Digital Persuasion Systems and Platform Dominance Risks

Introduction

Digital persuasion systems are technological systems through which online platforms influence users’ choices, attention, purchasing decisions, consumption patterns, or engagement. They include recommendation algorithms, personalised advertising, behavioural profiling, dark patterns, ranking systems, notifications, default settings, recommender engines, targeted offers, and algorithmically optimised interfaces.

From a competition-law perspective, persuasion becomes particularly significant when it is controlled by a dominant digital platform. A platform with substantial market power can use its control over data, interfaces, rankings, defaults, and user attention to reinforce its position and make competing products or services less visible, less attractive, or more difficult to access.

The central concern is therefore not simply that an algorithm persuades consumers. The competition concern arises when persuasive architecture becomes an instrument for exclusion, leveraging, self-preferencing, tying, exploitation, or the creation of durable entry barriers.

1. Meaning of Digital Persuasion Systems

Digital persuasion systems can be understood as algorithmically designed mechanisms intended to influence user behaviour.

They include:

1. Recommendation algorithms – determine what content, products, videos or services users see.
2. Personalised advertising – uses behavioural and contextual data to target particular users.
3. Ranking systems – determine the order in which competing products or services appear.
4. Dark patterns – interface designs that steer users toward particular choices.
5. Default settings – automatically select a platform's own product or service.
6. Behavioural nudging – notifications, reminders, prompts and incentives designed to increase engagement.
7. Personalised pricing or offers – different users may receive different commercial incentives.
8. Cross-service profiling – data collected from one service can improve persuasion in another.
9. Self-preferencing interfaces – the platform can position its own products more prominently.
10. Attention optimisation – algorithms optimise for engagement, retention or time spent on the platform.

The competition-law problem becomes acute where a dominant undertaking possesses both the ability to influence user behaviour and the economic incentive to influence that behaviour in favour of its own ecosystem.

2. Why Persuasion Can Become a Competition Problem

Ordinary advertising is not automatically anti-competitive. Businesses routinely attempt to persuade consumers.

The issue changes where a dominant platform possesses:

• large-scale behavioural data;
• control over a critical interface;
• network effects;
• switching costs;
• ecosystem lock-in;
• control over rankings;
• control over defaults;
• privileged access to consumer attention;
• ability to combine data across services; and
• ability to discriminate between its own services and competitors.

The platform may then convert informational advantage into structural market power.

A simplified model is:

Data → Profiling → Prediction → Persuasion → Behavioural change → More data → Stronger market position

This creates a potential data-attention-feedback loop.

3. Digital Persuasion and Self-Preferencing

A dominant platform may control the interface through which users access a downstream market.

For example:

Platform → marketplace → ranking algorithm → consumers

If the platform places its own products above competing products, the persuasion system may effectively become an exclusionary mechanism.

The issue is particularly serious where users rarely examine results beyond the first few rankings.

Thus:

Ranking power + consumer dependence + self-preferencing = potential foreclosure

The competition authority would normally need to establish more than mere algorithmic preference. It would examine whether the conduct:

• disadvantages rivals;
• affects competition on the merits;
• exploits platform gatekeeper power;
• reduces consumer choice;
• raises barriers to entry; or
• strengthens the dominant position.

4. Recommendation Algorithms as Competitive Gatekeepers

Recommendation systems can operate as private gatekeepers of attention.

A platform may decide:

• which seller appears first;
• which application is recommended;
• which video becomes popular;
• which news source receives visibility;
• which restaurant appears prominently;
• which financial product is suggested.

Where the platform is dominant, algorithmic ranking can therefore affect market access itself.

This creates a distinctive competition concern:

The platform does not merely compete in the market; it controls the mechanism through which competitors reach consumers.

That can create conflicts between:

• platform neutrality and commercial incentives;
• user welfare and platform monetisation;
• relevance ranking and self-preferencing;
• personalisation and discrimination;
• innovation and foreclosure.

5. Dark Patterns and Dominant Platforms

Dark patterns are interface practices that manipulate consumers into decisions they might not otherwise make.

Examples include:

• difficult cancellation;
• pre-selected options;
• misleading consent buttons;
• repeated prompts;
• hidden alternatives;
• countdown mechanisms;
• confusing subscription flows;
• forced account creation;
• asymmetric presentation of choices.

From a competition perspective, dark patterns become more significant where a dominant platform uses them to:

1. increase dependence on its ecosystem;
2. discourage switching;
3. prevent users from choosing rival services;
4. obtain additional data;
5. strengthen network effects; or
6. reinforce its dominant position.

Consequently, consumer protection and competition law can overlap.

6. Personalisation and Market Segmentation

Personalisation allows a platform to tailor its persuasion strategy to individual users.

A platform may know:

• what the user searches for;
• what products the user previously purchased;
• how frequently the user interacts;
• which advertisements attract attention;
• which competing services the user uses;
• how price-sensitive the user appears to be.

This creates a potential information asymmetry.

The dominant platform can potentially identify:

who can be persuaded, how they can be persuaded, and when they are most susceptible to persuasion.

In competitive markets, this information advantage may be legitimate. But when combined with substantial market power, it may contribute to exclusionary or exploitative conduct.

7. Network Effects and Persuasion

Digital platforms frequently benefit from network effects.

More users → more data → better personalisation → better recommendations → more engagement → more users.

This can produce a reinforcing cycle:

Scale → Data → Personalisation → Engagement → Scale

The problem for competition is that a smaller entrant may be unable to reproduce the same level of behavioural data.

Consequently, persuasion technology can become an entry barrier.

A new competitor may have an innovative product but lack:

• sufficient behavioural data;
• user history;
• advertising inventory;
• recommendation infrastructure;
• prediction models;
• cross-platform datasets.

Thus, data-driven persuasion can strengthen incumbent advantages independently of product quality.

8. Platform Dominance and Consumer Choice Architecture

A dominant platform can effectively determine the choice architecture presented to consumers.

Consider:

Choice A – platform's own service
Large button + default + recommendation + personalised discount

Choice B – rival service
Small link + additional steps + reduced visibility

Even if the rival technically remains available, the platform may have altered the competitive environment.

Competition law therefore increasingly has to examine not merely:

“Can the consumer choose the rival?”

but also:

“How has the dominant platform structured the environment in which that choice is made?”

9. Data Combination as a Persuasion Advantage

A platform operating multiple services can potentially combine data from:

• search;
• social media;
• maps;
• shopping;
• payments;
• video;
• advertising;
• communications.

Cross-service data combination can improve behavioural prediction.

The competition concern is that a rival may be unable to obtain an equivalent dataset.

This can create a form of data-based competitive asymmetry.

The analysis may therefore include:

• data access;
• data portability;
• interoperability;
• purpose limitation;
• consent;
• cross-use of data;
• data accumulation;
• switching costs.

10. Digital Persuasion and Tying

A dominant platform might use persuasive interface design to encourage users of one product to adopt another product.

For example:

Operating system → default browser → search engine → advertising ecosystem

or:

Marketplace → payment system → financial service

The relevant question is whether the platform is merely recommending its complementary product or using its dominant position to foreclose competing suppliers.

The stronger the dependence of users on the platform, the greater the competition concern.

11. Digital Persuasion and Exploitative Abuse

Persuasion can also have an exploitative dimension.

A dominant platform may potentially use its informational advantage to:

• extract excessive personal data;
• impose disadvantageous terms;
• reduce privacy;
• manipulate consumer choice;
• impose behavioural restrictions;
• make withdrawal difficult.

Competition law traditionally focuses heavily on prices and output. Digital markets complicate this because privacy, attention, autonomy and choice can themselves become competitive parameters.

A deterioration in non-price quality can therefore become relevant to competitive analysis.

12. Relevant Case Laws

1. Google Search (Shopping) — European Commission / General Court

Google Search (Shopping) is one of the most important authorities concerning digital ranking and platform self-preferencing.

The European Commission found that Google systematically positioned and displayed its comparison-shopping service more favourably in its general search results while applying less favourable ranking mechanisms to competing comparison-shopping services.

The General Court substantially upheld the Commission's approach.

Relevance to digital persuasion

The case demonstrates how control over search visibility can affect competition.

The platform's ranking mechanism was not merely technical. It determined how consumers encountered competing services.

The broader principle is:

A dominant platform's control over ranking and visibility can become a competitive weapon where it systematically advantages its own service.

This is directly relevant to algorithmic recommendation systems.

2. Google Android — European Commission / General Court

The Google Android litigation concerned Google's practices involving the Android ecosystem, including contractual arrangements connected with search, browsers and app distribution.

The case illustrates the importance of defaults, pre-installation and ecosystem architecture.

Relevance

A dominant platform can influence user behaviour through the structure of its operating system.

The competitive effect may arise not from an outright prohibition on rivals but from making the incumbent product:

• immediately available;
• prominently displayed;
• technically integrated; and
• easier to use.

This demonstrates why choice architecture can have exclusionary consequences.

3. Google Android Auto — Google and Alphabet v European Commission

The Google Android Auto dispute concerned Google's treatment of third-party applications seeking access to the Android Auto environment.

Relevance

The case illustrates the importance of platform access and interface control.

A platform that controls an operating environment may determine which complementary applications can effectively reach users.

Where the platform is dominant, technical access decisions can therefore have consequences comparable to traditional forms of market foreclosure.

4. Amazon Marketplace — European Commission

The European Commission's investigation into Amazon's use of marketplace data examined how Amazon could use non-public seller data generated through its marketplace.

The Commission also addressed Amazon's treatment of sellers in relation to the Buy Box.

Relevance

This is highly relevant to digital persuasion because the marketplace controls:

• product visibility;
• ranking;
• consumer attention;
• purchasing interfaces; and
• seller access to demand.

The case illustrates a structural conflict:

A platform can simultaneously operate the marketplace and compete against businesses dependent on that marketplace.

When the platform controls the interface, ranking or purchasing architecture, it may possess significant opportunities to influence consumer choices.

5. Google AdSense — European Commission / General Court

The Google AdSense case concerned contractual restrictions associated with Google's online search advertising intermediation business.

The Commission considered how contractual restrictions could prevent competing advertising services from obtaining effective access to publishers.

Relevance

Digital persuasion depends heavily upon advertising intermediation.

Control over advertising infrastructure can therefore allow a dominant undertaking to influence:

• advertisers;
• publishers;
• consumer targeting;
• advertising inventory; and
• rival advertising intermediaries.

The case illustrates how control over the infrastructure of persuasion can itself become a competition issue.

6. Facebook / Meta — German Federal Cartel Office (Bundeskartellamt)

The German competition authority's Facebook proceedings concerned the combination of user data from different Facebook/Meta services and third-party sources.

The case became particularly important because it connected data collection, consumer autonomy and market power.

Relevance

The case demonstrates that privacy-related conditions may become relevant to competition law when imposed by a dominant platform.

The broader concern is:

Market power → extensive data collection → greater behavioural knowledge → stronger personalisation → greater competitive advantage

This makes data combination potentially relevant not merely as a privacy issue but as part of the competitive structure of digital markets.

7. Booking.com — European Commission / National Competition Authorities

The Booking.com litigation concerning parity clauses illustrates how platform contractual conditions can affect competition between suppliers and alternative distribution channels.

Relevance

Digital platforms can influence consumer purchasing decisions while simultaneously imposing conditions upon businesses that depend on their platform.

This creates a potential dual-sided persuasion structure:

Platform controls consumer attention + platform controls supplier access

The greater the platform's importance as a distribution channel, the greater the potential competitive significance of its contractual and ranking practices.

8. Apple App Store — European Commission / EU Competition Authorities

The European competition-law proceedings involving Apple's App Store practices demonstrate the importance of platform rules governing app distribution and payments.

Relevance

Apple controls a major interface through which developers reach consumers.

This gives the platform influence over:

• discoverability;
• payment systems;
• app distribution;
• commissions;
• alternative commercial channels.

The broader competition question is whether platform rules can transform control of the interface into control over downstream competition.

13. Common Competition Risks

14. Theories of Harm

Several competition theories can potentially apply.

A. Foreclosure

The platform's persuasion system may reduce rivals' ability to reach consumers.

B. Self-preferencing

The dominant undertaking may systematically favour its own services.

C. Tying

Users may be nudged or technically directed toward complementary services.

D. Leveraging

Power in one market may be transferred into another market.

E. Exploitative conduct

Users may face deteriorated privacy, autonomy or choice.

F. Raising rivals' costs

Competitors may need to spend substantially more to obtain comparable visibility.

G. Entry barriers

Data, network effects and behavioural optimisation may make entry increasingly difficult.

H. Consumer lock-in

Personalisation and customised ecosystems may increase switching costs.

15. The Feedback-Loop Problem

One of the most important risks is a self-reinforcing algorithmic feedback loop.

Suppose a dominant platform gives its own product greater visibility.

Greater visibility
↓
More users
↓
More behavioural data
↓
Better recommendation accuracy
↓
Higher conversion
↓
More commercial success
↓
Greater investment in the platform
↓
Even stronger visibility

This means that relatively small initial advantages can potentially become structural advantages.

Competition authorities therefore need to examine not merely current market shares but also dynamic feedback effects.

16. Algorithmic Opacity

Another difficulty is that the platform may not publicly disclose how its recommendation or ranking system operates.

This creates an evidentiary problem.

A regulator may need to determine:

• what variables affect ranking;
• whether the algorithm treats the platform's own products differently;
• whether rivals receive systematically inferior exposure;
• how frequently algorithms change;
• whether discriminatory effects are intentional;
• whether ranking changes correlate with commercial incentives.

Consequently, algorithmic transparency, auditability and access to internal platform data may become important enforcement tools.

17. Intent Versus Effect

A platform may argue:

“The algorithm was designed to maximise relevance or user experience, not to exclude competitors.”

Competition law therefore should not necessarily depend exclusively on proving subjective intent.

The important questions may include:

1. What was the algorithm's actual effect?
2. Were rivals systematically disadvantaged?
3. Did the platform possess market power?
4. Was there a legitimate technical justification?
5. Could the same objective have been achieved through less exclusionary means?
6. Did the conduct strengthen existing entry barriers?

Thus, algorithmic effect can be more important than algorithmic intent.

18. Consumer Welfare and Digital Autonomy

Traditional consumer welfare analysis often focuses on:

• price;
• output;
• quality;
• innovation.

Digital persuasion introduces additional dimensions:

• choice;
• privacy;
• autonomy;
• attention;
• transparency;
• interoperability;
• switching ability.

This raises a broader question:

Should competition law protect only consumers' economic welfare, or also the competitive conditions that preserve meaningful consumer choice?

Different jurisdictions may answer this differently.

19. Interaction With the Digital Markets Act

The EU Digital Markets Act (DMA) is particularly important because it addresses several practices that historically required complex abuse-of-dominance litigation.

The DMA's framework is relevant to:

• self-preferencing;
• combining and using personal data;
• interoperability;
• switching;
• ranking;
• platform access;
• app-store restrictions;
• steering.

Therefore, digital persuasion increasingly exists within a dual regulatory environment:

Traditional competition law + ex ante digital-platform regulation

This reduces reliance on proving harm only after a dominant platform's conduct has already substantially distorted the market.

20. Regulatory Challenges

Competition authorities face several difficulties.

1. Algorithmic complexity

The decision-making process may involve machine-learning models that are difficult to interpret.

2. Rapid technological change

Competitive conditions can change faster than litigation.

3. Multi-sided markets

Platforms simultaneously interact with consumers, advertisers, sellers, developers and other businesses.

4. Non-price competition

The relevant harm may involve visibility, privacy or choice rather than higher prices.

5. Data asymmetry

The regulator may lack access to the information necessary to establish algorithmic discrimination.

6. Counterfactual difficulty

It may be difficult to establish what consumer behaviour would have looked like without the platform's intervention.

21. Appropriate Remedies

Possible remedies include:

Structural remedies

• divestiture;
• separation of platform and downstream operations;
• limits on acquisitions.

Behavioural remedies

• prohibition of self-preferencing;
• ranking neutrality;
• non-discrimination requirements;
• restrictions on data combination.

Data remedies

• data portability;
• interoperability;
• access to certain datasets;
• restrictions on cross-service data use.

Interface remedies

• meaningful choice screens;
• neutral defaults;
• easier switching;
• cancellation symmetry.

Algorithmic remedies

• independent audits;
• algorithmic monitoring;
• reporting obligations;
• preservation of algorithmic records.

The remedy should address the source of the competitive advantage, rather than merely correcting an isolated algorithmic outcome.

22. Key Legal Principle

The central competition-law principle can be expressed as follows:

A dominant digital platform should not be permitted to convert control over consumer attention and choice architecture into an instrument for excluding competitors from markets in which the platform itself competes.

Digital persuasion therefore becomes a competition concern when persuasive power, data power, interface control and market dominance reinforce one another.

Conclusion

Digital persuasion systems represent a new dimension of platform power. Search rankings, recommendations, defaults, targeted advertising, personalised interfaces and behavioural nudges can influence not only individual consumer decisions but also the structure of entire digital markets.

The most important competition-law concern is the combination of:

Dominance + Data + Algorithmic Personalisation + Interface Control + Network Effects

When these elements interact, a platform can potentially transform consumer persuasion into market foreclosure and ecosystem entrenchment.