Search Results

As has become customary with just about every new product announcement by Google these days, the company’s introduction on Tuesday of its new “Search, plus Your World” (SPYW) program, which aims to incorporate a user’s Google+ content into her organic search results, has met with cries of antitrust foul play. All the usual blustering and speculation in the latest Google antitrust debate has obscured what should, however, be the two key prior questions: (1) Did Google violate the antitrust laws by not including data from Facebook, Twitter and other social networks in its new SPYW program alongside Google+ content; and (2) How might antitrust restrain Google in conditioning participation in this program in the future?

Read the full piece here.

The web is all abuzz about possible antitrust implications concerning Google’s new personalized search (see, e.g., here and here), integrating search with Google Plus.  Here is Google’s description of “Search, plus Your World”:

We’re transforming Google into a search engine that understands not only content, but also people and relationships. We began this transformation with Social Search, and today we’re taking another big step in this direction by introducing three new features:

1. Personal Results, which enable you to find information just for you, such as Google+ photos and posts—both your own and those shared specifically with you, that only you will be able to see on your results page;
2. Profiles in Search, both in autocomplete and results, which enable you to immediately find people you’re close to or might be interested in following; and,
3. People and Pages, which help you find people profiles and Google+ pages related to a specific topic or area of interest, and enable you to follow them with just a few clicks. Because behind most every query is a community.

The linked articles raising antitrust concerns largely talk about things like leveraging monopoly power in search into social networks and so forth.  The usual arguments.  For example:

By making Google+ such a large part of search — as well as Picasa — Google certainly is toeing the line of a company using monopoly to extend its reach into adjacent markets. Consider Microsoft’s moves with Internet Explorer, which was bundled with Windows starting in 1998. Microsoft used its monopoly on PC operating systems to nudge into the browser market, where Netscape had overwhelming market share lead. How is what Google is doing different?

Let’s start with the obvious differences: (1) the DOJ had to prove anticompetitive effects in Microsoft; (2) Microsoft was unable to muster up an efficiency justification.  Discussions of antitrust implications of any business practice that don’t focus on competitive effects and efficiency justifications are non-starters.

So let’s start with the most obvious thing that should come to mind when watching the integration of general search with Google Plus.   Integration!  Personalizing search results makes (at least some!) users better off.  Users that prefer non-personalized results can have them too.  But the trend toward providing a deeper, better, and different forms of answers to questions posed in search queries is not a Google-specific thing.  Its an industry thing driven by consumer preferences on the web.  When Google or Facebook or Twitter is able to integrate functions of search and social networking to create something different and demanded by consumers, that consumers enjoy and derive surplus from, this is a competitive benefit.  Competitive benefits count in antitrust because they make consumers better off.  This is very basic. But worth repeating.

The antitrust question is whether, despite these obvious efficiencies, there is plausible evidence of anticompetitive harm — that is, harm to competition rather than individual rivals like Bing, Twitter, or Facebook.  My personal view — which I’ve written about at great length here, here, and here — is that there is no such evidence.  But for now, the critical point is that antitrust analysis counts the integration of these functions in a manner satisfying consumer preferences — and it seems obvious that this integration produces results that consumers want — as an important consumer benefit.  This is a feature and not a bug of antitrust law.   Antitrust law that ignores or is biased against the efficiencies of vertical integration, or the introduction of new products integrating previously separate functions (like personalized search, or improved search results with maps), is at significant tension with economic theory and is simply not compatible with a consumer-welfare based competition regime.

Filed under: antitrust, google, Internet search, technology

Back in September, the Senate Judiciary Committee’s Antitrust Subcommittee held a hearing on “The Power of Google: Serving Consumers or Threatening Competition?” Given the harsh questioning from the Subcommittee’s Chairman Herb Kohl (D-WI) and Ranking Member Mike Lee (R-UT), no one should have been surprised by the letter they sent yesterday to the Federal Trade Commission asking for a “thorough investigation” of the company. At least this time the danger is somewhat limited: by calling for the FTC to investigate Google, the senators are thus urging the agency to do . . . exactly what it’s already doing.

Read the full piece here.

In my series of three posts (here, here and here) drawn from my empirical study on search bias I have examined whether search bias exists, and, if so, how frequently it occurs.  This, the final post in the series, assesses the results of the study (as well as the Edelman & Lockwood (E&L) study to which it responds) to determine whether the own-content bias I’ve identified is in fact consistent with anticompetitive foreclosure or is otherwise sufficient to warrant antitrust intervention.

As I’ve repeatedly emphasized, while I refer to differences among search engines’ rankings of their own or affiliated content as “bias,” without more these differences do not imply anticompetitive conduct.  It is wholly unsurprising and indeed consistent with vigorous competition among engines that differentiation emerges with respect to algorithms.  However, it is especially important to note that the theories of anticompetitive foreclosure raised by Google’s rivals involve very specific claims about these differences.  Properly articulated vertical foreclosure theories proffer both that bias is (1) sufficient in magnitude to exclude Google’s rivals from achieving efficient scale, and (2) actually directed at Google’s rivals.  Unfortunately for search engine critics, their theories fail on both counts.  The observed own-content bias appears neither to be extensive enough to prevent rivals from gaining access to distribution nor does it appear to target Google’s rivals; rather, it seems to be a natural result of intense competition between search engines and of significant benefit to consumers.

Vertical foreclosure arguments are premised upon the notion that rivals are excluded with sufficient frequency and intensity as to render their efforts to compete for distribution uneconomical.  Yet the empirical results simply do not indicate that market conditions are in fact conducive to the types of harmful exclusion contemplated by application of the antitrust laws.  Rather, the evidence indicates that (1) the absolute level of search engine “bias” is extremely low, and (2) “bias” is not a function of market power, but an effective strategy that has arisen as a result of serious competition and innovation between and by search engines.  The first finding undermines competitive foreclosure arguments on their own terms, that is, even if there were no pro-consumer justifications for the integration of Google content with Google search results.  The second finding, even more importantly, reveals that the evolution of consumer preferences for more sophisticated and useful search results has driven rival search engines to satisfy that demand.  Both Bing and Google have shifted toward these results, rendering the complained-of conduct equivalent to satisfying the standard of care in the industry–not restraining competition.

A significant lack of search bias emerges in the representative sample of queries.  This result is entirely unsurprising, given that bias is relatively infrequent even in E&L’s sample of queries specifically designed to identify maximum bias.  In the representative sample, the total percentage of queries for which Google references its own content when rivals do not is even lower—only about 8%—meaning that Google favors its own content far less often than critics have suggested.  This fact is crucial and highly problematic for search engine critics, as their burden in articulating a cognizable antitrust harm includes not only demonstrating that bias exists, but further that it is actually competitively harmful.  As I’ve discussed, bias alone is simply not sufficient to demonstrate any prima facie anticompetitive harm as it is far more often procompetitive or competitively neutral than actively harmful.  Moreover, given that bias occurs in less than 10% of queries run on Google, anticompetitive exclusion arguments appear unsustainable.

Indeed, theories of vertical foreclosure find virtually zero empirical support in the data.  Moreover, it appears that, rather than being a function of monopolistic abuse of power, search bias has emerged as an efficient competitive strategy, allowing search engines to differentiate their products in ways that benefit consumers.  I find that when search engines do reference their own content on their search results pages, it is generally unlikely that another engine will reference this same content.  However, the fact that both this percentage and the absolute level of own content inclusion is similar across engines indicates that this practice is not a function of market power (or its abuse), but is rather an industry standard.  In fact, despite conducting a much smaller percentage of total consumer searches, Bing is consistently more biased than Google, illustrating that the benefits search engines enjoy from integrating their own content into results is not necessarily a function of search engine size or volume of queries.  These results are consistent with a business practice that is efficient and at significant tension with arguments that such integration is designed to facilitate competitive foreclosure.

Inclusion of own content accordingly appears to be just one dimension upon which search engines have endeavored to satisfy and anticipate heterogeneous and dynamic consumer preferences.  Consumers today likely make strategic decisions as to which engine to run their searches on, and certainly expect engines to return far more complex results than were available just a few years ago. For example, over the last few years, search engines have begun “personalizing” search results, tailoring results pages to individual searchers, and allowing users’ preferences to be reflected over time.  While the traditional “10 blue links” results page is simply not an effective competitive strategy today, it appears that own-content inclusion is.  By developing and offering their own products in search results, engines are better able to directly satisfy consumer desires.

Moreover, the purported bias does not involve attempts to prominently display Google’s own general or vertical search content over that of rivals.  Consider the few queries in Edelman & Lockwood’s small sample of terms for which Google returned Google content within the top three results but neither Bing nor Blekko referenced the same content anywhere on their first page of results.  For the query “voicemail,” for example, Google refers to both Google Voice and Google Talk; both instances appear unrelated to the grievances of general and vertical search rivals.  The query “movie” results in a OneBox with the next 3 organic results including movie.com, fandango.com, and yahoo.movies.com.  The single instance in Edelman & Lockwood’s sample for which Google ranks its own content in the Top 3 positions but this content is not referred to at all on Bing’s first page of results is a link to blogger.com in response to the query “blog.”  It is difficult to construct a story whereby this result impedes Bing’s competitive position.  In fact, none of these examples suggests that efforts to anticompetitively foreclose rivals are in play.  To the contrary, each seems to be a result of simple and expected procompetitive product differentiation.

Overall, the evidence reveals very little search engine bias, and no overwhelming or systematic biasing by Google against  search competitors.  Indeed, the data simply do not support claims that own-content bias is of the nature, quality, or magnitude to generate plausible antitrust concerns.  To the contrary, the results strongly suggest that own-content bias fosters natural and procompetitive product differentiation.  Accordingly, search bias is likely beneficial to consumers—and is clearly not indicative of harm to consumer welfare.

Antitrust regulators should proceed with caution when evaluating such claims given the overwhelmingly consistent economic learning concerning the competitive benefits generally of vertical integration for consumers.  Serious care must be taken in order not to deter vigorous competition between search engines and the natural competitive process between rivals constantly vying to best one another to serve consumers.

Filed under: advertising, antitrust, business, economics, exclusionary conduct, google, Internet search, law and economics, monopolization, technology Tagged: Bias, Bing, Blekko, Competition law, Edelman, google, microsoft, Web search engine

My last two posts on search bias (here and here) have analyzed and critiqued Edelman & Lockwood’s small study on search bias.  This post extends this same methodology and analysis to a random sample of 1,000 Google queries (released by AOL in 2006), to develop a more comprehensive understanding of own-content bias.  As I’ve stressed, these analyses provide useful—but importantly limited—glimpses into the nature of the search engine environment.  While these studies are descriptively helpful, actual harm to consumer welfare must always be demonstrated before cognizable antitrust injuries arise.  And naked identifications of own-content bias simply do not inherently translate to negative effects on consumers (see, e.g., here and here for more comprehensive discussion).

Now that’s settled, let’s jump into the results of the 1,000 random search query study.

How Do Search Engines Rank Their Own Content?

Consistent with our earlier analysis, a starting off point for thinking about measuring differentiation among search engines with respect to placing their own content is to compare how a search engine ranks its own content relative to how other engines place that same content (e.g. to compare how Google ranks “Google Maps” relative to how Bing or Blekko rank it).   Restricting attention exclusively to the first or “top” position, I find that Google simply does not refer to its own content in over 90% of queries.  Similarly, Bing does not reference Microsoft content in 85.4% of queries.  Google refers to its own content in the first position when other search engines do not in only 6.7% of queries; while Bing does so over twice as often, referencing Microsoft content that no other engine references in the first position in 14.3% of queries.  The following two charts illustrate the percentage of Google or Bing first position results, respectively, dedicated to own content across search engines.

The most striking aspect of these results is the small fraction of queries for which placement of own-content is relevant.  The results are similar when I expand consideration to the entire first page of results; interestingly, however, while the levels of own-content bias are similar considering the entire first page of results, Bing is far more likely than Google to reference its own content in its very first results position.

Examining Search Engine “Bias” on Google

Two distinct differences between the results of this larger study and my replication of Edelman & Lockwood emerge: (1) Google and Bing refer to their own content in a significantly smaller percentage of cases here than in the non-random sample; and (2) in general, when Google or Bing does rank its own content highly, rival engines are unlikely to similarly rank that same content.

The following table reports the percentages of queries for which Google’s ranking of its own content and its rivals’ rankings of that same content differ significantly. When Google refers to its own content within its Top 5 results, at least one other engine similarly ranks this content for only about 5% of queries.

The following table presents the likelihood that Google content will appear in a Google search, relative to searches conducted on rival engines (reported in odds ratios).

The first and third columns report results indicating that Google affiliated content is more likely to appear in a search executed on Google rather than rival engines.  Google is approximately 16 times more likely to refer to its own content on its first page as is any other engine.  Bing and Blekko are both significantly less likely to refer to Google content in their first result or on their first page than Google is to refer to Google content within these same parameters.  In each iteration, Bing is more likely to refer to Google content than is Blekko, and in the case of the first result, Bing is much more likely to do so.  Again, to be clear, the fact that Bing is more likely to rank its own content is not suggestive that the practice is problematic.  Quite the contrary, the demonstration that firms both with and without market power in search (to the extent that is a relevant antitrust market) engage in similar conduct the correct inference is that there must be efficiency explanations for the practice.  The standard response, of course, is that the competitive implications of a practice are different when a firm with market power does it.  That’s not exactly right.  It is true that firms with market power can engage in conduct that gives rise to potential antitrust problems when the same conduct from a firm without market power would not; however, when firms without market power engage in the same business practice it demands that antitrust analysts seriously consider the efficiency implications of the practice.  In other words, there is nothing in the mantra that things are “different” when larger firms do them that undercut potential efficiency explanations.

Examining Search Engine “Bias” on Bing

For queries within the larger sample, Bing refers to Microsoft content within its Top 1 and 3 results when no other engine similarly references this content for a slightly smaller percentage of queries than in my Edelman & Lockwood replication.  Yet Bing continues to exhibit a strong tendency to rank Microsoft content more prominently than rival engines.  For example, when Bing refers to Microsoft content within its Top 5 results, other engines agree with this ranking for less than 2% of queries; and Bing refers to Microsoft content that no other engine does within its Top 3 results for 99.2% of queries:

Regression analysis further illustrates Bing’s propensity to reference Microsoft content that rivals do not.  The following table reports the likelihood that Microsoft content is referred to in a Bing search as compared to searches on rival engines (again reported in odds ratios).

Bing refers to Microsoft content in its first results position about 56 times more often than rival engines refer to Microsoft content in this same position.  Across the entire first page, Microsoft content appears on a Bing search about 25 times more often than it does on any other engine.  Both Google and Blekko are accordingly significantly less likely to reference Microsoft content.  Notice further that, contrary to the findings in the smaller study, Google is slightly less likely to return Microsoft content than is Blekko, both in its first results position and across its entire first page.

A Closer Look at Google v. Bing

 Consistent with the smaller sample, I find again that Bing is more biased than Google using these metrics.  In other words, Bing ranks its own content significantly more highly than its rivals do more frequently then Google does, although the discrepancy between the two engines is smaller here than in the study of Edelman & Lockwood’s queries.  As noted above, Bing is over twice as likely to refer to own content in first results position than is Google.

Figures 7 and 8 present the same data reported above, but with Blekko removed, to allow for a direct visual comparison of own-content bias between Google and Bing.

Consistent with my earlier results, Bing appears to consistently rank Microsoft content higher than Google ranks the same (Microsoft) content more frequently than Google ranks Google content more prominently than Bing ranks the same (Google) content.

This result is particularly interesting given the strength of the accusations condemning Google for behaving in precisely this way.  That Bing references Microsoft content just as often as—and frequently even more often than!—Google references its own content strongly suggests that this behavior is a function of procompetitive product differentiation, and not abuse of market power.  But I’ll save an in-depth analysis of this issue for my next post, where I’ll also discuss whether any of the results reported in this series of posts support anticompetitive foreclosure theories or otherwise suggest antitrust intervention is warranted.

Filed under: antitrust, economics, google, Internet search, law and economics, technology Tagged: Bias, Bing, Blekko, google, microsoft, Web search engine

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.

Filed under: antitrust, business, economics, google, Internet search, law and economics, monopolization, technology Tagged: antitrust, Bias, Bing, Blekko, google, microsoft, search, Web search engine, Yahoo

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.

Filed under: antitrust, business, economics, google, Internet search, law and economics, monopolization, technology Tagged: antitrust, Bing, google, search, search bias, Search Engines, search neutrality, Web search engine, Yahoo

Summary

Search engines produce immense value by identifying, organizing, and presenting the Internet´s information in response to users´ queries.1 Search engines efficiently provide better and faster answers to users´ questions than alternatives.

Recently, critics have taken issue with the various methods search engines use to identify relevant content and rank search results for users. Google, in particular, has been the subject of much of this criticism on the grounds that its organic search results—those generated algorithmically—favor its own products and services at the expense of those of its rivals. It is widely understood that search engines´ algorithms for ranking various web pages naturally differ. Likewise, there is widespread recognition that competition among search engines is vigorous, and that differentiation between engines´ ranking functions is not only desirable, but a natural byproduct of competition, necessary to survival, and beneficial to consumers.2 Nonetheless, despite widespread recognition of the consumer benefits of such differentiation, complaints from rival search engines have persisted and succeeded in attracting attention from a number of state, federal and international regulatory agencies. Unfortunately, much of this attention has focused on the impact upon individual websites of differences among search engines´ algorithmic methods of identifying and ranking relevant content, rather than analyzing these differences from a conventional consumer?welfare driven antitrust analysis.

For example, many of these complaints ignore the fact that search engine users self?select into different engines or use multiple engines for different types of searches when considering the competitive implications of search rankings.3 Rather than focus upon competition among search engines in how results are identified and presented to users, critics and complainants craft their arguments around alleged search engine “discrimination” or “bias.”4 The complainants must have in mind something other than competitive decisions to rank content that differ from the decisions made by rivals; bias in this sense is both necessary to and inherent within any useful indexing tool. Yet, critics have generally avoided a precise definition of the allegedly troublesome conduct. Indeed, the term “bias” is used colloquially and is frequently invoked in the search engine debate to encompass a wide array of behavior—generally suggesting a latent malignancy within search engine conduct—with some critics citing mere differences in results across engines as evidence of harmful conduct.5

The more useful attempts to define “bias,” however, focus upon differences in organic rankings attributable to the search engine ranking its own content (“owncontent bias”); that is, a sufficient condition for own?content bias is that a search engine ranks its own content more prominently than its rivals do. To be even more precise about the nature of the alleged “own?content bias,” it should be clear that this form of  bias refers exclusively to organic results, i.e., those results the search engine produces algorithmically, as distinguished from the paid advertisements that might appear at the top, bottom, or right?hand side of a search result page.6 Critics at the Senate’s recent hearing on the “Power of Google” were particularly vociferous on this front, accusing Google of having “cooked”7 its algorithm and of “rig[ging] its results, biasing in favor of Google.”8

Competition economists and regulatory agencies are familiar with business arrangements which give rise to concerns of own?content bias.9 Complaints and economic theories of harm assert that a vertically integrated firm (in this case, Google offers search results as well as products like YouTube and Google Maps) might discriminate against its rivals by “foreclosing” them from access to a critical input. Here, the critical input necessary for rivals´ success is alleged to be prominent placement in Google´s search results. The economics of the potential anticompetitive exclusion of rivals involving vertically integrated firms are well understood in antitrust. The conditions that must be satisfied for these concerns to generate real risk to consumers are also well known. Over a century of antitrust jurisprudence, economic study, and enforcement agency practice have produced a well?understood economic analysis of the competitive effects of a vertically integrated firm´s “discrimination” in favor of its own products or services, including widespread recognition that such arrangements generally produce significant benefits for consumers. Modern competition policy recognizes that vertical integration and contractual arrangements are generally procompetitive; it also understands that discrimination of this sort may create the potential for competitive harm under some conditions. Sensible competition policy involving vertical integration and contractual arrangements requires one to be sensitive to the potential consumer welfare?enhancing potential of such vertical integration while also taking seriously the possibility that a firm might successfully harm competition itself (and not merely a rival).

In addition to the failure to distinguish procompetitive conduct from anticompetitive behavior, critics´ allegations of own?content bias suffer deeper conceptual ambiguities. The perceived issue for Google´s rivals is not merely that Google links to a map when responding to search queries, suggesting one might be  relevant for the user; indeed, rival search engines frequently respond to similar user queries with their own or other map products. Rather, critics find problematic that Google responds to user queries with a Google Map. This is a critical distinction because it concedes that rivals´ complaints are not satisfied by the response that consumers are better off with the map; nor do critics pause to consider that perhaps the Google search user prefers the Google Map to rival products.10 Thus, critics brazenly take issue with the relationship between Google and the search result even where they concede Google produces more relevant results for consumers.11 Rather than focusing upon consumers, critics argue that the fact that Google is affiliated with the referred search result is itself prima facie evidence of competitively harmful bias.12 On its face, this argument turns conventional antitrust wisdom on its head. Conduct that harms rivals merely because it attracts consumers from rivals is the essence of competition and the logical core of the maxim that antitrust protects “competition, not competitors.?13

Critics´ failure to account for the potential consumer benefits from ?own?content bias? extends beyond ignoring the fact that users might prefer Google´s products to rivals´. Most critics simply ignore the myriad of procompetitive explanations for vertical integration in the economics literature. This omission by critics, and especially by economist critics, is mystifying given that economists have documented not only a plethora of procompetitive justifications for such integration, but also that such vertical relationships are much more likely to be competitively beneficial or benign than to raise serious threats of foreclosure.14

The critical antitrust question is always whether the underlying conduct creates or maintains monopoly power and thus reduces competition and consumer welfare, or is more likely efficient and procompetitive. To be clear, documenting the mere existence of own?content bias itself does little to answer this question. Bias is not a sufficient condition for competitive harm as a matter of economics because it can increase, decrease, or have no impact at all upon consumer welfare; neither is bias, without more, sufficient to state a cognizable antitrust claim.15

Nonetheless, documenting whether and how much of the alleged bias exists in Google´s and its rivals´ search results can improve our understanding of its competitive implications—that is, whether the evidence of discrimination in favor of one´s own content across search engines is more consistent with anticompetitive foreclosure or with competitive differentiation.

Critically, in order to generate plausible competitive concerns, search bias must, at minimum, be sufficient in magnitude to foreclose rivals from achieving minimum efficient scale (otherwise, if it merely represents effective competition that makes life harder for competitors, it is not an antitrust concern at all). It follows from this necessary condition that not all evidence of ?bias? is relevant to this competitive concern; in particular, Google referring to its own products and services more prominently than its rivals rank those same services has little to do with critics´ complaints unless they implicate general or vertical search.

Despite widespread discussion of search engine bias, virtually no evidence exists indicating that bias abounds—and very little that it exists at all. Edelman & Lockwood recently addressed this dearth of evidence by conducting a small study focused upon own?content bias in 32 search queries. They contend that their results are indicative of systemic and significant bias demanding antitrust intervention.16 The authors define and measure ?bias? as the extent to which a search engine´s ranking of its own content differs from how its rivals rank the same content. This approach provides some useful information concerning differences among search engine rankings. However, the study should not be relied upon to support broad sweeping antitrust policy concerns with Google.

The small sample of search queries provides one reason for caution. Perhaps more importantly, the non?random sample of search queries undermines its utility for addressing the critical antitrust policy questions focusing upon the magnitude of search bias, both generally and as it relates to whether the degree and nature of observed bias satisfies the well?known conditions required for competitive foreclosure. Further, evaluating their evidence at face value, Edelman & Lockwood misinterpret its relevance (Edelman & Lockwood in fact find almost no evidence of bias) and, most problematically, simply assume that own?content bias is inherently suspect from a consumer welfare perspective rather than considering the well?known consumer benefits of vertical integration. Despite these shortcomings, Edelman & Lockwood´s study has received considerable attention, both in the press and from Google´s critics, who cite it as evidence of harmful and anticompetitive search engine behavior.17 In the present analysis, as a starting point, we first “replicate” and analyze Edelman & Lockwood´s earlier study of a small, non?random sample of search queries in the modern search market. We then extend this methodology to a larger random sample of search queries in order to draw more reliable inferences concerning the answers to crucial questions for the competition policy debate surrounding search engine bias, including: (1) what precisely is search engine bias?; (2) what are its  competitive implications?; (3) how common is it?; (4) what explains its existence and relative frequency across search engines?; and, most importantly, (5) does observed search engine bias pose a competitive threat or is it a feature of competition between search engines?

Part I of this paper articulates an antitrust?appropriate framework for analyzing claims of “own?content bias” and delineates its utility and shortcomings as a theory of antitrust harm; it further evaluates Edelman & Lockwood’s study, methodology and analysis using this framework. Part II lays out the methodology employed in our own studies. Part III presents the results of our replication of Edelman & Lockwood and analyzes antitrust implications for the search engine bias debate; Part IV does the same for our larger, random sample of search queries. Part V concludes.