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.

Today, many technological advances fall under the umbrella of AI, including generative AI. In this blog, we’ll explore the difference between generative AI and AI, discuss the rise of generative AI, and explain why it’s worth using. We’ll also look at the impact it will have on media and marketing activities.

“Traditional” AI

Let’s start with AI in general. AI refers to algorithms and models designed to perform specific tasks based on pre‑defined rules, and it has been used for many years. These programs rely on massive amounts of data to identify patterns and make predictions. They can handle complex tasks and have long been used in digital marketing, for example, optimizing campaigns in platforms like Meta or Google.

In the past, it was critical for marketers to have deep channel expertise to optimize campaigns effectively. Today, it’s more common to be advised to buy media as broadly as possible. We also see this shift in the role of specialists, who are increasingly trained as generalists.

In this approach, the algorithms do the work, and the generalist monitors the results. In many verticals, this works well, but in others, the algorithm doesn’t always deliver the best results.

At Draft Digital, we believe in a mix of highly trained specialists combined with the right technology. We also recognize that broad media buying can be highly effective, but we’re convinced that adding data to media delivers better results — and that’s where deep expertise is needed.

Generative AI

Generative AI, on the other hand, aims to create new, original content that mimics human creativity. It uses advanced machine learning to learn from massive datasets and applies this knowledge to produce new data. This technology has been around for some time, but it really gained mainstream attention with the launch of ChatGPT in November 2022.

Generative AI can be used to create text, music, code, images, video, and much more. Its unique feature is that it can create something new based on its learnings, without relying on specific rules or instructions.

A key characteristic of generative AI is the concept of “unsupervised learning.” Unlike traditional AI, where input and output data must be clearly defined, generative AI can learn and operate from unlabeled data. This allows it to push boundaries and come up with entirely new ideas.

Applications of Generative AI

Generative AI has the potential to transform many industries. In marketing, it can help marketers create better content for their target audience. It can aid media strategists in generating more compelling creative ideas for clients, or help data marketers build more effective analyses, or even write better scripts.

Although generative AI offers promising possibilities, it also brings challenges, such as ethical considerations and the risk of misuse. It’s vital to approach its development and use responsibly to ensure it contributes to positive progress and doesn’t cause harm.

Looking at the evolution of AI and generative AI, it’s clear that generative AI is an exciting leap forward in the development of artificial intelligence. Its ability to create new content and unlock creative potential opens the door to fresh opportunities and innovations. While AI as a whole encompasses a broad range of applications, generative AI is the branch that invites us to move beyond mimicking human intelligence, allowing us to create something genuinely new and unique.

Adopting AI in Your Organization

Generative AI offers significant benefits for marketing organizations and can be a valuable tool for boosting campaign effectiveness. Our advice is to experiment with tools like ChatGPT and Bard. By leveraging generative AI, marketers can work more quickly and efficiently.

Moreover, generative AI allows marketers to test and iterate rapidly, making it easier to respond to changing trends. By embracing generative AI, marketing organizations can gain a competitive edge, boost productivity, and deliver more personalized and compelling experiences for their audiences. If you’d like help implementing AI within your organization, get in touch with us .

Why Is It So Important to Embrace Artificial Intelligence in Your Organization Right Now?

At Draft, we’re increasingly noticing that staff who use AI extensively in their work stand out compared to other employees. What’s striking is that, according to ICT Magazine, 80% of people still haven’t used ChatGPT (Link). Employees who use these tools can carry out many tasks faster and more efficiently, from conducting data analyses and creating content to building scripts.

At the moment, we still see people in our line of work who don’t use generative AI because they don’t recognize its benefits. Right now, it’s not a requirement to use generative AI in your job, it’s not yet essential. However, in about two years, it’s very likely that it will be expected. If you don’t have enough knowledge or experience by then, it could have an impact on your future career prospects.

We also expect the role of an operational (media) specialist to evolve more and more into that of a ‘prompter.’ It will become increasingly important to be proficient with these AI tools, as they operate far faster than the human brain, and in the future, they will be even more accurate too.

This allows you to set up and optimize campaigns for platforms like Google, Meta, or TikTok much faster. To get started, it’s especially helpful to begin using AI for content creation, a relatively simple and low‑risk way to introduce AI into your workflow.

Creating Content

One of the first areas where AI can be a great help is content creation. This can range from writing text and translating it to generating images. AI can even be used to create video content, although the results are still underwhelming for now. Using AI to create content is a safe and low‑risk way to get started, and from a privacy standpoint, it’s also a relatively risk‑free approach.

Examples

Here are a few examples of how AI is used to generate content:

• Text Generated: AI can be used to generate text for blog posts, articles, web pages, and other types of content. It can also be used to create text for marketing materials, such as email campaigns or social media posts. We use ChatGPT for many of our blogs as well, although we don’t post the material directly, it often still contains errors.
• Translation: AI is used to translate text between different languages. This can help you translate content more quickly and also allows you to reach new international audiences. Do keep in mind that the quality may not be 100% perfect, although we’ve found that AI translations generally work very well. For English texts, it’s always a good idea to review and fine‑tune the translation for the best results.
• Video: It can be used to create videos that are relevant to a company’s target audience. However, we’ve noticed that this doesn’t work very well yet.
• Images: AI can be used to create images that are relevant to a company’s target audience. It can also be used to personalize images for individual users. While tools like MidJourney are often used for this, we’ve also found that Bing works well for creating simpler images. Feel free to give it a try!

Artificial Intelligence Makes Your Work Easier

As you can see, AI can help you create content quickly and make your work easier. At the same time, it allows you to become familiar with one of the most important trends for the future. AI is a powerful tool that can help generate content and enable marketers to save time and work more efficiently. However, it’s essential to review and fine‑tune the output before publishing. For this blog, we also used ChatGPT and Bard, but we still invested time in rewriting and refining the text. It’s not advisable to write all your emails with generative AI. In the next section, we’ll explore other ways generative AI can be used.

Other Ways to Use AI

AI offers marketers many possibilities beyond just creating content. By using the right prompts, it can automatically set up campaigns in platforms like DV360, Meta, or Google Ads. This allows marketers to save time on campaign setup and focus more on optimization, although it’s often recommended to buy broadly, so that AI can do the heavy lifting.

In addition, AI can be used to write scripts for data modeling and optimization, such as media mix modeling or building display banners. A simple example can be found here.

It still requires knowledge of the programming language being used, but it can take a significant portion of the work off your hands.

P.S. This example is purely for illustration purposes.

Prompt in ChatGPT: “Write an HTML5 script for a 300×250 Display Banner”

<!DOCTYPE html> <html> <head> <title>Display Banner</title> <style> .banner { width: 300px; height: 250px; background-color: #f2f2f2; border: 1px solid #ccc; text-align: center; font-family: Arial, sans-serif; } </style> </head> <body> <div class="”banner”"> <h2>Display 300×250 Banner</h2> <p>This is the content of the banner.</p> </div> </body> </html>

Conclusion

In conclusion, AI offers marketers countless opportunities to work more efficiently and effectively. From automating ad campaigns and generating content to writing scripts and conducting advanced analyses, artificial intelligence can provide valuable support. To get started with generative AI, a great first step is creating content. However, it’s crucial to adhere to privacy regulations and maintain high ethical standards when using AI. Never input sensitive personal data into these systems.

By embracing AI and integrating it into marketing activities, marketers can boost their productivity, gain deeper insights, and secure a competitive edge. It’s clear that generative AI will become an essential part of the modern marketing landscape, making it vital for marketers to understand its potential and benefits. We write extensively about AI and other trends, want to stay updated? Sign up for our newsletter.