How Will Generative AI Impact Programmatic Media Buying?
What if there was a (programmatic) revolution, but nobody came?
The integration of AI and generative AI into programmatic media buying has the potential to reshape the advertising industry for years to come. Remember yesterday when it was all about automation? But with generative AI entering the game creative possibilities emerge that have the potential to generate compelling ad content tailored to individual audiences.
This brings fundamental changes to programmatic media buying. Publishers who want to stay on top of their game have to future-proof their businesses today to be part of the programmatic AI revolution.
But let’s take a step back and look at programmatic media buying. Programmatic media buying has been a game-changer, allowing advertisers to automate the process of buying and placing ads, but what happens when you introduce the power of generative AI into the mix?
What is Generative AI?
Generative AI, short for Generative Artificial Intelligence, is an advanced technology that enables users to swiftly produce new content such as text, images, audio, and more, that appears to be created by humans, by learning patterns, and structures from large datasets.
According to a Hubspot trend report “AI Trends for Marketers” The most popular AI tool for content creation is Compose AI (18%), followed closely by Jasper (17%) and Copy.ai (16%) but the most famous AI chatbot remains ChatGPT, which reached 100 million users in just two months.
The difference between AI and generative AI
Artificial Intelligence (AI) is a broad field of computer science. It focuses on creating machines and computer programs that can perform tasks that typically require human intelligence. AI encompasses a wide range of techniques and technologies, including machine learning, natural language processing, computer vision, and more. It aims to develop systems that can reason, learn from data, solve problems, understand and generate human language. Meaning it makes decisions in a way that mimics human intelligence.
Generative AI is a specific subfield or application of AI. Generative AI refers to AI systems that are designed to generate new content or data that is difficult to differentiate from human produced content. AI systems create this content, such as text, images, music, and more, by learning patterns and structures from existing data. Meaning, the main difference between AI and generative AI is their scope and focus:
AI: AI is the overarching field that encompasses a wide range of technologies and methods aimed at creating intelligent machines that can perform tasks across various domains, including but not limited to natural language processing, computer vision, etc.
Generative AI: Generative AI is a specific application or subset of AI that specializes in creating new data and content. Generative AI models focus on tasks such as text generation, image synthesis, and music composition, where the goal is to generate creative and human-like outputs.
The Impact of Generative AI on Programmatic Media Buying
So, how does generative AI fit into the world of programmatic media buying? For one generative AI models can be used to analyze the context and content of CTVs. It then generates insights into the most suitable ad placements based on the obtained data. But the impact of generative AI on programmatic media buying goes far beyond:
- Enhanced Ad Creatives
Generative AI can be used to create compelling ad creatives. By analyzing consumer data, it can generate personalized ad content that resonates with individual viewers. This goes both ways, publishers are benefitting from ads that speak directly to the interests and preferences of their target audience. And some users might actually like the idea to see ads that are generated with their interests in mind.
- Audience Targeting and Segmentation
One of the strengths of programmatic media buying lies in its ability to target specific audiences. Generative AI takes this a step further by continuously analyzing user behavior and adjusting ad campaigns in real-time. Think about it, it means that your ads can adapt to changing consumer preferences on the fly.
- Ad Placement and Optimization
Automated bidding and ad placement are benefitting from generative AI as well, because the algorithms can optimize ad placements based on various factors, ensuring that your ads reach the right users at the right time, while also staying within budget.
- Fraud Detection and Prevention
Ad fraud is a persistent challenge in digital advertising. Generative AI can help identify and mitigate ad fraud by analyzing patterns and anomalies in ad delivery. This saves money but also maintains trust and transparency amongst publishers and advertisers.
The benefits of generative AI
You’ll agree that generative AI is pretty impressive although its important to consider its ethical concerns, for example biases in training data, but let’s look at some key advantages:
Content generation: Generative AI can automate the creation of content, including text, images, music, and more. This is valuable for content creators, marketers, and businesses looking to generate a large volume of content quickly. We are not saying that’s the right approach but it can definitely be helpful to integrate some AI into once content strategy.
Anomaly detection: Generative models can be used to identify anomalies or outliers in data, aiding in fraud detection, quality control, and cybersecurity.
Data augmentation: Generative AI can be used to create additional training data for machine learning models, improving their performance and generalization to real-world scenarios.
AI is undeniably here to stay, and the field of Generative AI is only in its nascent stages, poised to revolutionize various aspects of our (digital) lives. As this technology continues to advance, it will undoubtedly make tremendous impacts on numerous domains, including but not limited to personalization, predictive analysis, ad creative assistance, and many more.
So, the future of programmatic media buying has arrived, with generative AI leading its way. As generative AI continues to evolve, we can expect more sophisticated, hyper-personalized ads, improved targeting, and enhanced fraud detection. The industry will need professionals well-versed in AI and ethical practices to navigate this exciting but complex landscape.