Regulation & Policy
Digital Markets Act
Also known as: DMA, EU Digital Markets Act
The Digital Markets Act (DMA) is an EU regulation that sets conduct rules for very large online platforms designated as gatekeepers, such as major search engines, app stores, marketplaces, browsers and social networks. It bans practices like self preferencing in ranking and restricts how gatekeepers combine personal data across their services without consent. For marketers it changes how results, choice screens and tracking work for EU users.
What it is
The DMA is a competition style regulation rather than a privacy law. It applies to firms designated by the European Commission as gatekeepers of core platform services, and it lists obligations they must meet and practices they must stop. Enforcement sits with the Commission, which can investigate non compliance and impose fines based on worldwide turnover.
Why it matters
Gatekeeper platforms are where most discovery happens, so rules about ranking, defaults and data consent feed straight into organic visibility, paid performance and measurement. Result layouts in the EU have changed as gatekeepers adjust to obligations, which affects click distribution between platform owned units, aggregators and brand sites. Consent requirements also shape how much cross service data is available for targeting and attribution.
How it works
Gatekeepers publish compliance changes and reports, and the Commission opens investigations where it suspects obligations are not met. In practice teams track EU specific search result changes, test whether comparison and aggregator listings gain or lose ground, review consent flows for ad and analytics data, and watch for choice screens that reset browser or search defaults. Many organisations run separate EU reporting views so policy driven shifts are not mistaken for seasonality or algorithm updates.
When it applies
It applies when your audience, customers or traffic sits in the EU and your discovery depends on designated gatekeeper services. It is most relevant during compliance deadlines, platform feature changes and consent policy updates.
Examples
- A travel brand sees more comparison site links and fewer platform owned booking units in EU search results, and rebuilds its forecast for non brand clicks.
- An app publisher offers an alternative download route in the EU after distribution rules change, and adds tracking for that channel.
- A retailer updates consent flows so ad platform data sharing only happens with permission, then rebuilds EU conversion reporting on modelled data.
How it is measured
- EU versus non EU organic clicks and impressions for affected query sets
- Share of result page space held by platform owned units against third party listings
- Consent rate for ad and analytics data among EU visitors
- Share of default search or browser choices retained after choice screen exposure
Related terms in Regulation & Policy
- AI complianceAI compliance is the work of making sure AI systems meet the laws, regulations, standards and internal policies that apply to them. It spans data protection, transparency, risk classification, documentation, human oversight and record keeping across the life of a system. In practice it combines legal interpretation, engineering controls and ongoing evidence gathering.
- AI governanceAI governance is the set of policies, roles, controls and review processes an organisation uses to manage how AI systems are built, bought and used. It covers risk assessment, documentation, human oversight, data handling and accountability. It applies both to AI a company develops and to third-party AI tools used by staff.
- AI privacyAI privacy is the set of practices, rights and obligations that govern how personal data is collected, used, stored and exposed when building or using AI systems. It covers training data, prompts and outputs, retention by AI vendors, and the transparency and control offered to the people whose data is involved. For marketing teams it shapes what customer data can safely be put into AI tools and what must be disclosed.
- AI safetyAI safety is the practice of designing, testing and operating AI systems so they cause less harm, behave predictably and resist misuse. It covers alignment with intended behaviour, evaluation and red teaming, content guardrails, and monitoring once a system is live. For marketers it shapes what models will say, how assistants handle brands, and what compliance teams expect before AI tools go into production.
- AI transparencyAI transparency is the practice of making clear how an AI system works, what sits behind it, and when content or an interaction involves AI. It covers regulatory disclosure duties as well as voluntary explanations such as model cards, labels on synthetic media and citations in AI generated answers. For publishers and marketers it sets expectations about when AI involvement should be declared and how clearly.
- Competition and Markets AuthorityThe Competition and Markets Authority (CMA) is the United Kingdom's competition and consumer protection regulator. It investigates mergers, anti-competitive conduct and market practices, and it holds specific powers over large digital firms under the Digital Markets, Competition and Consumers Act 2024. Its decisions shape how search engines, app stores and AI assistants operate in the UK market.
Primary research · August 2026
How ChatGPT Shortlists Software Brands
An audit across 10 categories and 60 buying questions. I recorded what ChatGPT reads, throws away and links to when a buyer asks it which software to buy, and what that decides.
- 60
- Questions asked
- 10
- Software markets
- 2,680
- Results read
- 367
- Links shown
Free download
Get the full report
35 pages · PDF · 536 KB. Enter your details and it downloads straight away.