1. Introduction

Influence Measurement Markets are emerging markets in which firms measure, quantify, attribute, certify, or rank the influence generated by advertising, social-media activity, creators, platforms, search results, digital content, recommendation systems, and other forms of attention-based commerce.

Traditional audience measurement generally asks:

• How many people saw an advertisement?
• How frequently was it viewed?
• Which demographic groups were reached?

Modern influence measurement goes considerably further. It may attempt to determine:

• whether a person was persuaded;
• whether a consumer's purchasing decision was influenced;
• whether an influencer generated measurable sales;
• whether a recommendation changed user behaviour;
• how much "influence" a particular creator or platform possesses;
• whether a digital campaign generated attributable economic value;
• which content, algorithm or recommendation caused a conversion; and
• what economic value should be assigned to attention, engagement, reputation or behavioural change.

Competition law therefore faces a new question: can control over the infrastructure used to measure influence itself become a source of market power?

The issue is not merely hypothetical. Competition authorities have already treated advertising-expenditure measurement and cross-platform audience measurement as distinct markets. The FTC, for example, identified advertising-expenditure measurement services as a relevant market in the VNU/Nielsen matter and described significant barriers arising from technology, historical datasets, long-term contracts and reputation for accuracy.

The UK's CMA has likewise identified verification, attribution and effectiveness measurement as important components of digital advertising competition.

2. Meaning of Influence Measurement Markets

An influence measurement market can be understood as a market for services that transform behavioural or attention data into commercially usable measurements of influence.

Typical services include:

1. Audience measurement
2. Reach and frequency measurement
3. Attribution services
4. Conversion measurement
5. Influencer-performance measurement
6. Brand-lift measurement
7. Engagement analytics
8. Cross-platform identity resolution
9. Recommendation-effect measurement
10. Attention measurement
11. Sentiment and behavioural analysis
12. Influence scoring and benchmarking

The market may therefore contain several interconnected layers:

Data collection → identity matching → attribution → analytics → influence score → commercial certification → advertising decisions

The company controlling several layers may possess substantial strategic advantages.

3. Why Influence Measurement Matters to Competition Law

Measurement is not simply an administrative function.

Suppose an advertising platform controls:

• the advertising inventory;
• user data;
• the attribution technology;
• the measurement standard;
• the performance dashboard; and
• the certification of campaign effectiveness.

It could potentially occupy a measurement bottleneck between advertisers and publishers.

The CMA has specifically recognised that advertisers need to evaluate the quality and effectiveness of digital advertising inventory in order for effective competition to operate.

Thus, a measurement provider can potentially influence competition in two directions:

A. Market power in the measurement market

The measurement provider itself may become dominant.

B. Measurement power in another market

A dominant advertising or platform undertaking may control the measurement mechanism used to assess competitors.

The second problem may be particularly significant because the platform can potentially become both market participant and market referee.

4. Relevant Competition-Law Framework

A. Relevant Market

Authorities may define markets around:

• advertising expenditure measurement;
• audience measurement;
• cross-platform measurement;
• digital attribution;
• campaign-effectiveness measurement;
• influencer analytics;
• advertising verification;
• data analytics;
• identity-resolution services.

The VNU/Nielsen proceeding demonstrates that a specialised measurement service can constitute a distinct relevant market rather than simply being treated as an incidental component of advertising.

B. Market Power

Traditional market-share analysis may become insufficient.

Relevant indicators may include:

• unique datasets;
• historical measurement records;
• proprietary panels;
• exclusive access to platform data;
• interoperability;
• measurement standards;
• network effects;
• switching costs;
• accreditation;
• reputation for accuracy;
• API access;
• algorithmic sophistication; and
• control over industry benchmarks.

The FTC's VNU/Nielsen analysis expressly identified technology, historical data, long-term contracts and reputation for accuracy as barriers to entry.

5. Data as a Competitive Asset

Influence measurement increasingly depends upon enormous quantities of data.

For example:

User → impression → click → engagement → purchase → repeat purchase

If only one platform can observe the complete chain, independent measurement becomes difficult.

This produces a potential data advantage.

A dominant platform may possess:

• first-party behavioural data;
• conversion data;
• browsing information;
• transaction data;
• engagement data;
• demographic information;
• identity graphs; and
• historical campaign information.

Competitors may possess only fragments.

Future competition authorities may therefore have to examine whether withholding measurement-relevant data constitutes:

• exclusionary conduct;
• discriminatory access;
• self-preferencing;
• tying;
• refusal to supply;
• interoperability restriction; or
• an exploitative practice.

The EU's Digital Markets Act already provides an important illustration of this regulatory direction: Article 6(8) requires designated gatekeepers, on request, to provide advertisers and publishers with access to performance-measuring tools and relevant aggregated and non-aggregated data needed for independent verification of advertising inventory.

6. The Problem of Measurement Neutrality

A central future competition concern will be neutrality.

Consider a platform that:

1. sells advertising;
2. operates an advertising exchange;
3. supplies attribution technology; and
4. determines which advertisements receive the highest "influence" score.

It may have incentives to design measurement methodologies favourable to its own products.

This resembles the conflict-of-interest concerns already examined in digital advertising.

In the EU's Google adtech proceedings, the Commission examined conduct involving Google's presence at multiple levels of the advertising technology chain and alleged preferential treatment of its own services. The Commission ultimately adopted a decision in September 2025 concerning Google's advertising-technology practices.

The same analytical principle could eventually extend to influence measurement.

7. Self-Preferencing in Influence Measurement

A platform could theoretically provide:

Platform A — Influence Score: 92
Independent Creator B — Influence Score: 67

The competition problem would arise if Platform A controlled:

• the underlying data;
• the methodology;
• the ranking algorithm; and
• the commercial marketplace in which the scores are used.

The measurement system could then become a mechanism for reinforcing the platform's own market position.

Potential theories of harm include:

• self-preferencing;
• discriminatory measurement;
• exclusion of competing measurement providers;
• manipulation of benchmarks;
• preferential API access;
• discriminatory attribution;
• foreclosure of independent analytics firms.

8. Interoperability and Measurement Portability

Future competition policy may increasingly demand measurement portability.

Advertisers and creators should potentially be able to move relevant performance information between measurement providers.

Without portability, customers may become locked into one ecosystem.

For example:

Platform A → proprietary influence score → advertiser dependence → inability to compare Platform B

This produces a feedback loop:

More users → more data → better measurement → greater advertiser reliance → more users

Consequently, influence measurement can exhibit strong data-driven network effects.

9. Six Major Case Laws / Enforcement Precedents

Case 1 — FTC: VNU N.V. / Nielsen Media Research (1999–2000)

This is one of the most directly relevant precedents.

The FTC examined VNU's proposed acquisition of Nielsen Media Research in the market for advertising expenditure measurement services.

The FTC identified only two major suppliers in the relevant U.S. market and concluded that the transaction threatened to eliminate competition. The proposed remedy required divestiture of VNU's Competitive Media Reporting division.

Principle

Competition law can recognise measurement services themselves as a relevant antitrust market.

Future relevance

The same approach can apply to:

• influencer measurement;
• attribution;
• engagement measurement;
• brand-effect measurement; and
• AI-generated influence scores.

Case 2 — FTC: Nielsen Holdings / Arbitron (2013–2014)

The FTC challenged Nielsen's acquisition of Arbitron because both firms were developing national syndicated cross-platform audience measurement services.

The FTC was concerned that eliminating Arbitron's competitive development path could reduce future competition and increase market power. The final remedy required divestiture and licensing of relevant assets.

The FTC's analysis was particularly significant because the relevant competitive harm concerned future innovation, rather than merely existing sales.

Principle

Competition law can protect nascent or emerging measurement competition.

Future relevance

A merger between:

• an established influence-measurement provider; and
• an emerging AI attribution provider

could therefore receive scrutiny even if the second firm has comparatively modest current revenue.

Case 3 — FTC: Nielsen / Arbitron – LinkMeter Divestiture

The subsequent approval of the sale of LinkMeter-related cross-platform measurement assets to comScore illustrates the importance of maintaining an independent measurement capability.

The FTC required divestiture arrangements intended to preserve competitive development of cross-platform audience measurement.

Principle

Measurement technology and associated data can constitute strategically important competitive assets.

Future relevance

In future transactions, authorities may consider:

• proprietary measurement algorithms;
• identity graphs;
• historical influence datasets;
• APIs;
• measurement panels;
• calibration technology; and
• benchmarking databases

as assets requiring preservation or divestiture.

Case 4 — European Commission: Google Search (Google Shopping)

The Google Shopping decision established an important precedent concerning the treatment of a platform's own services within search and ranking infrastructure.

Although not an influence-measurement case, it is relevant because measurement markets may also involve ranking and visibility mechanisms.

The broader principle is that a platform occupying an important intermediation position may face competition-law scrutiny when its control over infrastructure is used to advantage its own downstream service.

Future relevance

An influence platform could potentially favour its own:

• creators;
• advertising products;
• content;
• analytics;
• measurement tools; or
• commercial partners.

Case 5 — European Commission: Google Adtech

The European Commission's Google adtech proceedings provide a particularly important modern precedent.

The Commission's investigation examined Google's presence across multiple levels of the online advertising technology supply chain and concerns about preferential treatment of Google's own advertising services. The Commission ultimately adopted a 2025 decision finding an infringement in Google's adtech conduct and imposed a €2.95 billion fine.

Principle

Vertical integration across interconnected digital advertising layers can create competition concerns where the undertaking controls important infrastructure.

Future relevance

An influence-measurement platform operating simultaneously as:

measurement provider + advertising intermediary + data provider + marketplace

could raise analogous concerns.

Case 6 — United States v. Google — Digital Advertising Technology

In 2025, the U.S. District Court for the Eastern District of Virginia found Google liable for monopolization in important open-web digital advertising technology markets. The litigation concerned Google's conduct across the ad-tech stack.

In September 2026, the DOJ announced substantial remedial measures, including data-access and interoperability requirements involving competing technologies and restrictions concerning preferential bidding.

Principle

Competition remedies can extend beyond fines to:

• interoperability;
• data access;
• integration with rivals;
• non-discrimination;
• monitoring; and
• structural or behavioural obligations.

Future relevance

These remedies provide a possible model for future oversight of dominant influence-measurement infrastructure.

10. Additional Precedent: CMA Google Adtech Investigation

The UK's CMA has investigated Google's conduct across portions of the adtech stack. In 2024, it issued a statement of objections alleging that Google used its position in online display advertising to favour its own adtech services; the investigation remained ongoing as of the CMA's May 2026 update, so those allegations should not be treated as a final infringement finding.

This is relevant to influence measurement because measurement can become another layer within the same vertically integrated ecosystem.

11. New Forms of Anticompetitive Conduct

Future influence-measurement markets could generate several distinctive theories of harm.

1. Measurement foreclosure

A dominant platform prevents rival measurement companies from obtaining necessary data.

2. Measurement discrimination

The platform supplies higher-quality data to affiliated measurement services.

3. Self-preferencing

Its own influence scores receive greater visibility or credibility.

4. Attribution manipulation

The platform systematically assigns conversions to its own advertising inventory.

5. Benchmark manipulation

A dominant measurement provider changes industry benchmarks in ways that disadvantage competitors.

6. Data tying

Advertisers must purchase measurement services together with advertising inventory.

7. API foreclosure

Independent measurement providers receive restricted or delayed API access.

8. Algorithmic exclusion

Competitors are excluded from measurement ecosystems through technical design.

12. Influence Scores as Competitive Infrastructure

A particularly important future development is the emergence of standardised influence scores.

For example:

Influence Score = reach + engagement + conversion + retention + behavioural effect

If advertisers begin treating that score as a market standard, the score itself may become commercially indispensable.

A dominant measurement provider could therefore become a private standard setter.

This raises competition-law questions concerning:

• access;
• transparency;
• certification;
• methodology;
• interoperability;
• auditability;
• discrimination;
• conflicts of interest; and
• manipulation.

13. Algorithmic Measurement and AI

AI will make influence measurement considerably more sophisticated.

Systems may attempt to measure:

• emotional response;
• purchasing propensity;
• attention duration;
• persuasion;
• consumer sentiment;
• recommendation impact;
• brand association;
• creator authenticity;
• behavioural change; and
• causal influence.

However, AI-generated scores create a fundamental competition issue:

Correlation is not necessarily causation.

If a platform claims:

"Creator X caused 20% of purchases"

the underlying calculation may depend on proprietary algorithms that competitors cannot inspect.

Competition authorities may therefore need to distinguish:

Observed engagement

from

causal influence.

14. Measurement Accuracy as a Competition Variable

The quality of measurement itself can become a competitive parameter.

Important variables include:

• accuracy;
• error rates;
• sampling methodology;
• data freshness;
• cross-platform coverage;
• identity resolution;
• attribution windows;
• fraud detection;
• bot detection;
• methodology transparency;
• independent verification.

The VNU/Nielsen proceeding is especially instructive because the FTC identified reputation for accuracy and historical data as barriers to entry.

Therefore, a dominant measurement provider could potentially benefit from a reputational moat that is difficult for new entrants to overcome.

15. Network Effects

Influence measurement can produce several reinforcing network effects.

Direct network effect

More users generate more behavioural data.

Data network effect

More data improves the measurement model.

Commercial network effect

More advertisers use the measurement standard.

Benchmarking network effect

More users make the benchmark more authoritative.

Reputation network effect

More industry adoption increases trust in the measurement score.

This can create:

Data → better measurement → greater adoption → more data

Such feedback loops may create durable market power.

16. Merger-Control Issues

Competition authorities should potentially examine mergers involving:

• influencer analytics firms;
• attribution providers;
• advertising platforms;
• social networks;
• consumer-data companies;
• identity-resolution firms;
• measurement standards organisations;
• AI analytics companies.

Traditional turnover thresholds may not capture the competitive importance of a small but strategically important measurement company.

The Nielsen/Arbitron matter demonstrates why authorities may need to consider future competition and innovation rather than merely current market shares.

17. Possible Remedies

A. Data-access remedies

Dominant platforms could be required to provide relevant data to independent measurement providers.

B. API interoperability

Measurement APIs could be made accessible on fair and non-discriminatory terms.

C. Independent auditing

Measurement methodologies could be subjected to independent verification.

D. Data portability

Advertisers could transfer measurement information between providers.

E. Non-discrimination

A platform could be prohibited from providing superior measurement access to affiliated businesses.

F. Structural separation

In particularly serious cases, measurement operations could potentially be separated from advertising operations.

G. Divestiture

The VNU/Nielsen and Nielsen/Arbitron precedents demonstrate that divestiture can be used where concentration threatens measurement competition.

18. Future Regulatory Model

A future framework could establish five principal obligations.

1. Measurement transparency

Providers should disclose sufficient information concerning methodology and material limitations.

2. Measurement portability

Customers should be able to move relevant measurement data.

3. Interoperability

Independent measurement providers should have reasonable technical access.

4. Independent verification

Important market-wide metrics should be capable of external auditing.

5. Conflict-of-interest controls

A company should not be able to manipulate a measurement system to favour its own downstream commercial interests.

19. Competition Law and the Problem of "Influence Monopolies"

The most significant future concern may not be a conventional monopoly over advertising.

It may be a monopoly over knowledge about advertising effectiveness.

Imagine a market in which one undertaking controls:

user data + attribution + influence scoring + campaign verification + industry benchmark.

Such an undertaking could potentially influence how advertisers, creators and publishers understand competitive performance.

That creates a form of informational market power.

The competition concern is therefore not merely:

"Who controls the customers?"

It may increasingly become:

"Who controls the information by which customers decide among competing products?"

20. Future Oversight Model

Competition authorities could develop an Influence Measurement Market Assessment Framework (IMMAF) based on the following questions:

21. Relationship With Digital Competition Regulation

Influence measurement increasingly intersects with digital-platform regulation.

The CMA's digital advertising work already treats measurement, attribution and effectiveness as important components of competitive functioning.

The EU's DMA approach is even more explicit in requiring access to advertising performance-measurement tools and data for independent verification.

This suggests a movement away from a purely ex-post antitrust model toward a combination of:

competition law + interoperability + data access + transparency + ex-ante digital regulation.

22. Key Legal Principles Emerging From the Case Law

The six principal precedents collectively support several propositions:

Principle 1

Measurement services can themselves constitute an antitrust market.

VNU/Nielsen.

Principle 2

Competition authorities may protect emerging measurement competition.

Nielsen/Arbitron.

Principle 3

Measurement data and technology can constitute critical competitive assets.

Nielsen/Arbitron and LinkMeter divestiture.

Principle 4

Vertical integration can create conflicts where an undertaking controls several layers of digital advertising infrastructure.

Google adtech proceedings.

Principle 5

Competition remedies may require interoperability and data access.

U.S. Google adtech proceedings.

Principle 6

Digital measurement systems require attention to verification and attribution, not merely price.

CMA digital advertising market study.

23. Challenges for Competition Authorities

Future enforcement will face significant difficulties.

A. Causation

It may be difficult to prove that a measurement score actually caused competitive harm.

B. Dynamic markets

Influence technologies change rapidly.

C. Multi-sided markets

The same platform may serve advertisers, publishers, creators and consumers.

D. Data privacy

Competition remedies involving data access must coexist with privacy law.

E. Algorithmic opacity

Authorities may not easily reproduce proprietary AI measurement systems.

F. Measurement disagreement

Different methodologies may produce legitimate but different results.

G. Global markets

Influence measurement frequently crosses national borders.

24. Conclusion

Influence Measurement Markets represent a significant future frontier for competition law.

The historical cases involving VNU/Nielsen and Nielsen/Arbitron demonstrate that competition authorities have long recognised the strategic importance of specialised measurement markets.

Modern digital-advertising proceedings involving Google demonstrate the additional importance of:

• vertically integrated data ecosystems;
• interoperability;
• non-discriminatory access;
• data portability;
• independent verification; and
• conflicts of interest in digital intermediation. 

The future challenge is likely to move beyond conventional questions of who sells advertising toward the more fundamental question of who measures, attributes and validates influence.

If a single undertaking controls the data, algorithms, attribution system, benchmark and certification mechanism, its influence may extend beyond ordinary market power into the infrastructure through which competition itself is measured.