Competition Law and Data Brokerage Market Power

Competition Law and Data Brokerage Market Power

1. Introduction

The data brokerage industry has become increasingly important to modern competition law. Data brokers collect information from numerous sources, combine and analyse it, create profiles or datasets, and provide those data products to businesses, advertisers, financial institutions, analytics companies, platforms, and other customers.

The U.S. Federal Trade Commission (FTC) has described data brokers as businesses that collect consumer information from public and non-public sources and resell or otherwise provide that information to other companies. Its studies have also emphasized the enormous scale of information collected by major brokers and the limited visibility consumers may have into these activities.

From a competition-law perspective, the important question is not simply whether a company possesses large quantities of information. The central issue is whether control over particular data, combined with other factors such as scale, technology, network effects, contractual restrictions or barriers to entry, gives a company market power and whether that power is obtained or maintained through conduct prohibited by competition law.

This distinction is fundamental. Competition law generally does not prohibit a company merely because it is large, successful or possesses valuable information. For example, under U.S. monopolization principles, monopoly power becomes a competition-law concern when it is acquired or maintained through exclusionary or otherwise unlawful conduct rather than legitimate competition.

2. What Is Market Power in Data Brokerage?

Market power generally means the ability of a business to behave to a meaningful extent without being constrained by competitors, customers or new entrants.

In conventional markets, regulators frequently examine:

• market shares;
• prices;
• output;
• availability of substitutes;
• switching costs;
• entry barriers; and
• control over important inputs.

Data brokerage complicates this analysis because data itself can function as an important competitive input.

A broker possessing large, historical and difficult-to-reproduce datasets may potentially obtain an advantage over a new entrant. A new company may possess good technology but still be unable to compete effectively if it cannot obtain comparable data.

The competitive importance of data therefore depends on its characteristics rather than merely its volume.

3. Data as a Source of Market Power

A. Scale of Data

A broker may obtain information concerning millions of individuals, transactions, devices or locations.

Large-scale datasets can improve:

• audience segmentation;
• identity resolution;
• fraud detection;
• advertising targeting;
• predictive analytics; and
• measurement services.

Scale alone does not establish dominance. Regulators must consider whether competitors can obtain comparable information elsewhere.

B. Variety of Data

A company combining information from numerous independent sources can sometimes construct more detailed datasets than companies relying on a single source.

The combination of demographic, transactional, behavioural, location and online information can increase the commercial usefulness of the resulting database.

C. Historical Data

Historical information can be particularly difficult for new competitors to reproduce.

A new entrant can begin collecting information today but may be unable immediately to recreate years of historical observations held by an established provider.

This can create a time-based entry barrier.

D. Exclusive Data

The strongest competition concerns can arise where commercially important information is exclusive.

Suppose Broker A has exclusive contractual access to information from several major suppliers. Broker B cannot simply purchase identical information elsewhere.

If the information is essential for competing effectively, exclusivity can reinforce Broker A's market position.

4. Data-Driven Feedback Loops

Digital markets can sometimes develop feedback effects:

More users or customers → more data → improved analytics → better products → more customers → still more data.

Such a cycle can strengthen an incumbent's position.

However, competition authorities should determine whether the alleged feedback loop actually creates durable market power. More data does not automatically mean better products indefinitely, and competitors may have alternative datasets or technologies.

Consequently, market power normally requires evidence concerning substitutability, entry conditions and actual competitive constraints.

5. Defining the Relevant Market

Market definition is especially difficult in data brokerage because different data products may serve different purposes.

Possible markets could concern:

• consumer identity information;
• location-data services;
• marketing databases;
• identity-resolution services;
• financial-risk information;
• advertising audiences;
• business intelligence;
• fraud-prevention information; or
• specialised analytics.

Authorities must determine whether customers consider alternative products sufficiently interchangeable.

A broad description such as the "data market" may therefore be too vague for competition analysis.

The relevant market may instead be a narrower service built around a particular type of information or use.

6. Barriers to Entry

Several characteristics of data markets can create barriers to entry.

Data acquisition costs

Collecting, purchasing and cleaning large datasets can require substantial investment.

Historical advantage

An established company may possess information accumulated over many years.

Exclusive agreements

Contracts may prevent suppliers from providing commercially important information to competing brokers.

Network effects

Some businesses become more useful as participation grows, indirectly increasing the information available to the company.

Technology and infrastructure

Raw information is often commercially useless without infrastructure capable of matching identities, removing errors and generating useful predictions.

Privacy and regulatory compliance

Data-protection requirements may increase the cost of establishing and maintaining large data operations.

None of these factors independently proves market power. Their cumulative effect is more important.

7. Competition Problems Involving Data Brokers

A. Exclusionary Data Agreements

A dominant business might enter agreements preventing important data suppliers from supplying rivals.

Competition authorities would examine whether those restrictions have legitimate commercial purposes or instead substantially foreclose competing brokers.

B. Refusal to Provide Data

A company controlling strategically important information might refuse access to a competitor.

Competition law generally does not impose a universal obligation to share valuable assets. Intervention therefore depends heavily on jurisdiction and circumstances.

Nevertheless, access restrictions become more significant where control over information is combined with dominance and exclusionary conduct.

C. Bundling and Tying

A powerful data provider could combine several services.

For example:

Product A: identity database
Product B: analytics platform.

Customers seeking the database might also be required to purchase the analytics service.

Competition concerns become stronger where market power in one product is used to restrict competition in another.

D. Discriminatory Access

A vertically integrated company could provide valuable information to its own downstream operation on better terms than those offered to independent competitors.

Authorities may investigate whether such differences have an exclusionary effect.

E. Acquisitions of Data-Rich Businesses

Acquisitions can also increase data concentration.

The competition question is not simply how many companies remain. Authorities can examine whether combining datasets substantially strengthens entry barriers or removes an important competitive constraint.

8. Privacy and Competition Are Different Legal Questions

Privacy law and competition law can overlap, but they protect different interests.

A privacy case can concern:

• consumer consent;
• sensitive information;
• transparency;
• security; or
• unlawful disclosure.

A competition case normally concerns:

• monopoly or dominance;
• exclusion;
• foreclosure;
• collusion;
• anticompetitive agreements; or
• mergers that substantially harm competition.

The distinction is illustrated by FTC v. Kochava. The case concerned the sale and disclosure of sensitive location information rather than a judicial finding that Kochava monopolized a data-brokerage market. In 2026, the FTC announced a settlement restricting Kochava and its subsidiary from selling or disclosing certain sensitive location data without affirmative consumer consent.

Therefore, a data-broker case should not automatically be described as an antitrust precedent merely because data is economically valuable.

9. Important Case Laws and Authorities

Because relatively few reported antitrust judgments deal exclusively with a narrowly defined data-brokerage market, the following cases are best understood as authorities establishing principles applicable to data-driven market power.

1. United States v. Google LLC — Search Monopolization

Court: U.S. District Court for the District of Columbia
Major decision: 2024

This is one of the most important modern cases concerning competition, scale and data.

The court concluded that Google had monopoly power in relevant search markets and unlawfully maintained its monopoly through exclusionary distribution arrangements. The case involved default-search agreements and the competitive significance of scale.

The later remedies process included requirements concerning access to certain search-index and user-interaction data for qualifying competitors.

Importance for data brokerage

The case demonstrates that data can contribute to competitive advantages when combined with scale and distribution.

The broader principle is that authorities should examine the complete competitive mechanism:

access → scale → information → product improvement → additional usage.

Possessing data alone is not the violation. The legal question concerns whether exclusionary conduct protects or reinforces market power.

2. United States v. Google LLC — Advertising Technology

Court: U.S. District Court for the Eastern District of Virginia
Case commenced: 2023
Major liability decision: 2025

The U.S. Department of Justice and participating states challenged Google's conduct in digital advertising technology under federal antitrust law.

The case concerned monopolization and attempted monopolization allegations involving technology connecting publishers and advertisers. The official case record identifies monopolization and tying among the alleged violations.

Importance

Advertising technology illustrates how information, platforms, technical infrastructure and intermediary services can interact.

For data brokerage, the case demonstrates why regulators examine not merely ownership of information but also control over infrastructure through which information is commercialised.

3. hiQ Labs, Inc. v. LinkedIn Corp.

Court: U.S. Court of Appeals for the Ninth Circuit

hiQ operated analytics services using information appearing on publicly accessible LinkedIn profiles.

LinkedIn attempted to prevent hiQ from scraping that information. Litigation followed concerning, among other matters, application of the Computer Fraud and Abuse Act.

The Ninth Circuit's analysis recognized the competitive significance of access to publicly available information. The record also included allegations that preventing access could eliminate a company competing in data analytics.

Importance

The case illustrates an important issue for data-driven competition:

Can control over access to information become a mechanism for excluding downstream analytics competitors?

It does not establish a general antitrust right to scrape websites. Instead, it demonstrates how restrictions on access to information can interact with competition between digital businesses.

4. FTC v. Kochava, Inc.

Court: U.S. District Court for the District of Idaho
Filed: 2022

The FTC alleged that Kochava's data-brokerage activities involving precise location information constituted unfair practices under the FTC Act.

The litigation addressed information capable of revealing visits to sensitive locations.

In 2026, the FTC announced an agreement that restricts Kochava and its subsidiary from selling, licensing, transferring, sharing or disclosing specified sensitive location information without affirmative express consent under the circumstances covered by the order.

Importance

This is particularly useful for understanding the structure of the data-broker industry.

However, it must be classified correctly: Kochava is primarily a consumer-protection/privacy case, not a finding of monopolization.

For competition analysis, it demonstrates that legal restrictions on collection and commercialisation can affect what constitutes a commercially available data input.

5. United States v. Microsoft Corp.

Court: U.S. Court of Appeals for the District of Columbia Circuit
Decision: 2001

Microsoft is a foundational monopolization precedent involving exclusionary practices in technology markets.

The litigation examined Microsoft's conduct designed to protect its operating-system monopoly from emerging competitive threats.

Importance for data brokerage

The case establishes a broader principle highly relevant to digital markets:

A dominant position itself is not automatically unlawful. The legal concern is the use of exclusionary conduct to maintain monopoly power.

Applied to data brokers, authorities would therefore distinguish between:

lawfully building a superior database

and

using exclusionary contractual or technical measures to prevent viable competitors from obtaining the inputs necessary to compete.

6. Aspen Skiing Co. v. Aspen Highlands Skiing Corp.

Court: U.S. Supreme Court
Decision: 1985

Aspen Skiing is a major U.S. monopolization precedent concerning refusal to continue a cooperative commercial arrangement with a competitor.

The Supreme Court found the circumstances capable of supporting monopolization liability.

Importance for data markets

The decision is frequently relevant to discussions about refusals to deal.

If a dominant data company terminates access to information previously supplied to competitors, competition lawyers may examine refusal-to-deal principles.

But Aspen Skiing is deliberately narrow. It does not establish a general rule requiring dominant businesses to share databases with competitors.

7. Verizon Communications Inc. v. Law Offices of Curtis V. Trinko, LLP

Court: U.S. Supreme Court
Decision: 2004

Trinko significantly limited the circumstances in which unilateral refusal to cooperate with competitors creates liability under U.S. monopolization law.

The Supreme Court emphasized that firms generally have substantial freedom to decide with whom they deal.

Importance for data brokerage

This is crucial where competitors demand access to a dominant company's information.

A company possessing unique information is not automatically required under U.S. antitrust law to license or share that information.

Accordingly, the fact that a database is commercially important does not by itself establish an antitrust duty to provide competitors with access.

8. FTC v. Actavis, Inc.

Court: U.S. Supreme Court
Decision: 2013

Although Actavis concerned pharmaceutical patent settlements rather than data brokerage, it provides another important competition-law principle.

The Supreme Court rejected the proposition that the existence of a lawful intellectual-property right automatically immunizes potentially anticompetitive agreements from antitrust scrutiny.

Importance for data brokerage

Data businesses frequently rely upon contracts, database rights, copyright, trade secrets and technological controls.

Possessing legitimate legal rights over information does not necessarily mean that every agreement concerning that information is immune from competition-law analysis.

10. Applying These Cases to Data Brokerage

Taken together, these authorities establish several useful principles.

Principle 1 — Data ownership does not automatically equal monopoly power

A business may possess enormous quantities of information while facing strong competitors possessing equivalent datasets.

Principle 2 — Replicability matters

If competitors can easily obtain comparable information, the incumbent's database is less likely to constitute a substantial barrier.

Principle 3 — Exclusion matters more than size alone

The most serious antitrust questions arise when powerful firms combine valuable data with exclusionary agreements, discriminatory access, tying or other conduct capable of restricting competition.

Principle 4 — Access obligations are exceptional

Aspen Skiing and Trinko demonstrate why competition law normally approaches mandatory sharing cautiously.

Principle 5 — Data and distribution must be analysed together

The Google litigation demonstrates that competitive advantages can arise from interacting factors such as scale, distribution, user activity and information.

Principle 6 — Privacy and antitrust must not be confused

Kochava demonstrates that conduct involving commercial data can raise serious legal concerns without necessarily constituting monopolization.

11. Data Brokerage Mergers

Data also matters during merger review.

Suppose:

Broker A + Broker B = combined company possessing unique datasets unavailable to competitors.

Authorities may examine whether the transaction would:

• eliminate direct competition;
• combine previously competing databases;
• increase barriers to entry;
• restrict downstream access to information;
• enable discriminatory access;
• strengthen network effects; or
• facilitate foreclosure.

The correct analysis is therefore not simply:

"How much data will the merged company own?"

The stronger question is:

"Will control of the combined information materially reduce competitive constraints or make effective entry substantially harder?"

12. Possible Remedies

Where competition violations involving data are established, remedies can potentially include:

• prohibiting exclusionary agreements;
• eliminating discriminatory contractual restrictions;
• requiring interoperability;
• restricting tying arrangements;
• requiring access to particular information under defined conditions;
• imposing merger conditions;
• preventing anticompetitive exclusivity; or
• structural remedies where legally justified.

Modern Google litigation illustrates that data-access and interoperability obligations can form part of remedies in digital-market monopolization cases.

Any access remedy must nevertheless consider privacy, security and intellectual-property obligations.

13. Economic Analysis

Economists examining data-broker market power may focus on four questions.

Substitutability

Can customers replace one broker's dataset with information from another provider?

Replicability

Could a new competitor reproduce the information within a commercially reasonable period and at reasonable cost?

Exclusivity

Does the incumbent have exclusive access to important information sources?

Competitive significance

Would losing access materially weaken a competitor?

These questions help distinguish genuinely strategic information from datasets that merely appear impressive because of their size.

14. Example

Assume three companies provide fraud-detection databases.

Company A: 70% market share
Company B: 20%
Company C: 10%

Company A signs long-term exclusive contracts with nearly every major supplier of transaction information.

A new competitor cannot create a comparable fraud-detection system because the underlying information is unavailable.

The competition problem would not simply be that Company A owns substantial data.

Authorities would investigate whether:

1. Company A possesses substantial market power;
2. the supplier agreements foreclose commercially important inputs;
3. competitors have realistic alternative information sources;
4. the restrictions increase barriers to entry;
5. legitimate efficiency explanations exist; and
6. the conduct produces anticompetitive effects.

That is the difference between data advantage and potentially anticompetitive data foreclosure.

15. Conclusion

Competition law increasingly treats data as a potentially important competitive asset, but large-scale data possession is not automatically unlawful market power.

The strongest competition concerns arise when several conditions combine:

market power + difficult-to-replicate data + high entry barriers + exclusionary conduct.

The cases discussed above show different parts of this framework. United States v. Google demonstrates how scale, distribution and information can reinforce digital-market power; hiQ Labs v. LinkedIn illustrates disputes over access to information used by analytics competitors; Microsoft provides foundational rules concerning exclusionary conduct by dominant technology companies; Aspen Skiing and Trinko define the narrow boundaries of refusal-to-deal liability; Actavis demonstrates that legal control over an asset does not necessarily remove competition scrutiny; and FTC v. Kochava illustrates the separate but increasingly connected regulation of commercial data practices.

Accordingly, competition analysis of data brokerage should focus not merely on how much information a company possesses, but on whether the information is competitively important, whether rivals can reproduce or substitute for it, how the company obtained its position, and whether contractual or technological practices unlawfully protect that position from effective competition.