Competition Law and Data-Driven Foreclosure Strategies

1. Introduction

Data has become an important competitive asset in modern digital markets. Search engines, social networks, online marketplaces, mobile operating systems, advertising platforms, payment systems, streaming services, and artificial-intelligence businesses may depend heavily on large quantities of user, transaction, behavioural, location, or commercial data.

A data-driven foreclosure strategy arises where a firm with substantial market power uses its control over data, data-generating infrastructure, or access to users in a manner capable of making it materially harder for actual or potential competitors to compete.

The competition-law concern is not that possessing a large dataset is automatically unlawful. Successful firms are generally allowed to collect data, improve their products, and benefit from legitimate investment and innovation. The concern arises where control over data is combined with conduct such as discriminatory access, exclusivity, tying, self-preferencing, interoperability restrictions, contractual limitations, acquisitions, or other exclusionary practices.

In EU competition law, such conduct may principally be examined under Article 102 TFEU where the undertaking is dominant. Agreements involving data may also fall within Article 101 TFEU, while acquisitions of strategically important datasets or data-intensive businesses may raise merger-control concerns.

2. Meaning of Data-Driven Foreclosure

Foreclosure in competition law generally means conduct that restricts competitors' ability to obtain customers, inputs, distribution opportunities, or other resources necessary for effective competition.

Data-driven foreclosure can therefore be understood as foreclosure in which data, access to data, or the ability to generate data forms an important part of the exclusionary mechanism.

A typical structure may look like:

Large user base → more data → better service/targeting → more users → still more data

This feedback mechanism can create substantial competitive advantages.

It does not itself establish an infringement. Competition authorities normally need to examine matters such as market power, the importance of the data, availability of alternative datasets, network effects, switching costs, interoperability, barriers to entry, and the actual or likely effects of the challenged conduct.

3. Main Forms of Data-Driven Foreclosure

A. Refusal or Restriction of Access to Data

A vertically integrated company may possess information that downstream competitors would find valuable.

For example, a platform could operate both an infrastructure service and its own competing retail service. If third-party businesses receive materially poorer access to information than the platform's own service, competition concerns can arise.

However, competition law does not ordinarily create a general obligation to share valuable data with competitors. Particularly demanding legal requirements may apply where a claimant effectively seeks mandatory access to an asset or infrastructure.

B. Exclusive Data Arrangements

A company can seek contractual arrangements under which suppliers, advertisers, merchants, publishers, or other partners provide important information exclusively to it.

Such exclusivity can become problematic where competitors are prevented from obtaining sufficient alternative data to develop competing services.

C. Data Combination

A platform operating several services may combine information generated by each service.

Combining datasets can produce substantial efficiencies—for example, improved fraud prevention, personalisation, security, or product development. But where a dominant undertaking obtains a unique data advantage unavailable to rivals, competition authorities may examine whether the method by which the advantage is obtained reinforces or extends market power.

D. Self-Preferencing

A vertically integrated digital platform can possess information concerning both its own services and competing businesses using the platform.

Competition concerns may arise where the platform uses its position in an upstream or gateway market to systematically favour its own downstream service.

The legal issue is therefore broader than simple possession of data: it concerns the relationship between information advantages, platform control and preferential treatment.

E. Interoperability Restrictions

Competitors frequently require interoperability with dominant digital ecosystems.

Restricting APIs, technical interfaces, portability, or interoperability may increase rivals' costs or prevent them from obtaining information necessary to provide competing services.

The assessment is highly fact-specific because interoperability restrictions may also have legitimate explanations involving privacy, cybersecurity, system integrity, intellectual property, or investment incentives.

F. Tying and Bundling

A firm may connect a data-rich service to another product.

This can help the firm generate additional information across multiple services while simultaneously limiting rivals' opportunities to obtain scale.

Competition authorities may investigate whether tying or bundling gives rivals a realistic opportunity to compete or instead strengthens an existing position through exclusionary mechanisms.

G. Acquisitions of Data-Rich Businesses

Merger control can also address data foreclosure.

An established platform may acquire a company possessing a valuable dataset, technology, user base, or data-generating capability.

Authorities may investigate whether the transaction could:

• eliminate an emerging competitive constraint;
• combine uniquely valuable datasets;
• allow restriction of rivals' access to an important input;
• strengthen network effects;
• raise barriers to entry; or
• reduce incentives for independent innovation.

Again, possession or acquisition of data alone does not establish competitive harm.

Important Case Law and Enforcement Examples

1. Google and Alphabet v Commission — Google Shopping

General Court, Case T-612/17 (2021), followed by the Court of Justice appeal proceedings

The Google Shopping litigation is important for understanding digital foreclosure even though the central legal theory was preferential treatment rather than a standalone refusal to supply data.

The European Commission concluded that Google had abused its dominant position by favouring its own comparison-shopping service in its general search results while rival comparison-shopping services were treated differently.

The General Court substantially upheld the Commission's findings.

The significance for data-driven markets is the interaction between platform control, user traffic, search positioning and the ability to generate further interactions and information.

A service receiving substantially greater visibility may obtain more users. More interactions can, depending on the service, improve its commercial position and generate additional information. Conversely, reduced visibility can make achieving competitive scale considerably harder.

The litigation consequently demonstrates how platform architecture and preferential access to users can operate as foreclosure mechanisms without requiring a conventional refusal to deal.

2. Google and Alphabet v Commission — Google Android

General Court, Case T-604/18, Judgment of 14 September 2022

This case concerned Google's Android ecosystem, including Google Search, Chrome, the Play Store and agreements with device manufacturers and mobile network operators.

The Commission had identified several practices involving product bundling, exclusivity payments and anti-fragmentation obligations. The General Court's 2022 judgment largely upheld the Commission's case, although it annulled the finding concerning certain portfolio-based revenue-sharing agreements and adjusted the fine.

The case is particularly relevant because search markets can involve strong feedback mechanisms:

pre-installation/default exposure → usage → queries and interactions → service improvement/commercialisation → continued usage

The judgment therefore illustrates how distribution restrictions and ecosystem control can reinforce competitive advantages associated with scale and user interaction.

It also demonstrates an important principle: competition law does not necessarily attack the possession of data itself. The analysis concerns the conduct used to preserve or extend market power.

3. Bundeskartellamt v Facebook / Meta

Bundeskartellamt decision (2019); German Federal Court proceedings (2020); CJEU Case C-252/21, Meta Platforms and Others (2023)

This is one of the clearest examples of the intersection between competition law and control over personal data.

Germany's Bundeskartellamt objected to conditions allowing Facebook to combine information associated with Facebook accounts with information originating from other Meta services and third-party sources without the form of user choice required by the authority's decision.

The case eventually reached the Court of Justice through questions referred by the Düsseldorf Higher Regional Court.

In 2023, the CJEU confirmed, among other points, that a competition authority examining abuse of dominance may consider compliance with data-protection rules where that examination is necessary for deciding whether conduct constitutes an abuse, while coordinating appropriately with data-protection authorities.

The competition significance is substantial.

Extensive data collection can potentially produce:

more information → improved targeting/service → stronger monetisation → increased market strength

Competitors possessing smaller user networks may find this advantage difficult to replicate.

The German proceeding was ultimately concluded in 2024 following measures giving users greater options concerning combination of their information; Meta withdrew its remaining appeal.

The case demonstrates that privacy, data protection and competition are legally distinct fields but can intersect where data-processing conditions contribute to the exercise or reinforcement of market power.

4. Microsoft Corp. v Commission

Case T-201/04, General Court, 2007

The Microsoft judgment predates today's platform economy but remains fundamental to debates concerning access to information and interoperability.

The Commission found, among other matters, that Microsoft's refusal to provide certain interoperability information concerning work-group server operating systems constituted an abuse of dominance.

The General Court upheld the central findings.

The case established an important analytical foundation for modern data-access disputes.

A dominant undertaking is not normally required simply to surrender commercially valuable resources to competitors. However, under exceptional circumstances, withholding access to information necessary for interoperability can constitute abuse.

Its modern relevance can be seen in disputes involving:

• APIs;
• technical specifications;
• interoperability information;
• platform interfaces;
• ecosystem compatibility; and
• potentially indispensable datasets.

The important distinction is between protecting legitimate investment incentives and allowing control of an upstream resource to eliminate effective downstream competition.

5. IMS Health GmbH & Co. OHG v NDC Health GmbH

Case C-418/01, Court of Justice, 2004

IMS Health concerned access to a copyrighted structure used for pharmaceutical sales information.

The case is highly relevant to modern arguments that competitors should receive access to information controlled by a dominant undertaking.

The Court applied strict requirements concerning compulsory licensing.

Among the relevant considerations were whether the protected input was indispensable, whether refusal prevented the emergence of a new product for which there was potential consumer demand, whether the refusal lacked objective justification, and whether it reserved a secondary market to the rights holder.

The significance for data foreclosure is clear:

A competitor cannot simply argue:

“The dominant company has better data, therefore it must share it.”

Competition law ordinarily requires substantially more.

Authorities must examine whether alternative information can realistically be obtained or created and whether the legal requirements governing compulsory access are satisfied.

6. Bronner

Case C-7/97, Oscar Bronner GmbH & Co KG v Mediaprint

Bronner concerned access to a newspaper home-delivery system rather than digital information, but it remains central to the law governing compulsory access to dominant firms' assets.

The Court imposed a demanding standard for compulsory access.

In particular, the relevant facility had to be genuinely indispensable rather than merely more convenient or economically attractive.

Bronner therefore matters enormously to data-access disputes.

Suppose Company A possesses a superior consumer dataset and Company B argues that competition requires access.

The correct legal question is not simply whether access would make B more competitive.

The analysis may instead ask:

Can a competitor realistically create or obtain an alternative?

If viable substitutes exist, a compulsory-sharing argument becomes considerably more difficult.

Bronner consequently protects incentives to invest while leaving open intervention in sufficiently exceptional foreclosure circumstances.

7. Slovak Telekom v Commission

Case C-165/19 P, Court of Justice, 2021

Slovak Telekom is important because it clarifies the relationship between refusal-to-supply doctrine and other forms of exclusionary conduct involving access.

The dispute involved access to telecommunications infrastructure and conditions imposed by a dominant operator.

The Court explained that the exceptionally strict Bronner indispensability requirements do not automatically govern every abusive practice connected with access to infrastructure.

That distinction has considerable relevance to digital markets.

There is an important difference between:

1. requiring a dominant company to provide access that it had never previously provided; and
2. challenging unfair or exclusionary conditions governing access that is already being supplied.

Applied to data, a company that voluntarily provides an API or dataset but allegedly imposes discriminatory conditions may therefore present a different legal problem from a company being asked to create completely new access for competitors.

8. Meta Platforms / Within Unlimited — United States

The U.S. Federal Trade Commission challenged Meta's proposed acquisition of Within Unlimited, developer of the VR fitness application Supernatural.

The FTC argued that the transaction could harm competition and innovation in VR fitness markets. Meta already operated major parts of the VR ecosystem, including VR hardware, an app store and applications.

A federal court declined to grant the requested preliminary injunction, and the FTC subsequently dismissed its administrative complaint in February 2023.

This outcome is important because it shows that theories concerning digital ecosystems, platform advantages and future competition still require sufficient evidence under the governing merger-law standard.

Data, ecosystem position and network effects can be relevant evidence, but they do not substitute for demonstrating the required competitive harm.

4. Legal Test for Data-Driven Foreclosure

A useful competition-law framework involves several stages.

Step 1 — Define the Relevant Market

Authorities determine the relevant product/service and geographic markets.

Digital businesses complicate this exercise because platforms may be multi-sided and may offer monetary-zero-price services to one user group while monetising another side through advertising, subscriptions, commissions or complementary services.

Step 2 — Establish Market Power or Dominance

Large quantities of data alone do not prove dominance.

Relevant factors may include market shares, network effects, switching costs, multi-homing, barriers to entry, access to users, economies of scale and scope, ecosystem integration, and availability of comparable datasets.

Step 3 — Identify the Relevant Data Advantage

Authorities can ask:

What information does the undertaking possess?

How is it generated?

Can competitors acquire comparable information?

How quickly does the information lose value?

Can users transfer it?

Can competitors generate substitutes?

The economic characteristics of data matter greatly.

Some information can easily be replicated. Other datasets become competitively valuable because of enormous scale, historical depth, exclusivity, real-time collection or combination with complementary datasets.

Step 4 — Identify the Exclusionary Conduct

The authority must normally identify conduct beyond simply being successful.

Potential mechanisms include:

Dominant position + strategic data advantage + exclusionary practice → potential foreclosure

Relevant practices could include discriminatory access, exclusivity, tying, self-preferencing, interoperability restrictions or strategically designed access conditions.

Step 5 — Examine Foreclosure Effects

The next question is whether equally efficient or otherwise competitively significant rivals are materially disadvantaged.

Possible evidence includes increased entry costs, reduced access to users, inability to achieve minimum scale, declining interoperability, reduced innovation incentives or barriers to effective expansion.

Step 6 — Consider Objective Justification and Efficiencies

Not every restriction is abusive.

Companies may invoke legitimate reasons including cybersecurity, privacy protection, fraud prevention, intellectual-property protection, system integrity, quality assurance or investment incentives.

Authorities must consider these explanations under the applicable legal framework rather than assuming that all restrictions on data access are anticompetitive.

5. Data as a Barrier to Entry

Data becomes especially important where learning effects exist.

Imagine two competing services.

Platform A has 100 million interactions from which its system can learn, while a new entrant begins with comparatively little information.

More interactions may improve recommendations, matching, fraud detection or advertising effectiveness.

That can produce a feedback cycle:

Users → Data → Better service → More users → More data

Competition law sometimes describes these dynamics through concepts such as network effects, scale economies and barriers to entry.

But the cycle must be demonstrated rather than assumed. In some markets, relatively small datasets are sufficient; public or purchased datasets may be substitutes; users may multi-home; and technological innovation can overcome an incumbent's informational advantage.

6. Data Foreclosure and the Essential Facilities Doctrine

One of the most difficult questions is whether competition law can require a dominant company to provide competitors with data.

The essential-facilities line of cases, particularly Bronner, IMS Health and Microsoft, provides important guidance.

A simplified distinction is:

Useful data ≠ automatically essential data.

A competitor generally needs much stronger evidence than showing that obtaining the incumbent's dataset would reduce its costs.

Depending on the precise legal theory and jurisdiction, questions may include indispensability, realistic alternatives, elimination of effective competition, objective justification, and effects on innovation.

This demanding approach reflects an important competition-policy trade-off.

Excessively broad mandatory sharing can weaken incentives to create databases and infrastructure, while excessively restrictive access policies can in some circumstances permit control over an indispensable input to protect adjacent markets.

7. Privacy Law and Competition Law

The Facebook/Meta litigation demonstrates that privacy and competition can interact.

However, they pursue different objectives.

Data-protection law principally regulates lawful processing and protection of personal information.

Competition law principally protects the competitive process.

A privacy violation therefore does not automatically constitute an antitrust violation, and an antitrust infringement does not automatically constitute a privacy violation.

Nevertheless, the same behaviour can become relevant to both legal regimes.

The CJEU's 2023 Meta judgment confirmed that competition authorities may, in appropriate circumstances, take data-protection rules into account when assessing abuse of dominance, while respecting the institutional role of the authorities responsible for GDPR enforcement.

8. Consumer Harm and Innovation Harm

Data foreclosure need not produce an immediate price increase.

Many digital services have a zero monetary price.

Competition authorities may therefore examine other dimensions of competition, including:

• service quality;
• privacy;
• consumer choice;
• innovation;
• interoperability;
• advertising conditions;
• switching possibilities; and
• development of new products.

A strategy that prevents innovative competitors from reaching sufficient scale may potentially reduce future competition even where today's consumer price remains unchanged.

At the same time, authorities need evidence connecting the challenged practice to likely competitive harm rather than treating concentration of data as inherently unlawful.

9. Summary of the Case-Law Principles

The major authorities illustrate different parts of the doctrine:

Conclusion

Data-driven foreclosure is best understood as the strategic use of control over data, data-generating infrastructure, users, interfaces, or digital ecosystems in ways capable of restricting effective competition.

Modern competition law therefore focuses less on the proposition that “big data is illegal” and more on the combination of market power + conduct + competitive effects.

The case law also establishes an important balance. Bronner and IMS Health demonstrate that competitors cannot ordinarily demand access merely because another firm's information is commercially valuable. Microsoft shows that access or interoperability obligations can nevertheless arise in exceptional circumstances. Google Shopping and Google Android demonstrate that foreclosure can operate through platform design, distribution and preferential treatment rather than an outright denial of data. Meta/Facebook demonstrates how accumulation and combination of personal information can intersect with dominance and data-protection rules.