From Traditional Buying to Agent-to-Agent Technology

The digital advertising market currently operates primarily through two models: Direct IO and programmatic.

• Direct IO offers transparency and control but is less scalable and requires manual processes.
• Programmatic offers scale and speed but operates through multiple technological layers. As a result, a significant portion of the budget is allocated to infrastructure rather than media.

The agentic model organizes this differently. Instead of an auction-based model, the demand and supply sides communicate directly with each other through structured data exchange. Negotiation and activation take place automatically based on predefined rules.

Working Media and Operational Efficiency

Within this campaign, the share of Working Media increased from approximately 70% to 94%. Concretely, this means that instead of around €0.30 per euro being allocated to technological intermediaries, approximately €0.06 is spent on infrastructure. About €0.24 per euro is therefore redirected toward actual media impact.

Additionally, a campaign can go live within approximately two hours, from briefing to activation. Whereas traditional buying processes involve multiple intermediaries and manual steps, this process is fully AI-driven.

Continuous Optimization

Importantly, optimization fundamentally changes. Because negotiation, activation, and adjustment take place continuously via agents, optimization can occur in real time based on context, performance, and price. This does not happen at fixed evaluation moments but continuously and at scale.

As a result, optimization can take place more deeply, faster, and more frequently than is possible within a traditional human-managed model. The operation shifts from campaign management to agent management.

How Does It Work in Practice?

On the publisher side, Planet Nine Media configures the Sales Agent. This agent makes inventory available, including contextual information, quality parameters, and pricing agreements.

The Buying Agent receives the briefing from BridgeFund, including target audience definition, contextual preferences, and performance criteria. Through AdCP, this is translated into a structured request. The Sales Agent evaluates this request and responds with suitable inventory, including contextual data and pricing agreements.

If necessary, the agents submit counterproposals based on predefined negotiation rules. Once agreement is reached, the media buy is automatically created and activated.

Within this model, no traditional DSPs or SSPs are used, and no open auction takes place.

A new standard for programmatic advertising

The programmatic landscape is becoming increasingly complex. With the rise of AI-generated content and the growing number of Made-for-Advertising sites, maintaining control over advertising environments is more challenging than ever. 

To tackle that challenge, Draft Digital became the first agency in the Netherlands to introduce Brand Standards — an AI-driven solution from Scope3 that evaluates content based on nuance and context, rather than relying on simple keyword blocking.

Instead of using a standard brand safety blocklist, an LLM agent (large language model) determines in real time whether a webpage is suitable to place a brand alongside. It evaluates context, brand values, fraud prevention, CO₂ emissions, and attention metrics.

“We are proud that Draft Digital was the first Dutch partner to implement Brand Standards. It shows how innovation and sustainability can go hand in hand.”
— Kate Moeller, Director  of Partnerships Europe, Scope3

Strategy, implementation and guidance by Draft Digital

Draft Digital oversaw the entire process: from the strategic development of the prompt to the technical implementation and A/B testing to make the impact measurable.
Together with BridgeFund, a Brand Standards prompt was developed that precisely defined which content is ‘aligned’ and ‘unaligned’ with the brand. The following, among others, was excluded:

• content related to violence, fraud, war, or sexually explicit material
  
• economic crises or negative policies affecting vulnerable groups
  
• puzzle, gaming, and radio sites
• In addition, preference was given to high-quality content in specific languages, including Dutch, Turkish, Arabic, French, German, Italian, Spanish, and English.

The prompt was then tested on 183,000 Dutch articles. With feedback from the team, the AI agent was continuously refined— a strong example of the ‘Human in the Loop’ process that Draft Digital prefers in its AI-driven approach.

Measurable impact on brand metrics and performancee

The pilot, carried out by Draft Digital in collaboration with BridgeFund, delivered compelling results:

• +2% higher viewability (from 84% to 86%)
  
• –30% lower CPA
  
• +3% more ad exposure >10 seconds (from 36.87% to 39.61%)
  
• –50% decrease in Cost per Lead in an A/B test between two line items

The insights confirm that brand safety does not have to come at the expense of performance. By using context more intelligently, greater impact was achieved with less advertising waste.

“With this approach, we were able to define much more precisely where our ads did and did not belong. That gave us greater control and noticeably better results.”
— Mark Hoekx, Performance Marketeer, BridgeFund

The next step: moving toward agentic advertising

Following the success of the pilot, Draft Digital is now working on the structural integration of Brand Standards across its full programmatic approach. BridgeFund is one of the first partners to also apply this structurally within its campaigns.
The next step? Testing with Brand Stories — an advanced LLM solution that personalizes ads in real time based on audience segmentation.

“Agentic advertising is the future. With this technology, brands like BridgeFund can advertise at scale, internationally, and with meaningful relevance. We’re excited for what comes next.”
— Aliks Roling, Digital Marketing Consultant, Draft Digital

The Challenge

As a lottery brand, Lot of Happiness aims to reach a broad audience with inspiring campaigns, but in a responsible way. On Meta, large-scale reach campaigns were purchased without insight into the content alongside which the ads were appearing. While Meta allows targeting by age group, a feature already in use, there was still a potential mismatch when it came to the context in which the ads were shown. 

The Solution

To address this challenge, Lot of Happiness partnered with Draft Digital to use Scope3’s innovative Brand Standards solution. This AI-driven system enables brands to create their own brand agent, fully tailored to their values and guidelines. Scope3 has access to all content IDs within Meta and uses Large Language Models to analyze whether the content aligns with the brand profile. Any content that does not match is classified and excluded from the campaign within 3–5 hours of being posted on Meta.

What makes this solution unique:

• Personal brand profiles: The AI is trained with input from the brand, ensuring maximum relevance.
• Sustainable impact: In addition to the Brand Agent, Scope3 also takes CO₂ emissions into account across different times, placements, and creative types. 
• Broad focus: In addition to brand safety, Scope3 also looks at attention KPIs to maximize impact.
• Human-in-the-loop process to validate content through human review, allowing the AI model to be trained even more effectively. 

Results

The initial results are promising:

• 25% of content IDs were blocked during the test period. For Lot of Happiness, this shows the importance of adding this classification method, as there is still a large amount of Meta content that does not align with the brand’s values. 
• No negative impact on performance — reach, CPM, viewability, and exposure time remained stable.
• Better brand protection by preventing impressions alongside unwanted or sensitive content.
• Greater relevance for the end user through a more precise alignment with the brand profile.

“The context in which people see your ads is – especially for us as a lottery – extremely important. With Scope3, we can be sure that our ads won’t appear alongside content that doesn’t align with our values, such as content related to children or addictions.

“On the other hand, we want to be able to adapt the content of our ads to the context. For example, in an article about charities, we like to show images of our annual donations, while in an article about long-distance travel, we prefer to highlight the chance to win big. We’re really looking forward to experimenting with this together with Scope3 and Draft.”
— Leo Nijs, Online Marketer at Lot of Happiness

“As an agency, we believe it’s important to stay ahead of the curve. The Scope3 solution is not only scalable and easy to implement, but it also delivers immediate, visible results.”
— Lars Postmus, Founder of Draft Digital

Next steps

The positive results mark the starting point for a broader deployment of Scope3 within Lot of Happiness’s media mix. In the coming period, Brand Standards will be tested within programmatic campaigns to gain more control over context and brand safety there as well. In addition, the current brand profile will be further refined to improve performance. 

At the same time, we will experiment with the use of Scope3 Brand Stories, in which personas take center stage. This combination of brand safety and relevant storytelling not only protects against unwanted associations but also creates opportunities for improved performance. The ambition is to make AI-driven content matching a permanent part of Lot of Happiness’s always-on media landscape.

Phases & Metrics

There are various metrics and phases you can build a custom algorithm around, from sales metrics such as conversions or Q‑Visits (a quality click) to other metrics tailored to specific time windows, post‑click, or view‑through attribution. By assigning a value to each conversion action within the custom algorithm, you can guide it to optimize exactly as you intend.

It’s also possible to evaluate clicks and assign a value to them. However, we generally advise against this, as a click with no further value doesn’t tell you much.

Finally, you have a range of awareness metrics you can optimize for, one of the biggest improvements over the old custom models. In the next section, we’ll take a closer look at the different metrics and highlight the most important ones.

Viewable Impressions

A simple example of value assignment is the viewability metric. By focusing on viewable impressions, you can guide the algorithm. This approach is fairly similar to the standard viewable algorithm, and it only becomes truly valuable when combined with other metrics.

Time in View

The next variant is far more interesting. By assigning a value to the number of seconds a banner is in view, you can optimize for longer time‑in‑view, a feature not available in the standard algorithms. At Draft Digital, we recommend setting a maximum value, as some sites naturally have long view times that aren’t necessarily high‑quality. A good example is Nederland.FM, an online radio station that often plays in the background. While DV360 will register the banner as in‑view for a long time, this doesn’t always mean it delivers valuable attention.

Completed Views

It’s also possible to incorporate completed views, although this is already available within DV360’s standard algorithms. However, combining this metric can be especially valuable when it comes to video campaigns.

Audibility

This metric is often overlooked in video campaigns, yet it’s incredibly important. Without sound, a video can’t be truly heard, and most advertisers create their videos with audio in mind. This issue is especially common with outstream placements, where sound is typically turned off. Since outstream ads tend to be cheaper than instream placements, standard algorithms often allocate a large portion of the budget to these slots. By adding audibility as a metric and assigning a value to it within your algorithm, you can deliver more impactful results.

Screen Size

This metric is also a strong addition to video campaigns. In programmatic advertising, there’s a lot of inventory that doesn’t deliver quality results, and it’s common to see “instream” video positions sold where the consumer’s attention doesn’t actually land. For example, placements that are technically in‑view, but positioned where the viewer is unlikely to look.

Fold Position

In programmatic advertising, performance can vary greatly depending on whether a banner is placed above or below the fold. Until now, this was only available as a reporting metric, allowing you to include or exclude certain positions in campaigns. By adding this to a custom bidding algorithm, you can gain more control and optimize specifically for above‑the‑fold placements.

Device

Especially with video campaigns, we see that the device used can have a significant impact. Many advertisers now adopt a Connected TV strategy. By adding device targeting to the custom bidding algorithm, you can optimize more precisely for the devices that matter most.

Scoring vs. Multiplier

The advantage of the custom algorithm tool is that it gives you different ways to assign value to impressions. For the most common metrics, you can only apply a score, but for fold positions, you can also add a multiplier. This is especially important for advertisers who want to secure top‑of‑page positions. By applying a multiplier, you can exert more precise control over these high‑value placements.

Usability

The DV360 Custom Bidding model is a highly practical way to optimize for awareness KPIs. Through experiments in DV360, it’s possible to test this approach effectively against standard models. However, you’re still limited to the metrics and KPIs available within DV360 itself. To truly optimize for attention value, third‑party tools such as DoubleVerify, MOAT or Lumen are required.

Summary

The use of custom algorithms within DV360 provides a valuable and practical way to improve the effectiveness of display, video, and native campaigns, especially now that traditional tracking methods are under pressure. By integrating metrics such as viewability, time in view, audibility, and fold position, advertisers can optimize more precisely for the quality of their impressions. While this approach delivers significant benefits, it’s important to acknowledge the limitations of DV360 and, when needed, complement it with third‑party tools such as DoubleVerify, MOAT, or Lumen to enable more in‑depth attention measurement. At Draft Digital, we believe in the power of tailored solutions and continuous optimization, helping us grow together and deliver outstanding results. If you’d like to learn more, feel free to get in touch with us via this (link).

Data has become a valuable asset for businesses. Collecting and analyzing data can provide valuable insights that lead to improved performance and decision-making. This is especially true in digital marketing and programmatic advertising, where data has been a crucial component of success. Historically, third-party cookies were used to track users across the internet, allowing advertisers to serve the right content at the right time. However, third-party cookies are set to disappear permanently in the near future, and their reliability is already far from optimal. Many browsers have already begun to largely block them.

For this reason, companies are seeking solutions to continue personalized advertising. In many cases, server-side tagging or customer match are used. However, these solutions are typically accessible to large tech companies like Google and Meta, making collaboration between Dutch publishers such as DPG Media or Marktplaats more challenging. To address this, various parties have explored ways to work together with these publishers, and the solution appears to be Clean Rooms.

What Are Clean Rooms?

Data bunkers are an emerging technology that enables secure data sharing and aggregation without exchanging the underlying data itself. Through Clean Rooms, companies can gain valuable insights and make data-driven decisions without compromising user privacy. Here are some ways data bunkers operate. 

Data Aggregation in Clean Rooms

Data bunkers enable the integration of data from multiple sources without sharing the underlying data itself. Instead, aggregated and anonymized statistics and patterns are exchanged, allowing companies to gain valuable insights into trends and behaviors without exposing individual information. Moreover, only Personally Identifiable Information (PII) is used, eliminating dependence on third‑ or first‑party cookies. 

Cross-Reference Analysis via a Clean Room

With data bunkers, companies can compare and analyze data across different datasets without sharing the underlying data itself. This enables businesses to gain insights into customer behavior, market trends, and other valuable information without exposing sensitive data to risk. For example, you could compare your own customer base with that of a partner, allowing you to strategically target potential new customers. 

Data Security in Clean Rooms

Clean Rooms use advanced security protocols to ensure the confidentiality and integrity of data. This includes encryption, strict access controls, and monitoring of data access to guarantee that only authorized users can access the information.

Data bunkers like Infosum (www.infosum.com) & EDM (www.edm.nl) play an important role in finding a balance between privacy and performance. Data bunkers provide a secure environment to store and process data, while enabling companies to gain valuable insights without having to share the underlying data itself. By using these technologies, businesses can safeguard privacy while still benefiting from data analysis and insights. 

So, there is a way to securely share data between different parties, but how does this work in practice, and how could it be used? 

Example of How to Use a Clean Room

In this example, we’re working with the company Draft, which wants to purchase ads on NU.nl. 

• Both Draft and NU.nl upload personal data into their own clean rooms.
  • Draft only uploads the data they want to target into the clean room. For example, people who have previously made a purchase.
  • NU.nl uploads all their data into the clean room to increase the chances of finding matches. Additionally, NU.nl must provide an ID that is used within their advertising platforms.
• It’s important to regularly coordinate how the data is structured. For example, if matching is based on postal codes, it’s crucial that the data is formatted consistently.
• Once the data is in the data bunkers, it is matched and sent back, including IDs, to NU.nl’s advertising platform.
• Draft can now purchase inventory based on these IDs through NU.nl and re-engage the target audience.

We can conclude that data bunkers offer a solution to use your own data on external platforms, but what exactly can you do with them?

How Can You Use Clean Rooms to Improve Digital Performance?

Targeting

In addition to being able to find users again, it can also be used to exclude certain customers. Look-alike audiences can also be leveraged. Since the external platform can see what these users do within their own environment, it can search for people who resemble the initial group. This allows you to deliver more relevant ads. 

Data Enrichment

By matching data with external platforms, it’s also possible to learn from this data. If you share data with Marktplaats, for example, you can discover which categories your target audience frequently browses or uses. If your audience is interested in interior design, this insight can serve as a valuable hook for other marketing efforts.

Channels

In principle, data bunkers can be utilized across all channels where CRM data is matched. Currently, this is mostly applied in display and video advertising in collaboration with partners such as DPG Media, Mediahuis, and Marktplaats. However, it should also be feasible on more traditional channels like TV. TV platforms use set-top boxes that store personal data. Although addressable advertising on TV is not yet common practice in the Netherlands, it is expected to become possible in the near future: https://www.adformatie.nl/media/adverteerders-kunnen-tv-commercials-bij-talpa-en-rtl-richten

From then on, more and more opportunities for personalization on TV will emerge. In Belgium, this is already possible. 

Retail Media and Clean Rooms

Naast reguliere advertising zien we ook een trend op het gebied van retail media. Grote partijen zoals Albert Heijn, Jumbo, MediaMarkt en Amazon zijn hiermee aan het experimenteren in Nederland. Doordat deze retailers over zeer veel first party data beschikken kan een databunker ook de connectie zijn tussen de data van retailpartner en adverteerder. Hierdoor zijn ze niet afhankelijk van reguliere customer match oplossing.

Conclusion

Alongside traditional advertising, we’re also seeing a growing trend in retail media. Major players like Albert Heijn, Jumbo, MediaMarkt, and Amazon are experimenting with this in the Netherlands. Since these retailers possess extensive first-party data, a data bunker can serve as the bridge between the retail partner’s and the advertiser’s data. This means they aren’t reliant on standard customer match solutions.

Thanks to data bunkers, companies can collaborate with external partners, such as publishers, to deliver personalized ads to the right audience without directly sharing first-party data. This opens new opportunities for advertising across various channels, including digital platforms and, in the future, even traditional channels like television.

Using data bunkers requires close coordination between the involved parties, such as the company sharing the data and the platform receiving it. Ensuring proper data structuring and agreement on the identifiers used is crucial to guarantee successful matching.

Contact

All in all, data bunkers offer a promising solution to balance privacy with personalized advertising. Through secure data sharing and advanced analytics, companies can gain valuable insights and deliver targeted ads while protecting individual user privacy. It’s a positive step forward for the future of data-driven marketing. If you’d like to receive more information about data bunkers, please contact us at get in touch with us .

Programmatic advertising has become an essential part of the digital landscape, but the way it’s purchased is constantly evolving. In the past, it was common to have precise measurement of everything, but this is becoming increasingly difficult. That’s why it’s important to consider the different tactics used by traders. Essentially, there are two types of traders, and the best trader sits somewhere in the middle. The first type lets the algorithm do most of the work and buys broadly. Their focus is on quantity, allowing the algorithm to independently optimize for quality. The other type focuses more on qualitative inventory and aims to create impact, although they still rely on algorithms from DSPs like Google or Adform.

In this blog, we’ll explore why quality-driven buying is becoming increasingly important in programmatic advertising and why relying solely on algorithmic automation is facing more limitations.

Programmatic Advertising Is Changing

Due to trends such as tracking, fraud, and attention, programmatic advertising is evolving rapidly. We highlight three key trends driving the growing importance of quality.

The Programmatic Advertising Algorithm

Tools like Google and Meta have powerful algorithms, but often they optimize for non-incremental conversions, conversions that would likely have happened anyway. While this may increase conversions at the channel level, it overlooks the true impact of ads on consumer behavior.

Measuring incremental impact, the difference your ads actually make beyond natural behavior, is essential. This can be done through Geo Experiments or Conversion Lift Studies. Regularly test to ensure your budget is well spent.

Challenges in Measuring Conversions

Conversion tracking is becoming more difficult as third-party cookies disappear. These cookies traditionally tracked user behavior to attribute conversions to ads. With growing privacy concerns, third-party cookies are increasingly restricted, forcing advertisers to shift focus toward alternative measurement methods. This shift highlights the importance of prioritizing qualitative aspects over purely quantitative metrics.

Traders who buy broadly and focus on volume will struggle to optimize post-view values, especially since click-through rates (CTR) often fall below 1%. Relying solely on click conversions means much of your media buying goes unassessed, reducing effectiveness. Start focusing on quality early and make informed inventory choices.

Traders who buy broadly and focus on volume will struggle to optimize post-view values, especially since click-through rates (CTR) often fall below 1%. Relying solely on click conversions means much of your media buying goes unassessed, reducing effectiveness. Start focusing on quality early and make informed inventory choices. Google and other DSPs will offer solutions, but it’s increasingly difficult to measure some conversion values accurately, especially on Apple devices and browsers like Safari and Firefox. Ultimately, this is about respecting user privacy.

The Importance of Standing Out in the Ad Overload

Consumers face a flood of ads daily across various platforms and channels. Capturing and holding attention is harder than ever. It’s crucial to stand out by delivering relevant, high-quality ads that make a lasting impression, even if not immediately through click conversions but via brand KPIs. Examples include:

1. Relevance and Engagement: Quality ads that align with audience interests grab attention and drive engagement. With people seeing nearly 300 ads daily on average, standing out is vital.
2. Building Brand Equity: Consistent, engaging, and relevant ads help build a positive brand image. Use distinctive brand assets so creative efforts compound.
3. Effective Budget Allocation: Focusing on quality lets advertisers allocate budgets more efficiently, avoiding waste on ineffective ads, such as fraudulent impressions. You don’t want to be caught paying for those.

How to Get Started

Quantity-driven buying often results from difficulty setting the right KPIs. How do you know if impression A is better than B? Since DSPs allow limited KPIs, many focus on CPM, Viewability, CTR, CPC, GA metrics, or CPA (post-view), which don’t fully capture quality. This makes cheap, broad inventory appear better than high-quality inventory.

In DSPs like Google DV360, Xandr, or Adform, you can increasingly gain insights into impression quality. However, third-party tools like DoubleVerify, MOAT, Lumen, and IAS excel here. These providers have long valued impressions by metrics like Authentic Attention and Attentive Seconds, and they help reduce fraud, which remains widespread. Fraud prevention alone can justify the investment in these tools.See this NOS.nl article. Just the fraud prevention benefits alone make these tools worth the investment.

Conclusion

In programmatic advertising, it’s tempting to chase quantity and maximize channel conversions. However, valuing the true quality of impressions is increasingly vital. Measuring incremental impact, tackling conversion measurement challenges, and striving for standout ads are key to ensuring quality in programmatic. Investing in relevant, high-quality ads enables advertisers to communicate more effectively and build lasting audience relationships.

Try to focus on attention metrics and check if you can correlate them to increased conversions before cookies disappear. It’s crucial to know that your optimizations impact your revenue. Geo experiments are another way to gain this insight.

Want help selecting the right tool? get in touch with us .

From various reports, including Deloitte’s Spend Report(link)and the IAB Europe Sustainability Report 2023(link)we see that sustainability is one of the most important themes for marketers. Initially, emissions were mainly discussed in relation to offline channels like print advertising, but it appears that the digital advertising industry also contributes significant CO2 emissions. This is summarized in the Scope3 report. In this blog, we will primarily focus on CO2 emissions within programmatic advertising, where they mostly come from and how things currently stand, so we can offer you concrete advice on what to do. At Draft, we believe that a sustainable marketing strategy can also lead to improved performance.

The Research

Scope3 conducted research in Australia, France, the UK, Germany, and the US to measure CO2 emissions across different advertising stages, ad creation, device usage by consumers, hosting, and ad delivery. A new metric called gCO2pm was introduced, measuring grams of CO2 emitted per 1,000 impressions. Key findings include:

By Country

The US has the lowest relative emissions, while Germany has the highest. Although the US emits the most overall, differences between countries are relatively small, which makes sense given the widespread use of international programmatic tools like Google and Xandr. For context, billions of impressions are served daily, and 1,000 impressions equal roughly one load of laundry. 

By Publisher

Emissions vary widely by publisher, ranging from 187 to 1,772 gCO2pm, compared to 511 to 631 by country. Publishers with sites primarily designed for ads (MFA sites) score poorly in emissions, as do sites with low editorial value or fraudulent activity. Steering your strategy away from such sites can reduce emissions. MFA sites typically show:

• High ad density
• Mostly clickbait content
• Traffic largely from paid channels

On average, MFA sites emit 13% more CO2. 

Programmatic Process Stages: How to Practice Sustainable Marketing

The programmatic process consists of four stages:

Ad Selection

The supply path where ads are traded, including SSPs, data sources, and targeting tools. 

Creative Distribution

Emissions linked to producing the ad, like banner creation and involved suppliers. 

Media Distribution

Total emissions associated with media delivery, including company emissions, data transfer, and electricity grid impact.

Consumer Device

The time consumers spend viewing ads on their devices. 

As expected, Ad Selection and its related processes generate the most emissions. Real-time bidding depends on many parties (SSPs, DSPs, Ad Servers, data providers). The prevalent open market strategy triggers many tool requests for each bid offer, multiplying system emissions. However, there are ways to reduce these. 

Steering Towards CO2 Reduction: Positive Results

A Scope 3 study found that pausing the top 10% highest-emitting sites led to positive results, a 1.4% increase in completion rate and a 9.9% reduction in emissions. This illustrates how CO2-focused steering can benefit performance.

Sustainable Marketing and Emission Reduction in the Dutch Market 

The Dutch market is also making progress to reduce emissions. Agencies are increasingly tracking their media’s carbon footprint to foster conversations and action. DPG Media is developing a self-serve platform that integrates with their tools to limit tool use and reduce emissions. Adform is working to incorporate emission studies in their DSP, automatically excluding MFA and other high-emission sites. These tools help advertisers steer toward sustainable marketing.

What Can You Do to Create a Sustainable Marketing Strategy? 

Reducing emissions can be challenging, especially for smaller agencies and advertisers. Conducting a CO2 audit of your programmatic supply path can be costly and may not be feasible for all. However, there are steps you can take:

Sharpen your whitelist

As mentioned earlier in this article, MFA sites emit 13% more CO2 than the average website, making it a simple choice to reduce emissions by excluding them. It might be wise to first conduct a domain analysis to assess the impact of excluding these domains. However, we have found that the quality of these sites is often lower since their traffic mainly comes from paid advertising. The value of remaining on these sites is relatively low. 

If you’re not already using a whitelist, Draft strongly advises you to start. The internet is vast, with thousands of websites, making it impossible to monitor whether your ads appear on trustworthy sites without a whitelist.

Prevent Fraud

Fraudulent sites also contribute significantly to emissions, and this is something that can be identified. In 2022, NOS published an article revealing that tens of billions are lost annually due to fraud. Additionally, fraudulent impressions hold no value, and excluding them can lead to improved performance. Therefore, addressing fraud is a logical and important step.

Ways to do this include:

• Use brand safety settings available in various DSPs.
• Utilize anti-fraud detection tools like DoubleVerify or MOAT. Always evaluate whether these tools continue to add value over time, and discontinue use if they don’t.
• Implement a stricter whitelist.

Take Inventory of Your Current Advertising Stack

Take a critical look at the tools currently under your management and evaluate the added value of each. Are all these tools still necessary to keep in use? 

Engage in Conversations with Partners

Even if you don’t have insight into the footprint of your digital ads, it can still be worthwhile to engage in conversations with your partners. They may have this information and be able to help optimize it.

Analyze Your Buying Strategy

Even if you don’t have the footprint of your digital ads, it can still be valuable to start a conversation with your partners. They might have this insight and be able to help steer it.

Ambition for the Dutch Market

Since this topic is relevant for the entire market, it would be logical for industry organizations to take the lead in analyzing what is and isn’t emitting, so all advertisers and agencies can benefit. This approach also enables smaller parties to contribute and ensures the entire market views this major societal issue consistently.

Want to learn more about sustainability in media? get in touch with us .

What Is Display Advertising?

Display advertising refers to placing visual ads, such as banners or images, on websites, apps, and other online platforms. It’s used to attract users’ attention and engage them with a brand, product, or service. These ads appear in strategic locations on web pages or even within content itself. The goal isn’t just immediate conversions but building brand awareness and influencing potential customers throughout their online journey through targeted placements.

Display Advertising Is Not a Last-Click Channel

Display ads are often not considered ideal for generating last-click conversions. Instead, they serve as a platform to boost brand awareness or spark interest. It’s about creating a presence where potential customers spend time online. Through compelling banners and rich media, advertisers can show CTAs and capture user attention. While this can lead to later conversions, display advertising is better suited for awareness and prospecting goals.

Hyper-Targeted Advertising for Every Audience

One of the most compelling reasons to embrace display advertising is the wide variety of targeting options available. Whether targeting business clients (B2B) or consumers (B2C), display advertising can be tailored to specific demographics, behaviors, and interests of the audience. This targeting enables advertisers to deliver their message to people who are likely to be interested. For B2B, using broad audiences is less effective; instead, selecting specific titles, such as those from Vakmedianet.nl or FD Media groep specific titles can be chosen. For B2C, DSP data can be utilized, or collaborations can be made with Dutch publishers like DPG and Mediahuis.

Partnering with Quality Publishers

Choosing where to place your display ads is crucial. Working with reputable publishers such as DPG, Mediahuis, or Talpa not only boosts your ad credibility but also builds trust and transparency with your audience. Advertising on trustworthy websites increases your chances of success.

Tips for Effective Display Advertising

To run successful display campaigns, deploying skilled specialists is vital. Here are some quick tips:

• Inclusion Over Exclusion Use a strict inclusion list rather than an exclusion list to focus on premium placements that align with your brand and audience, minimizing misplaced ads.
• Challenge Google Audiences: Google’s audience segments are helpful but should be tested and not blindly trusted. This helps you maintain control and reach the right targets.
• Use Third-Party Tools Utilize tools like MOAT or DoubleVerify to monitor impression quality and ensure ads run on safe, reliable platforms.
• Custom Algorithms for Optimal Results: Collaborate with your Demand Side Platform (DSP) to create custom algorithms. This ensures your DSP understands your goals and strategies for more efficient ad optimization.

Display advertising offers a powerful platform to engage users in context, build brand awareness, and leave a lasting impact. By leveraging hyper-targeted strategies, partnering with premium publishers, and applying a strategic approach, you can turn display advertising into a key marketing asset.

If you don’t yet have a skilled specialist or just want to brainstorm. get in touch with us .

In the (research) by Screenforce, they have shown that television viewing time continues to decline. As a result, more advertisers are compelled to adopt an effective online video strategy. A key ad format in this strategy is the preroll. In this blog, we explain what a preroll is and how to use it effectively.

What Is a Preroll?

A preroll is a short video ad that plays before the main video content begins. It’s the first ad you typically see when watching a YouTube video or other online video platforms. Prerolls usually last between 15 and 30 seconds, giving advertisers the chance to communicate their message before viewers focus on the main content.

Difference Between Preroll, Midroll, and Postroll

Besides prerolls, there are midrolls and postrolls. Though these ad formats are similar, their differences are significant:

1. Preroll: Plays before the main content. It’s the first ad the viewer sees and is generally considered less disruptive than midrolls or postrolls because it doesn’t interrupt the viewing experience.
2. Midroll: Inserts an ad during the main content. This can be more disruptive as it forces viewers to pause the video to watch the ad.
3. Postroll: Plays after the main content has finished. Usually seen as the least effective, as viewers often leave before the postroll plays.

Why Are Prerolls More Effective?

One key reason prerolls are preferred over midrolls and postrolls is their higher View-Through Rate (VTR), the percentage of viewers who watch the ad to completion. Prerolls generally have higher VTR because they’re the first video the user sees, making them less likely to leave the page and more likely to watch the full ad.

On YouTube, prerolls can be skipped after 6 seconds, but many prerolls elsewhere do not offer this option, requiring users to watch the full content. Postrolls tend to have lower VTR since viewers often leave before the ad plays, reducing the advertiser’s message impact.

What to Consider When Buying Prerolls for Online Videos

As an advertiser, effective use of prerolls is crucial. Keep these points in mind:

1. Use Private Marketplaces or Programmatic Guaranteed Deals: In the Netherlands, quality inventory is scarce. Direct contact with publishers through Private Marketplaces or Programmatic Guaranteed ensures quality and price agreements.
2. Look Beyond Impressions and Cost Per Completed View: Consider metrics like video viewability, whether sound is on, and viewer interaction. These help assess ad quality.
3. Mind Device Ratios: Research shows that connected TV often delivers better results than mobile or desktop. Consider where your target audience watches videos and adjust your strategy accordingly.
4. Relevant Content: Ensure your message aligns with the audience and the type of video content where the preroll appears. The user’s screen, mobile device or TV, influences ad impact.

Prerolls are a powerful way to capture online viewers’ attention before they engage with the main content. By applying the right strategy in buying prerolls and considering key metrics and audience behavior, advertisers can create more effective campaigns and amplify their message impact in online video advertising.

If you need help buying prerolls, get in touch with us .

Understanding the System Floodlight Model

The System Floodlight Model is the default attribution method within CM360 and DV360. This means campaign optimization is based on this model. As shown in the image below, it’s possible to optimize or customize this attribution method with various options.

Baseline Attribution Models

Baseline is the attribution model used to manage campaigns in the Google Marketing Platform and DV360. Several models exist, with the Floodlight model as the default. Other options include Last Interaction, First Interaction, Linear, Time Decay, Position Based, and Data-Driven Attribution. The Data-Driven Attribution model is particularly interesting to test. Based on the Markov Model, it determines the value of an impression or click. It can be insightful to create an attribution model using Data-Driven Attribution and compare it with the standard Floodlight model. The other models are, in our opinion, less relevant, though they do provide useful insights. Markov Model which determines the value of an impression or click. It can therefore be valuable to create an attribution model using Data-Driven Attribution and compare it with the standard Floodlight models. The other models are, in our opinion, less relevant, although they do provide useful insights.

Attributed impressions

The next attribution choice concerns which impressions are included. In the default model, all impressions are counted, including non-viewable impressions. This is something you want to avoid, as it allows Google DV360 to optimize based on conversions tied to ads that were never actually seen by the final buyer. These are never incremental conversions and therefore represent wasted spend. It is possible to adjust this to Viewable Impressions or Engaged Views. Viewable impressions are measured according to the IAB standard, while engaged views can be defined based on your own criteria. Variables that can be added include viewability, time in view, device type, view-through rate (VTR), and skip vs. non-skip.

Draft recommends using viewable or engaged views within your attribution model, deviating from Google’s default settings. However, it is valuable to compare both attribution models afterward to see how much the DSP attributes to impressions where the banner was not viewable.

Modeled Conversions

Finally, you can choose to include or exclude Modeled Conversions. As Google’s tracking capabilities decline, modeling conversions has become necessary. Without it, you risk excluding entire browsers, such as Safari or Mozilla Firefox. Modeled conversions are enabled by default in the standard model, but it can be insightful to compare how much Google models and on which devices or browsers this occurs.

Conclusion & Advice

As you have read, we do not recommend using the standard attribution model and advise customizing it based on your own insights. Here are a few key positions we take on this:

• Compare multiple attribution models.
• Do not attribute non-viewable impressions.
• Try Data-Driven Attribution.

Experiment with different models to better understand how DV360 works and improve your campaigns. Attributing views to a platform is tricky since multiple channels are often involved. How can we guarantee that a view was decisive for a conversion without full customer journey insight? Despite this, views can guide the algorithm, so you might choose to count only a percentage of post-view conversions, which can be set in the DSP.

Need Help With Attribution in Your (Display & Video) Campaigns? We’re happy to assist you.