper refutes even this finding, notice what it means:  “Biased” search results lead to a reshuffling of results among the top few results offered up; there is no evidence that Google simply drops users’ preferred results.  While it is true that the difference in click-through rates between the top and second results can be significant, Edelman’s own findings actually demonstrate that consumers are capable of finding what they want when their preferred (more relevant) results appears in the second or third slot.

Edelman notes that Google ranks Gmail first and Yahoo! Mail second in his study, even though users seem to think Yahoo! Mail is the more relevant result:  Gmail receives only 29% of clicks while Yahoo! Mail receives 54%.  According to Edelman, this is proof that Google’s conduct forecloses access by competitors and harms consumers under the antitrust laws.

But is it?  Note that users click on the second, apparently more-relevant result nearly twice as often as they click on the first.  This demonstrates that Yahoo! is not competitively foreclosed from access to users, and that users are perfectly capable of identifying their preferred results, even when they appear lower in the results page.  This is simply not foreclosure — in fact, if anything, it demonstrates the opposite.

Among other things, foreclosure — limiting access by a competitor to a necessary input — under the antitrust laws must be substantial enough to prevent a rival from reaching sufficient scale that it can effectively compete.  It is no more “foreclosure” for Google to “impair” traffic to Kayak’s site by offering its own Flight Search than it is for Safeway to refuse to allow Kroger to sell Safeway’s house brand.  Rather, actionable foreclosure requires that a firm “impair[s] the ability of rivals to grow into effective competitors that erode the firm’s position.”  Such quantifiable claims are noticeably absent from critic’s complaints against Google.

And what about those allegedly harmed competitors?  How are they faring?  As of September 2012, Google ranks 7th in visits among metasearch travel sites, with a paltry 1.4% of such visits.  Residing at number one?  FairSearch founding member, Kayak, with a whopping 61% (up from 52% six months after Google entered the travel search business).  Nextag.com, another vocal Google critic, has complained that Google’s conduct has forced it to shift its strategy from attracting traffic through Google’s organic search results to other sources, including paid ads on Google.com.  And how has it fared?  It has parlayed its experience with new data sources into a successful new business model, Wize Commerce, showing exactly the sort of “incentive to develop comparable assets of their own” Barnett worries will be destroyed by aggressive antitrust enforcement.  And Barnett’s own Expedia.com?  Currently, it’s the largest travel company in the world, and it has only grown in recent years.

Meanwhile consumers’ interests have been absent from critics’ complaints since the beginning.  And not only do they fail to demonstrate any connection between harm to consumers and the claimed harms to competitors arising from Google’s conduct, but they also ignore the harm to consumers that may result from restricting potentially efficient business conduct — like the integration of Google Maps and other products into its search results.  That Google not only produces search results but also owns some of the content that generates those results is not a problem cognizable by modern antitrust.

FairSearch and other Google critics have utterly failed to make a compelling case, and their proposed remedies would serve only to harm, not help, consumers.

In my last post, I discussed Edelman & Lockwood’s (E&L’s) attempt to catch search engines in the act of biasing their results—as well as their failure to actually do so.  In this post, I present my own results from replicating their study.  Unlike E&L, I find that Bing is consistently more biased than Google, for reasons discussed further below, although neither engine references its own content as frequently as E&L suggest.

I ran searches for E&L’s original 32 non-random queries using three different search engines—Google, Bing, and Blekko—between June 23 and July 5 of this year.  This replication is useful, as search technology has changed dramatically since E&L recorded their results in August 2010.  Bing now powers Yahoo, and Blekko has had more time to mature and enhance its results.  Blekko serves as a helpful “control” engine in my study, as it is totally independent of Google and Microsoft, and so has no incentive to refer to Google or Microsoft content unless it is actually relevant to users.  In addition, because Blekko’s model is significantly different than Google and Microsoft’s, if results on all three engines agree that specific content is highly relevant to the user query, it lends significant credibility to the notion that the content places well on the merits rather than being attributable to bias or other factors.

How Do Search Engines Rank Their Own Content?

Focusing solely upon the first position, Google refers to its own products or services when no other search engine does in 21.9% of queries; in another 21.9% of queries, both Google and at least one other search engine rival (i.e. Bing or Blekko) refer to the same Google content with their first links.

But restricting focus upon the first position is too narrow.  Assuming that all instances in which Google or Bing rank their own content first and rivals do not amounts to bias would be a mistake; such a restrictive definition would include cases in which all three search engines rank the same content prominently—agreeing that it is highly relevant—although not all in the first position. 

The entire first page of results provides a more informative comparison.  I find that Google and at least one other engine return Google content on the first page of results in 7% of the queries.  Google refers to its own content on the first page of results without agreement from either rival search engine in only 7.9% of the queries.  Meanwhile, Bing and at least one other engine refer to Microsoft content in 3.2% of the queries.  Bing references Microsoft content without agreement from either Google or Blekko in 13.2% of the queries:

This evidence indicates that Google’s ranking of its own content differs significantly from its rivals in only 7.9% of queries, and that when Google ranks its own content prominently it is generally perceived as relevant.  Further, these results suggest that Bing’s organic search results are significantly more biased in favor of Microsoft content than Google’s search results are in favor of Google’s content.

Examining Search Engine “Bias” on Google

The following table presents the percentages of queries for which Google’s ranking of its own content differs significantly from its rivals’ ranking of that same content.

Note that percentages below 50 in this table indicate that rival search engines generally see the referenced Google content as relevant and independently believe that it should be ranked similarly.

So when Google ranks its own content highly, at least one rival engine typically agrees with this ranking; for example, when Google places its own content in its Top 3 results, at least one rival agrees with this ranking in over 70% of queries.  Bing especially agrees with Google’s rankings of Google content within its Top 3 and 5 results, failing to include Google content that Google ranks similarly in only a little more than a third of queries.

Examining Search Engine “Bias” on Bing

Bing refers to Microsoft content in its search results far more frequently than its rivals reference the same Microsoft content.  For example, Bing’s top result references Microsoft content for 5 queries, while neither Google nor Blekko ever rank Microsoft content in the first position:

This table illustrates the significant discrepancies between Bing’s treatment of its own Microsoft content relative to Google and Blekko.  Neither rival engine refers to Microsoft content Bing ranks within its Top 3 results; Google and Blekko do not include any Microsoft content Bing refers to on the first page of results in nearly 80% of queries.

Moreover, Bing frequently ranks Microsoft content highly even when rival engines do not refer to the same content at all in the first page of results.  For example, of the 5 queries for which Bing ranks Microsoft content in its top result, Google refers to only one of these 5 within its first page of results, while Blekko refers to none.  Even when comparing results across each engine’s full page of results, Google and Blekko only agree with Bing’s referral of Microsoft content in 20.4% of queries.

Although there are not enough Bing data to test results in the first position in E&L’s sample, Microsoft content appears as results on the first page of a Bing search about 7 times more often than Microsoft content appears on the first page of rival engines.  Also, Google is much more likely to refer to Microsoft content than Blekko, though both refer to significantly less Microsoft content than Bing.

A Closer Look at Google v. Bing

On E&L’s own terms, Bing results are more biased than Google results; rivals are more likely to agree with Google’s algorithmic assessment (than with Bing’s) that its own content is relevant to user queries.  Bing refers to Microsoft content other engines do not rank at all more often than Google refers its own content without any agreement from rivals.  Figures 1 and 2 display the same data presented above in order to facilitate direct comparisons between Google and Bing.

As Figures 1 and 2 illustrate, Bing search results for these 32 queries are more frequently “biased” in favor of its own content than are Google’s.  The bias is greatest for the Top 1 and Top 3 search results.

My study finds that Bing exhibits far more “bias” than E&L identify in their earlier analysis.  For example, in E&L’s study, Bing does not refer to Microsoft content at all in its Top 1 or Top 3 results; moreover, Bing refers to Microsoft content within its entire first page 11 times, while Google and Yahoo refer to Microsoft content 8 and 9 times, respectively.  Most likely, the significant increase in Bing’s “bias” differential is largely a function of Bing’s introduction of localized and personalized search results and represents serious competitive efforts on Bing’s behalf.

Again, it’s important to stress E&L’s limited and non-random sample, and to emphasize the danger of making strong inferences about the general nature or magnitude of search bias based upon these data alone.  However, the data indicate that Google’s own-content bias is relatively small even in a sample collected precisely to focus upon the queries most likely to generate it.  In fact—as I’ll discuss in my next post—own-content bias occurs even less often in a more representative sample of queries, strongly suggesting that such bias does not raise the competitive concerns attributed to it.

Last week I linked to my new study on “search bias.”  At the time I noted I would have a few blog posts in the coming days discussing the study.  This is the first of those posts.

A lot of the frenzy around Google turns on “search bias,” that is, instances when Google references its own links or its own content (such as Google Maps or YouTube) in its search results pages.  Some search engine critics condemn such references as inherently suspect and almost by their very nature harmful to consumers.  Yet these allegations suffer from several crucial shortcomings.  As I’ve noted (see, e.g., here and here), these naked assertions of discrimination are insufficient to state a cognizable antitrust claim, divorced as they are from consumer welfare analysis.  Indeed, such “discrimination” (some would call it “vertical integration”) has a well-recognized propensity to yield either pro-competitive or competitively neutral outcomes, rather than concrete consumer welfare losses.  Moreover, because search engines exist in an incredibly dynamic environment, marked by constant innovation and fierce competition, we would expect different engines, utilizing different algorithms and appealing to different consumer preferences, to emerge.  So when search engines engage in product differentiation of this sort, there is no reason to be immediately suspicious of these business decisions.

No reason to be immediately suspicious – but there could, conceivably, be a problem.  If there is, we would want to see empirical evidence of it—of both the existence of bias, as well as the consumer harm emanating from it.  But one of the most notable features of this debate is the striking lack of empirical data.  Surprisingly little research has been done in this area, despite frequent assertions that own-content bias is commonly practiced and poses a significant threat to consumers (see, e.g., here).

My paper is an attempt to rectify this.  In the paper, I investigate the available data to determine whether and to what extent own-content bias actually occurs, by analyzing and replicating a study by Ben Edelman and Ben Lockwood (E&L) and conducting my own study of a larger, randomized set of search queries.

In this post I discuss my analysis and critique of E&L; in future posts I’ll present my own replication of their study, as well as the results of my larger study of 1,000 random search queries.  Finally, I’ll analyze whether any of these findings support anticompetitive foreclosure theories or are otherwise sufficient to warrant antitrust intervention.

E&L “investigate . . . [w]hether search engines’ algorithmic results favor their own services, and if so, which search engines do most, to what extent, and in what substantive areas.”  Their approach is to measure the difference in how frequently search engines refer to their own content relative to how often their rivals do so.

One note at the outset:  While this approach provides useful descriptive facts about the differences between how search engines link to their own content, it does little to inform antitrust analysis because Edelman and Lockwood begin with the rather odd claim that competition among differentiated search engines for consumers is a puzzle that creates an air of suspicion around the practice—in fact, they claim that “it is hard to see why results would vary . . . across search engines.”  This assertion, of course, is simply absurd.  Indeed, Danny Sullivan provides a nice critique of this claim:

It’s not hard to see why search engine result differ at all.  Search engines each use their own “algorithm” to cull through the pages they’ve collected from across the web, to decide which pages to rank first . . . . Google has a different algorithm than Bing.  In short, Google will have a different opinion than Bing.  Opinions in the search world, as with the real world, don’t always agree.

Moreover, this assertion completely discounts both the vigorous competitive product differentiation that occurs in nearly all modern product markets as well as the obvious selection effects at work in own-content bias (Google users likely prefer Google content).  This combination detaches E&L’s analysis from the consumer welfare perspective, and thus antitrust policy relevance, despite their claims to the contrary (and the fact that their results actually exhibit very little bias).

Several methodological issues undermine the policy relevance of E&L’s analysis.  First, they hand select 32 search queries and execute searches on Google, Bing, Yahoo, AOL and Ask.  This hand-selected non-random sample of 32 search queries cannot generate reliable inferences regarding the frequency of bias—a critical ingredient to understanding its potential competitive effects.  Indeed, E&L acknowledge their queries are chosen precisely because they are likely to return results including Google content (e.g., email, images, maps, video, etc.).

E&L analyze the top three organic search results for each query on each engine.  They find that 19% of all results across all five search engines refer to content affiliated with one of them.  They focus upon the first three organic results and report that Google refers to its own content in the first (“top”) position about twice as often as Yahoo and Bing refer to Google content in this position.  Additionally, they note that Yahoo is more biased than Google when evaluating the first page rather than only the first organic search result.

E&L also offer a strained attempt to deal with the possibility of competitive product differentiation among search engines.  They examine differences among search engines’ references to their own content by “compar[ing] the frequency with which a search engine links to its own pages, relative to the frequency with which other search engines link to that search engine’s pages.”  However, their evidence undermines claims that Google’s own-content bias is significant and systematic relative to its rivals’.  In fact, almost zero evidence of statistically significant own-content bias by Google emerges.

E&L find, in general, Google is no more likely to refer to its own content than other search engines are to refer to that same content, and across the vast majority of their results, E&L find Google search results are not statistically more likely to refer to Google content than rivals’ search results.

The same data can be examined to test the likelihood that a search engine will refer to content affiliated with a rival search engine.  Rather than exhibiting bias in favor of an engine’s own content, a “biased” search engine might conceivably be less likely to refer to content affiliated with its rivals.  The table below reports the likelihood (in odds ratios) that a search engine’s content appears in a rival engine’s results.

The first two columns of the table demonstrate that both Google and Yahoo content are referred to in the first search result less frequently in rivals’ search results than in their own.  Although Bing does not have enough data for robust analysis of results in the first position in E&L’s original analysis, the next three columns in Table 1 illustrate that all three engines’ (Google, Yahoo, and Bing) content appears less often on the first page of rivals’ search results than on their own search engine.  However, only Yahoo’s results differ significantly from 1.  As between Google and Bing, the results are notably similar.

E&L also make a limited attempt to consider the possibility that favorable placement of a search engine’s own content is a response to user preferences rather than anticompetitive motives.  Using click-through data, they find, unsurprisingly, that the first search result tends to receive the most clicks (72%, on average).  They then identify one search term for which they believe bias plays an important role in driving user traffic.  For the search query “email,” Google ranks its own Gmail first and Yahoo Mail second; however, E&L also find that Gmail receives only 29% of clicks while Yahoo Mail receives 54%.  E&L claim that this finding strongly indicates that Google is engaging in conduct that harms users and undermines their search experience.

However, from a competition analysis perspective, that inference is not sound.  Indeed, the fact that the second-listed Yahoo Mail link received the majority of clicks demonstrates precisely that Yahoo was not competitively foreclosed from access to users.  Taken collectively, E&L are not able to muster evidence of potential competitive foreclosure.

While it’s important to have an evidence-based discussion surrounding search engine results and their competitive implications, it’s also critical to recognize that bias alone is not evidence of competitive harm.  Indeed, any identified bias must be evaluated in the appropriate antitrust economic context of competition and consumers, rather than individual competitors and websites.  E&L’s analysis provides a useful starting point for describing how search engines differ in their referrals to their own content.  But, taken at face value, their results actually demonstrate little or no evidence of bias—let alone that the little bias they do find is causing any consumer harm.

As I’ll discuss in coming posts, evidence gathered since E&L conducted their study further suggests their claims that bias is prevalent, inherently harmful, and sufficient to warrant antitrust intervention are overstated and misguided.