Just 20 years ago, Artificial Intelligence existed mainly on the pages of science fiction books, comic books, and movies. However, the world is developing with constant acceleration, equal to the acceleration of free fall, so today, AI is part of everyone’s routine life. AI is everywhere: in our interactive maps with geolocation functions, translators, messengers, and our favorite social networks.
According to Statista, the AI market will grow 20 times to nearly two trillion dollars by 2030.
The emergence of ChatGPT turned the world upside down, and the fact that in the first 5 days of availability, it gathered the first million users, in itself, speaks volumes. Society is just as interested in AI as we may need it in our daily lives.
Some are very happy that new technologies are coming quickly and easily into our lives. Some fear it because “AI will take people’s jobs away”. Some even create conspiracy theories that the machine rebellion is just around the corner. These views are likely to have enough evidence to be true to some extent.
But the fact is that progress cannot be stopped. You can only learn how to use it. And it is better to learn right now because if you do it later, you can fall far behind your competitors.
This is why the advertising industry has very quickly integrated Artificial Intelligence and Machine Learning capabilities into its products. AI plays a crucial role in programmatic advertising, using Machine Learning algorithms to analyze large amounts of data and make real-time decisions about ad placement, targeting, and optimization.
With AI, advertisers can spend much less time creating pictures and texts for the ad, personalize ad content, and target audiences based on their behavior, interests, and demographics, resulting in higher engagement and conversions. AI also helps automate the bidding process, making it faster and more efficient, and can detect and prevent ad fraud by analyzing patterns and identifying suspicious activity.
But let’s take it one step at a time.
What is programmatic advertising?
Programmatic advertising is the automated purchasing and selling of digital advertising space through a bidding system. This system allows advertisers to reach specific audiences with relevant real-time ads. The increasing popularity of programmatic advertising is due to its efficiency, accuracy, and effectiveness in reaching the desired audience.
What is Ad Exchange with Programmatic Advertising?
Ad exchanges and programmatic advertising are two interrelated concepts that have changed how digital advertising is bought and sold.
An ad exchange is a platform that allows you to buy and sell digital advertising inventory in real time through a bidding process. In other words, an ad exchange is a marketplace where advertisers and publishers come together to buy and sell ad space transparently and efficiently.
On the other hand, programmatic advertising is the automated buying and selling of digital advertising through a real-time bidding system (RTB). Programmatic advertising uses ad exchanges that allow advertisers to bid on advertising inventory, and whoever bids the highest price wins the ad placement, allowing the ad to be served to a target audience in real time.
In programmatic advertising, the buying and selling process is automated using algorithms and Machine Learning, which can analyze vast amounts of data to identify the best ad placement opportunities. This process makes programmatic advertising faster, more effective, and more accurate than traditional advertising methods.
AI Opportunities in Ad Exchange and Programmatic Advertising
AI has enormous potential for programmatic advertising. The vast majority of programmatic advertising platforms already use Artificial Intelligence and Machine Learning technologies to automate most processes and increase the accuracy of analytics data.
Here’s how AI can help programmatic advertising improve service delivery:
Ad placement and targeting optimization. AI can analyze huge amounts of data, such as browsing history and user behavior, to determine the most relevant and effective ads for a specific target audience. This leads to higher engagement and conversion rates.
Personalization of advertising content. AI can use data to personalize advertising content for each individual user, such as showing different products or messages based on their interests or viewing history. Such personalization leads to improved advertising effectiveness and increased involvement rates.
Automating the bidding process. AI can automate the bidding process, making it faster and more efficient. This leads to more accurate bids, more efficient use of ad budgets, and higher ROI.
Improved ad fraud detection and prevention. AI can analyze patterns and identify suspicious activities to prevent ad fraud. This leads to a safer and more reliable advertising environment for advertisers and publishers.
Providing real-time analytics and insights. AI can provide real-time analytics and insights into ad performance, allowing advertisers to make data-driven decisions and adjust their strategies on the fly.
How does it work?
It all sounds great in words, of course, but will it work in practice? Let’s take a look at a few examples of programmatic ads that have used AI technology:
ClickUp. ClickUp uses natural language processing AI to increase its blog traffic by 85%. Despite the many controversies over the use of AI in content creation, ClickUp’s approach to this issue is not just about using ChatGPT to write blog posts.
For example, ClickUp’s project management system uses various Artificial Intelligence tools, including Surfer SEO and Machine Learning technologies to:
- Identify opportunities for content optimization;
- Understand what keywords to use in articles (and how often);
- Create optimal article structure, including the number of images and length of subheadings.
BuzzFeed. BuzzFeed uses Artificial Intelligence to personalize content in quizzes. As one of the most popular content sites in the world, with more than 100 million monthly visitors, BuzzFeed is taking its first steps in automating content with AI.
However, the publisher has no intention of replacing human writers with robots. Instead, BuzzFeed is using OpenAI tools to create personalized content at a scale that would be unattainable without automation and Artificial Intelligence.
BuzzFeed’s CEO, Jonah Peretti, said the Artificial Intelligence approach helps “improve the quizbowl experience, informs our brainstorming, and personalizes our content for the audience”.
For example, one of the quizzes uses answers to seven questions to create a “new life” for the user.
Nestle. Nestle used AI to create their programmatic advertising campaigns for KitKat. So in 2023, as AI is getting more and more open to everyone, they let generative AI lead their latest campaign so they “could have a break”.
This is a great example of how AI can be used to improve ad creatives. Although in this case, it is more unusual and witty as it resonates with the main product positioning.
Some pretty generic briefs, such as: “Write KitKat ads the way Generation Z talks”, “Write KitKat ads about gamers”, and “Write KitKat ads about the latest trends”, generated some decent scripts. These scripts were used to query the image generator, which resulted in some “almost good” images.
The ads turned out to be fun and eye-catching.
Challenges and Limitations of Artificial Intelligence
Forbes says that more than 75% of consumers are concerned about misinformation from AI. It’s no secret that you can’t completely rely on the data ChatGPT provides since it may be outdated, inaccurate, or incorrect. AIs, although capable of processing huge amounts of data in a short period, are still imperfect tools.
Therefore, in this section, we would like to highlight a bit about the shortcomings of these systems:
Data quality. AI relies heavily on data to make decisions, and poor data quality can lead to inaccurate results. Advertisers need to make sure that the data used for AI analysis is accurate and reliable.
Algorithm bias. AI algorithms may be biased toward certain demographic groups due to inaccuracies in the ranking settings, which can lead to discriminatory advertising practices. Advertisers should be aware of these biases and take steps to prevent them.
Lack of transparency. Artificial Intelligence algorithms can be complex, and understanding how they make decisions can be difficult. Advertisers need to ensure that their AI models are transparent and can be tested to make sure the data is fair and accurate.
Ad fraud. While AI can help prevent ad fraud, it can also be used to commit fraud. Advertisers should be aware of these risks and take steps to avoid ad fraud.
Cost. Implementing AI in ad exchanges and programmatic advertising can be expensive, especially for smaller companies. Advertisers need to weigh the costs and benefits of using AI and make sure it is a cost-effective solution for their needs.
Regulatory challenges. There are growing concerns about data privacy and the use of AI in advertising. Advertisers need to comply with regulations such as the GDPR and CCPA to ensure the responsible and ethical use of AI.
Prospects for AI in Ad exchanges and programmatic advertising
AI and ML technologies are already actively used in programmatic advertising, and there is absolutely no reason for this direction of the industry to stop actively developing. Here are the programmatic advertising trends expected to grow the most in the coming years.
The adoption rate is expected to increase as more advertisers realize the benefits of using AI in ad exchange and programmatic advertising. According to a report by MarketsandMarkets, the global market for AI in advertising is expected to grow 29.79% from 2020 to 2025.
AI can help advertisers provide consumers with personalized and relevant ads. As AI technology continues to improve, we can expect even greater levels of personalization in programmatic advertising.
AI can help advertisers target ads to the right audience at the right time and through the right channels. As AI models improve, advertisers can expect to see more accurate targeting capabilities, leading to improved ad performance and ROI.
AI can help advertisers generate creative ideas and ad formats that resonate with consumers. We can expect to see more AI-powered creative solutions, such as ad text and design optimization tools, to help advertisers improve the effectiveness of their campaigns.
There is a growing awareness of the ethical and social implications of using AI in advertising. Advertisers are expected to approach AI more responsibly and ethically, ensuring their models are transparent, fair, and non-discriminatory.
AI will likely be integrated with other technologies, such as voice assistants and augmented reality, to create more immersive and engaging advertising experiences. This could help advertisers stand out in an increasingly crowded advertising landscape.
Development! Of course, we will only see more development in advertising, AI, and ML. They are interconnected and are likely to stretch each other as more and more technology emerges.
Artificial Intelligence has already shown its usefulness and relevance to our high-tech society, so even those who don’t like it will have to accept its existence and learn to take advantage of it.
Don’t be afraid of innovation, and don’t be afraid of the future; it will catch up with us sooner or later anyway because it is impossible to escape from what is already ahead of us. Don’t be afraid to use AI; it can make your life easier in many aspects of your life if you just put a little bit of effort into it.
About the Author
Roman Vrublivskyi, the CEO of SmartHub white-label programmatic solution. He started his career in 2016, and was focused on business development in Informational Technologies and SaaS industries. In 2019 he shifted his focus to enterprise-driven advertising technologies within SmartHub.