 is a technology platform where digital advertising inventory is automatically bought and sold between advertisers and publishers.


Like a stock exchange, advertising inventory is often traded through auctions. In an open auction, the highest bid usually wins, but not every ad impression automatically enters that auction. 

Programmatic guaranteed deals are sold directly in advance, while preferred deals receive priority before the open auction takes place.

 Only then do the remaining bids compete.

In addition, factors such as the publisher's floor price, the relevance of the advertisement, campaign quality and brand safety determine which advertisement is ultimately displayed.

 enable publishers to make their advertising inventory available through one or more ad exchanges. 

 enable advertisers and media agencies to automatically purchase advertising inventory through one or more ad exchanges. Together, 

Ad exchange

 is a form of television advertising in which different households are shown different commercials during the same television programme. This enables advertisers to tailor advertisements to specific audience segments based on factors such as demographics, interests, location and viewing behaviour.

Addressable TV uses digital distribution technology, audience segmentation and automated media buying. This allows advertisers to target television campaigns much more precisely than with traditional linear television, where all viewers see the same commercial.

, this means that the advertisements they see are more relevant to their interests. For example, a household with an interest in golf may be shown an advertisement for a golf holiday in Portugal, while another household watching the same commercial break sees a completely different advertisement.

, Addressable TV offers the opportunity to reach audiences more precisely, measure campaign performance more effectively and deliver different messages to different audience segments. It combines the broad reach of television with many of the targeting and measurement capabilities of digital advertising channels.

Addressable TV

 is artificial intelligence that can independently carry out an entire task or workflow from start to finish, rather than simply responding to a single prompt. It plans, makes decisions, and takes action with minimal human intervention. Think of software that doesn't just provide one answer, but keeps working until the assigned goal has been achieved.


A chatbot answers a question and then stops. Agentic AI, by contrast, remains active until the objective has been completed. It repeats steps when necessary, adapts its approach as new information becomes available, and carries out follow-up actions on its own, without requiring a person to approve every step.



Applications in marketing and media monitoring


Imagine an AI agent that takes over the entire media monitoring process. It detects brand mentions, assesses whether a response is needed, drafts a reply, and prepares it for publication. Another example is an AI that continuously allocates and optimizes advertising budgets across Google Ads and social media platforms based on real-time campaign performance. Similar AI agents are increasingly being used in customer service and content planning, where they manage entire workflows from detection to execution.

Imagine a brand facing a wave of negative media coverage following a product recall. A traditional AI tool would identify the relevant articles and stop there. An agentic AI system goes much further: it evaluates the tone and potential impact of each mention, drafts an appropriate response based on predefined guidelines, schedules it for publication, and automatically escalates the issue to a human whenever the situation falls outside the established parameters.

 a fundamental shift: from AI as a tool that assists with individual tasks to AI that autonomously executes and optimizes entire marketing workflows. 

According to a Gartner market forecast published in January 2026, by 2028, 60% of brands are expected to use agentic AI for personalized one-to-one interactions, up from virtually none in 2024. As with any forecast, this is a projection rather than a certainty, but it illustrates how rapidly the technology is gaining momentum.

Agentic AI 

 is a flexible marketing approach in which cross-functional teams work in short, iterative cycles to develop, test, evaluate and continuously improve marketing activities. By continuously measuring results and adapting their approach, organisations can respond more quickly to changing market conditions, customer needs and new insights.

Agile marketing is based on the principles of 

 software development and often uses frameworks such as 

. Teams work from a prioritised backlog and regularly deliver new campaigns, content or other marketing initiatives through short sprints or a continuous workflow.

A key principle of agile marketing is the rapid validation of ideas. Rather than spending months developing a campaign, concepts are tested as early as possible. Based on data, customer feedback and measurable results, campaigns are then refined and further optimised. This continuous cycle of testing, learning and improving is known as 

Many agile marketing teams hold short daily stand-up meetings to review progress, resolve obstacles quickly and coordinate their work. Progress is typically tracked using a digital Kanban board or a similar project management tool.

Collaboration, transparency, flexibility and a strong focus on customer value are at the core of agile marketing. By experimenting quickly and continuously optimising their activities, organisations can respond more effectively to change and deliver value faster than with traditional, long-running marketing projects.

Agile marketing

 is the collective term for technologies that enable computers to perform tasks that normally require human intelligence. These include analysing data, recognising patterns, understanding language, making predictions, generating content and supporting or automating decision-making.

 techniques. Rather than following only explicitly programmed instructions, they improve their performance by identifying patterns in large datasets. 

, a specialised branch of machine learning based on artificial neural networks, has enabled major advances in areas such as computer vision, speech recognition and natural language processing.

The term 

 during the Dartmouth Conference in the United States by computer scientist 

. Researchers believed that human intelligence could be simulated by machines, although practical progress proved far more difficult than initially expected.


Expert systems and the first practical machine learning techniques emerged.


The rapid growth of the internet and digitalisation generated enormous amounts of data, creating the foundation for modern AI.


Breakthroughs in deep learning, combined with powerful GPUs, enabled major advances in image recognition, speech recognition and language processing.


Large Language Models (LLMs), such as GPT, Claude and Gemini, together with generative AI, have made advanced AI capabilities widely accessible to businesses and consumers.


AI takes different forms, depending on the purpose for which it is used. Some applications are predictive, others advisory or creative, and yet others take fully autonomous decisions.


Netflix continuously analyses the viewing behaviour of millions of users to provide increasingly accurate and personalised recommendations.


Self-driving vehicles analyse information from cameras, sensors and radar systems in real time. AI recognises traffic situations, predicts the behaviour of other road users and supports or performs driving decisions such as braking, steering and lane changes.

AI in Media: Opportunities and Challenges

Artificial intelligence is transforming the media industry.

 It supports journalists, publishers, broadcasters and advertisers by helping to create content, personalise user experiences, optimise advertising campaigns, analyse audiences, automate translations and subtitles, and improve media planning.

At the same time, AI raises important questions about transparency, copyright, bias, misinformation and editorial responsibility. 

As AI becomes more deeply integrated into media workflows, maintaining human oversight and public trust remains essential.

AI (Artificial Intelligence)

 is a standardized interface that enables software applications to communicate with each other securely. Through an API, an application can request data, exchange information or use the functionality of another application without requiring access to its underlying source code.

APIs make it easy to integrate existing services into websites, apps and other software systems. This allows developers to build new applications without having to develop every feature from scratch.


An API consists of a set of rules and protocols that define how applications communicate with one another. It specifies which data or functions are available, how requests should be made and in which format the information is returned.

 format, although some systems also support 

 architecture, while technologies such as 


Virtually all major technology companies and many SaaS providers offer APIs. Examples include 

These APIs enable developers to integrate maps, process payments, synchronise documents or add AI functionality to their own applications.

 are intended exclusively for internal use within an organisation.

 are made available to selected business partners.

 are openly available to external developers, often subject to specific terms of use.


Suppose you are developing a weather app and want to display real-time weather information.

Without an API, you would have to extract data directly from a website using 

. This approach is fragile because changes to the website can cause your application to stop working correctly.

With an API, you send a structured request to the weather data provider. If the request complies with the API's specifications, the requested information is returned in a standardised format. This keeps the integration stable, even if the provider changes the design of its website.


APIs are the foundation of modern software development. They enable data and functionality to be exchanged securely, efficiently and at scale between systems. This allows organisations to focus on their core expertise while taking advantage of specialised services provided by other organisations.

Cloud applications, mobile apps, e-commerce platforms, payment services, social media and AI solutions such as ChatGPT all rely heavily on APIs to exchange information and functionality.

 is a video streaming business model that gives users free access to video content. Instead of paying for a subscription, viewers watch advertisements that finance the service.

, where users pay for individual films or programmes, and 

, where broadcasters make their own content available on demand.


YouTube is one of the best-known AVOD platforms in the Netherlands. Other leading ad-supported streaming services on the Dutch market include 

The popularity of AVOD continues to grow because consumers can access video content free of charge, while providers generate revenue through advertising. At the same time, an increasing number of streaming services are adopting hybrid business models, allowing users to choose between a lower-priced ad-supported subscription and a more expensive ad-free subscription.

AVOD (Advertising video on demand)

A blockchain is essentially a chronological list of data records to which information can only be added. The technology became widely known through Bitcoin, where a blockchain is used to record bitcoin transactions. On average, a new block containing several thousand transactions and a reference to the previous block is added every ten minutes. This creates a chain of blocks: the blockchain.

Bitcoin is a decentralized monetary system, meaning that its ledger is maintained and verified by a large group of participants without any central authority. This is the essence of the invention: a large group of unrelated participants can reach consensus on the system's ledger.

A blockchain is essential because it establishes the order of transactions. A large group of unrelated participants does not share a common sense of time. Because each block is linked to the previous one, a chronological sequence is created. The downside is that outside a truly decentralized system, a blockchain adds little value and is often an inefficient way to store data.

One of the key challenges is determining who is allowed to add the next block to the blockchain. Ideally, this is a different participant chosen at random each time. This is solved through a consensus mechanism: the method by which agreement is reached. One characteristic of a robust consensus mechanism is that participants cannot pretend to be multiple people and thereby cast multiple votes when establishing the ledger.

. Under this mechanism, participants ('miners') receive voting power in proportion to the computing power they contribute. Because computing power requires energy, no one can fake their influence. Other consensus mechanisms also exist, such as 

. In this model, participants ('validators') receive voting power in proportion to the amount of cryptocurrency they lock up. Bitcoin uses Proof-of-Work, while Ethereum has used Proof-of-Stake since 2022. In a public decentralized system such as Bitcoin or Ethereum, anyone can join the network, maintain a complete copy of the blockchain and independently verify that all the rules are being followed. They do not need to rely on a central authority such as a government, bank or technology company.

Today, blockchain technology is used not only for cryptocurrencies but also for applications such as asset tokenization, digital identity, supply chain management and recording ownership rights.

Blockchain

allow viewers to watch television broadcasters' programmes on demand. This may include previously broadcast programmes, live streams or exclusive online content. The services are typically free to access with advertising, although some platforms also offer paid premium subscriptions.

By making locally produced content available whenever viewers choose, BVOD bridges the gap between traditional linear television and today's flexible viewing habits.

In a market where international streaming services such as Netflix, Disney+ and Prime Video continue to gain market share, BVOD provides broadcasters with an important competitive advantage. It enables them to maintain a direct relationship with their audiences while generating advertising revenue through their own streaming platforms.

Examples of BVOD platforms in the Netherlands

BVOD (Broadcast Video on Demand)

is a software platform that collects, combines, and manages customer data from multiple sources to create a single, unified, and up-to-date customer profile. It enables organizations to bring together first-party data from websites, apps, CRM systems, email marketing, customer service, purchases, and other sources in one central environment.

A CDP links data belonging to the same individual across different systems and enriches it to create a comprehensive customer profile. This provides an up-to-date view of customer characteristics, interests, behavior, and interactions across multiple channels. These profiles can then be used for audience segmentation, personalization, analytics, and marketing campaigns.

CDPs are used for audience segmentation, personalized communication, marketing automation, omnichannel campaigns, audience activation, customer analytics, and reporting. They help organizations deliver more relevant customer interactions and improve the effectiveness of marketing campaigns.

A CRM primarily focuses on managing customer relationships and sales processes. A CDP goes a step further by collecting and combining behavioral data from digital channels, creating a more complete and dynamic customer view that can be directly used for marketing and personalization.

For advertisers, a CDP is a key source of first-party data for audience segmentation, personalization, and audience activation. Publishers use CDPs to better understand their audiences, build audience segments, and deliver more relevant content and advertising. As a result, CDPs play an important role in privacy-friendly marketing strategies, helping organizations become less dependent on third-party cookies.

CDP (Customer Data Platform)

 is a pricing model for (online) advertising in which costs are calculated per 

Cost of the advertising campaign
──────────────── = CPM
Number of impressions ÷ 1,000

CPM = (Total cost ÷ Number of impressions) × 1,000

 is a recorded display of an advertisement. This does not necessarily mean that the advertisement was actually visible to the user.

For this reason, digital advertising distinguishes between 

According to the international guidelines of the 

These guidelines are the international standard for measuring ad viewability.

CPM is one of the most widely used pricing models for digital display, video and social media advertising campaigns. Advertisers pay for the number of delivered impressions, while publishers are responsible for delivering the agreed number of ad impressions.

In addition to traditional CPM, campaigns are increasingly evaluated using additional quality metrics, such as:

 (the actual attention paid to advertisements)

As a result, advertisers evaluate campaigns not only by the number of impressions delivered, but also by the quality of the audience reached.

 is an important quality metric, not every campaign is traded or billed solely on the basis of 

. The measurement methods and KPIs used vary by publisher, advertising platform and campaign.

In practice, advertisers and publishers therefore agree on the desired level of 

 in advance, ensuring that both parties understand the quality standards the campaign is expected to achieve.

Crypto is originally an abbreviation for crypto currencies, the currencies of decentralised money systems such as Bitcoin and Ethereum. In this context, crypto refers to the cryptography used in transferring such a currency. By adding a digital signature, the owner proves that he or she may transfer the digital asset to another person.

Nowadays, crypto is an informal umbrella term for all crypto-assets. These are digital assets that are not managed by a central party such as a tech company, bank or government, but whose ownership is noted in decentralised records and can be transferred peer-to-peer. As such, the term crypto identifies a new asset class.

New financial markets have emerged around these new assets, with thousands of companies forming a vibrant sector worldwide. The word crypto is also used to refer to this activity as a whole. Thus, people are employed 'in crypto', and governments worldwide are working to create 'crypto laws' that apply to the entire industry.

It is important to realise that crypto as an asset class contains a wide variety of assets. It started with bitcoin as independent digital money. Then new assets appeared, trying to apply what Bitcoin does for money to other kinds of digital assets. Think identity data, access cards, art. Or proof of ownership of a loan, or that you are part of a decentralised organisation.

A common mistake is to equate crypto with a specific asset or application within the category. One then gives the impression of absolute homogeneity, when the opposite is true. For instance, Bitcoin as the first and most decentralised currency is incomparable to the properties of a digital art object or a stablecoin issued by a central party.

Crypto

 describes every interaction and experience a (potential) customer has with a brand, product or service. It begins when someone first becomes aware of a brand and continues through the purchase, product usage, customer loyalty and, ultimately, recommendations to others.

The customer journey helps organisations understand how customers research, make decisions and build relationships with a brand. This insight enables marketing and communication activities to be better aligned with customer needs at every stage of the journey.

Although the exact framework may vary, the customer journey typically consists of the following stages:

 – The potential customer becomes aware of a brand, product or service.

 – The customer gathers information, compares alternatives and evaluates which solution best meets their needs.

 – The customer decides to choose a particular brand, product or service.

 – After the purchase, the brand focuses on customer satisfaction, repeat purchases and building a long-term customer relationship through initiatives such as customer service, after-sales support, loyalty programmes and personalised communication.

 – Satisfied customers actively recommend the brand through word of mouth, online reviews or social media, becoming ambassadors for the brand.

The customer journey builds on the classic 

), but extends beyond the purchase itself. While AIDA primarily focuses on persuading a potential customer to make a purchase, the customer journey also includes the post-purchase stages, such as product usage, customer satisfaction, loyalty and advocacy.

The Customer Journey in Media and Marketing


Advertisers, marketers and media planners tailor their communication strategies and media choices to the different stages of the customer journey. Campaigns focused on 

 are designed to build brand recognition, while campaigns in the 

 stages aim to inform, persuade and drive conversions. After the purchase, the focus shifts to customer retention, loyalty and encouraging positive recommendations.

By delivering the right message through the right channel at the right time, organisations can enhance the customer experience, increase conversion rates and build long-lasting customer relationships.

Customer Journey

 is a secure environment in which two or more organisations can compare, analyse or combine data without exchanging each other's underlying personal data or raw datasets. The participating organisations retain control over their own data, while only pre-agreed analyses or aggregated results are made available.


Each organisation contributes its own first-party data to the data clean room. Within the secure environment, datasets can be matched or analysed according to predefined rules. Personal data remains protected and cannot leave the environment. The outputs typically consist of aggregated insights, audience segments or measurement results, without allowing individual people to be identified.


Data clean rooms are used for audience analysis, campaign planning, advertising measurement, attribution, reach analysis and data partnerships between advertisers, publishers, retailers and media platforms. They play an important role in retail media, programmatic advertising and the secure use and sharing of first-party data.


A retailer and a manufacturer want to determine which customers saw an advertising campaign and subsequently purchased a product. Both organisations upload their own first-party data into a data clean room. Within the secure environment, the datasets are analysed and only aggregated results are shared, such as the number of buyers reached and the effectiveness of the campaign. Neither organisation gains access to the other party's underlying personal data.

Data clean rooms are becoming increasingly important 

as organisations rely more heavily on first-party data, third-party cookies become less available and privacy legislation imposes stricter requirements on the sharing and processing of personal data. They enable secure data collaboration while allowing organisations to retain control over their own data.

Data Clean Room

 is a software platform that enables organisations to collect, organise, analyse and activate large volumes of primarily anonymised audience data for digital marketing and advertising purposes.

DMPs are primarily used to segment audiences and make digital advertising campaigns more efficient and relevant. They combine data from multiple sources, enabling advertisers to reach audiences across multiple advertising platforms.


A DMP collects data from a wide range of sources, including websites, mobile apps, advertising platforms and external data providers. This may include first-party, second-party and—where regulations and technology still permit—third-party data.


The collected data is organised into audience segments based on characteristics such as interests, online behaviour, demographic attributes and contextual information.


The DMP analyses these segments, helping marketers gain valuable insights into the behaviour, interests and preferences of different audiences.


The audience segments can then be used for 

, audience targeting, retargeting and campaign optimisation across advertising platforms.

The role of DMPs has evolved significantly in recent years due to stricter privacy legislation, such as the 

General Data Protection Regulation (GDPR)

, and the declining availability of third-party cookies. Browsers such as Safari and Firefox block third-party cookies by default, while Chrome allows users to disable them through their privacy settings. As a result, organisations are increasingly relying on first-party data and privacy-friendly identification methods.

Organisations using a DMP remain responsible for the lawful processing of personal data and must comply with applicable privacy legislation.

Although the terms are often used interchangeably, a 

anonymised audience segmentation for digital advertising

 and typically works with temporary or pseudonymous profiles.

 and supports a broader range of marketing activities, including personalisation, marketing automation and customer relationship management (CRM).

As the availability of third-party cookies continues to decline, more organisations are adopting a CDP as their central customer data platform, while DMPs continue to play an important role in 

DMP (data-management platform) 

 is a software platform that enables advertisers and media agencies to automatically purchase digital advertising inventory through one or more ad exchanges and other programmatic marketplaces.


Within a DSP, users can configure bidding strategies, audience targeting, budgets, frequency caps and other campaign settings to optimize media buying. Based on these settings, the DSP automatically places bids on available ad impressions.

DSP (demand-side platform)

 is the media attention you do not pay for but earn because people voluntarily talk about your brand, share your content, recommend your products or services, or mention you in news coverage, reviews or online discussions.

Customers, journalists, creators and other third parties become the media in this case.

lies in its credibility. Because the message comes from independent sources rather than the brand itself, it often has a strong influence on consumers during the buying process.

include positive customer reviews, editorial news coverage, social media shares, podcast mentions, blog articles, online discussions, and content that goes viral. Earned media is often the result of a successful combination of owned and paid media.

is that you have little direct control over it. It can be both positive and negative, is difficult to predict, cannot be scaled as easily as paid media, and its impact can be challenging to measure accurately.

Earned media

First-party data is information that an organization collects directly about its own customers, visitors, or users through its own channels. This data is generated through direct interactions, such as website visits, app usage, purchases, newsletter sign-ups, or customer service interactions.

Common sources include website and app analytics, CRM systems, transaction data, loyalty programs, surveys, and customer interactions via email or customer service. Because organizations collect this data themselves, it is generally more up to date, reliable, and relevant than data obtained from external parties.

Difference between second-party and third-party data


Second-party data is another organization's first-party data, shared through a direct partnership. Third-party data is collected by organizations that have no direct relationship with the end user and is then made available through data brokers or data marketplaces.

Why first-party data is becoming increasingly important


As privacy regulations such as the General Data Protection Regulation (GDPR) become stricter, and third-party cookies become less widely available—Safari and Firefox already block them by default, while Chrome users can disable them themselves—organizations are investing more heavily in first-party data strategies. These include loyalty programs, personalized content, and other ways of building direct customer relationships.

A publisher asks visitors to register free of charge to gain access to exclusive content. In doing so, the publisher collects first-party data, such as the user's email address, reading behavior, and interests. This data can then be used to personalize content, make newsletters more relevant, or create anonymized audience segments for advertisers without relying on third-party cookies.

First-party data

 is a business model for delivering over-the-top (OTT) content that gives users free access to video-on-demand content. Depending on the platform, the service may be funded through advertising, public funding or other revenue sources. FVOD is often used to reach a broad audience or as part of a broader VOD strategy.

A well-known example of FVOD in the Netherlands is 

. The platform allows viewers to watch a wide range of TV programmes on demand free of charge. The free service includes advertising. Users who want an ad-free viewing experience and access to additional features can upgrade to 

FVOD (Free Video on Demand)

 is the application of game elements and game design principles in a non-game environment to increase user engagement with a product, service or brand. Its purpose is to encourage motivation, engagement and desired behaviour by creating an engaging and interactive user experience.

Gamification uses elements such as progress tracking, challenges, points, badges, levels, rewards and social interaction to motivate users to achieve goals and return to a platform or service. When implemented effectively, gamification can increase user engagement, strengthen customer loyalty and create a more positive user experience.

However, gamification can also have drawbacks. When game mechanics are primarily designed to maximise screen time, encourage excessive competition or promote other forms of unhealthy behaviour, they can lead to frustration, overuse and damage to a brand's reputation.


A health platform uses gamification to encourage people to exercise regularly. Users earn points and badges by participating in workouts, walking or cycling. They can also complete personal challenges, track their progress and unlock new training programmes. This helps keep users motivated to stay active.


A social media platform uses gamification to encourage users to keep returning and remain active for as long as possible through leaderboards, streaks and rewards. This can lead to unhealthy usage, an excessive focus on popularity and the creation of sensational content purely to generate more engagement.

Successful gamification aligns with users' needs and motivations while supporting an organisation's objectives, such as customer loyalty, behaviour change, knowledge transfer or social interaction.

Gamification

European privacy regulation for the collection and processing of personal data, aimed to better protect the consumer. This is called the General Data Protection Regulation (GDPR or AVG Algemene Verordening Gegevensbescherming in Dutch).

As of 25 May 2018, everyone in the European Union must conform to the regulations stipulated in the General Data Protection Regulation (GDPR). The GDPR ensures that personal data can only be collected under strict conditions and only if it is used for legitimate purposes. In addition, organizations are obliged to protect the collected personal data from improper use and respect the rights of all persons involved.

What should your company do in order to be GDPR-compliant?

– indicate what personal data you collect and process
– explain why you use and process personal data
– clearly demonstrate how you collect the personal data
– specify how long you will store the personal data

make sure the correct protection of personal data is already taken into account in the design phase of the products and services. Make sure no additional data is registered without permission


appoint a Data Protection Officer if you process data of more than 5,000 persons per year


make sure you can show individuals have given their consent, for the collection and processing of their data, based on complete information


make sure you can provide the collected information to the individual involved


make sure the collected data is properly protected from data breaches


make it possible to electronically transfer the collected individual personal data from your system to another


give individuals the option to have their data deleted

New compared to previous privacy regulations:


– being able to prove valid consent from individuals to collect their personal data
– making it just as easy for individuals to give and to take back their consent

GDPR

 is a location-based technology that creates a virtual boundary around a specific geographic area. When a user with location services enabled enters, leaves or remains within that area, predefined actions can be triggered. In marketing, geofencing is commonly used to deliver relevant advertisements, push notifications or other personalised experiences based on a user's location. This is only possible if the user has granted permission and in compliance with applicable privacy legislation, such as the GDPR.


Geofencing is used by retailers to send special offers to customers near a store, by event organisers to provide visitors with additional on-site information, and by advertisers to reach audiences when they are near a specific location, such as one of their own locations or that of a competitor (competitor targeting).


A supermarket chain creates a virtual boundary with a radius of 500 metres around its stores. When a user with the supermarket's app and location permissions enabled enters the designated area, they receive a push notification with a current offer. Once the user leaves the area, no further ads or messages are delivered for that specific location.

Geofencing

 is het doen van misleidende, overdreven of onvoldoende onderbouwde milieu- of duurzaamheidsclaims om de indruk te wekken dat een bedrijf, product of dienst milieuvriendelijker of duurzamer is dan in werkelijkheid het geval is. Greenwashing kan vele vormen aannemen, waaronder het gebruik van vage bewoordingen, het selectief benadrukken van positieve informatie, misleidende labels of certificeringen, of het uitlichten van beperkte milieuvoordelen terwijl een veel grotere negatieve milieu-impact buiten beschouwing wordt gelaten.

Naarmate consumenten en toezichthouders steeds meer transparantie verlangen, komen misleidende duurzaamheidsclaims onder toenemende juridische en maatschappelijke aandacht te staan. Binnen de Europese Unie moeten bedrijven ervoor zorgen dat milieuclaims duidelijk, nauwkeurig en met bewijs onderbouwd zijn. Misleidende of onvoldoende onderbouwde claims kunnen in strijd zijn met de consumenten- en reclamewetgeving.


Een cosmeticabedrijf introduceert een nieuwe lijn huidverzorgingsproducten die wordt gepresenteerd als "natuurlijk" en "milieuvriendelijk". In de reclame-uitingen worden beelden gebruikt van bossen, bloemen en groene landschappen, terwijl de verpakking is vormgegeven in aardetinten en de communicatie sterk de nadruk legt op duurzaamheid.

Bij nader onderzoek blijkt echter dat slechts een klein deel van de ingrediënten van natuurlijke oorsprong is, dat de producten nog steeds milieubelastende stoffen bevatten en dat de plastic verpakking niet recyclebaar is. Bovendien levert het bedrijf geen bewijs om de milieuclaims te onderbouwen.

Dit is een voorbeeld van greenwashing, omdat de marketing een duurzamer beeld schetst dan door de beschikbare feiten kan worden onderbouwd.

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