The Digital Advertising Revolution: How Artificial Intelligence Is Changing the Game

Artificial intelligence (AI) plays a key role in industries of all kinds, and naturally, digital marketing is one of them. AI is one of the biggest technological advances currently influencing media planning, buying, and selling, and it could be said to be the most important innovation shaping the industry landscape. 

Many marketing specialists use AI technology to expand their marketing teams or perform technical tasks, as these AI methods can streamline and amplify human effort. The use cases of AI advertising cover from data analysis to real-time personalization, making it an exceptional tool to execute more comprehensive campaigns.

AI is not a science fiction prophecy for the future: it is happening now, and understanding the role it plays is critical for those who want to stay informed about market evolution. Companies that are prepared to adopt AI will see how it benefits their operations, while those that do not risk falling behind. 

Origins and Evolution of AI in Advertising

The first significant use of IA came in 2013 when it emerged as a tool for content organization. The following year, its uses expanded into advertising, aiding decision-making and reducing part of the labor involved in buying, selling, and placing ads on platforms. By 2015, AI was determining user intent from search results, and in 2016, it entered voice recognition and virtual assistants.

The reality is that in the beginning, AI and Paid Media Specialists were separate, with advertising platforms demanding control and specialists carrying out hundreds of tests to verify if the algorithm’s results were reliable. Errors arose due to limited algorithm learning, which allocated more effort to audiences that may not have worked as well as others. This is where the role of the Paid Media Specialist had to re-shape to understand and interpret the best results to scale them.

Today, things are different. A much more digital society and much more experienced algorithms have made the alliance between AI and media buying managers possible. This major change has led to a reconsideration and reorientation of time and effort in tasks.

Programmatic media advertising was one of the first areas to adopt AI as a tool to make the buying and selling of digital advertising more efficient, allowing advertisers and publishers to optimize their investments in digital advertising in real-time.

Other areas of digital marketing started doing the same. For example, chatbots and virtual assistants use natural language processing (NLP) techniques to understand human language and respond to user questions. Personalization and remarketing also use AI techniques to adapt advertising messages to individual consumer preferences and needs.

Now, we are seeing a greater operational workload by Artificial Intelligence to detect new opportunities based on its knowledge and experience, while the Media Buyers focus more on interpreting this data, scaling, and the strategic and creative part of the media plan.

Changes brought by AI in Advertising

But what are the specific and decisive changes that AI has introduced in how we advertise in digital media? Check some of them below:

• Segmentation: At the beginning of self-serve platforms it was essential to define in a very detailed manner who we wanted to target, using up to 4 exclusions so that the system would understand it. Today, AI-driven platforms leverage learning algorithms and big data for a more open segmentation approach, requiring fewer interests for precise targeting.
• Performance: With the arrival of AI, platforms require a minimum number of conversions (e.g., 50 weekly) for the algorithm to have sufficient learning to optimize campaigns in the best possible way. This enables the platform’s intelligence to understand which bids to place in order to reduce CPL (Cost Per Lead) and achieve the expected CPA (Cost Per Acquisition) goals.
• Ads: Previously, separate campaigns or ad groups were created for each ad to have total control over their performance. Now, modern platforms recommend having at least 5 ads in a campaign to increase the conversion rate and allow the platform to identify the winning ad for optimization.
• Media: The algorithms of platforms like Meta, Google, and TikTok have greatly improved thanks to the massive amount of data they receive per minute and the work of AI to understand it. Nowadays, these tools constantly seek to make the work of advertisers easier and to find better results more easily. 
• Reporting: Modern platforms use AI to generate detailed and personalized reports on campaign performance, allowing advertisers to obtain valuable information about return on investment and adjust their strategy accordingly. In addition, automatic rules can be created to be activated or deactivated based on specific parameters. They also generate alerts and recommendations automatically. 
• Insights: Artificial intelligence can help advertisers obtain useful information about their audience, such as demographic data, interests, and purchasing behavior, which allows the creation of more effective messages for each segment. AI tools also aid in finding the best audiences and enable real-time testing for optimal results.
• New formats: AI is driving the creation of new advertising formats, such as augmented reality ads and voice ads. Moreover, it is becoming increasingly common to provide the platform with multiple assets so that it can find the best possible combination among them to maximize results. Nowadays, you can apply automatic enhancements that show different versions of ads based on the interpretation of each user to whom they are displayed. For example, in Meta, some enhancements can be enabled, such as 3D animation, adding music, and automatic image retouching. 
• Chat GPT: AI-powered chatbots can help advertisers interact with their audience in a more personalized and effective manner, understanding natural language and responding to consumers’ questions and needs. They can also engage effectively, create conversion events, and generate assets and copies for campaigns, making the advertising process more efficient and impactful.

In an increasingly cookieless digital world, it is essential for advertisers to find new ways to measure campaign performance. AI helps gather and analyze diverse data sources, providing valuable insights, and platforms like Meta and Google offer cookie-independent measurement solutions (e.g., CAPI, Offline Conversions), ensuring accurate campaign assessment. Adapting to this cookieless era and embracing innovative measurement methods are vital for successful advertising in today’s digital landscape.

Pros and Cons of using AI to manage digital media campaigns

AI has not only brought advantages in the management of digital media campaigns, but, like any tool, it carries risks. Here are some pros and cons:

Pros: 

• Fast and Accurate Data Processing: AI can quickly and accurately process large amounts of data and use that information to optimize digital media campaigns. 
• Improved Efficiency: AI can help identify patterns and trends in data and use that information to improve the efficiency and effectiveness of digital media campaigns. 
• Time and effort savings: AI can make decisions and perform tasks autonomously, allowing humans to dedicate their time and effort to other important tasks. 
• Increased productivity: The time and effort savings results in increased productivity. AI can automate many of the small tasks involved in the overall sales process. 
• Budget optimization: The final outcome is important for all businesses, including those in the advertising market. The use of AI can help companies make smarter budget decisions, ensuring optimal results with the least possible expense. 
• User Understanding: Thanks to AI, entire gigabytes of data can be analyzed in seconds, and through dynamic ads, allows for a more personalized and objective match based on the prospect and the product offered by the company.

Cons:

• Lack of contextual understanding: AI may lack the contextual understanding and empathy needed to fully understand the needs and preferences of customers. 
• Data Quality Dependency: The accuracy and effectiveness of AI largely depends on the quality of the input data, so it is important to ensure that the data is accurate and complete. 
• Lack of creativity: AI is based on patterns and trends, so it may lack the creativity and unconventional thinking needed to identify innovative solutions to complex problems.

Balancing AI in a transformed digital media management world

Artificial intelligence can be very useful for managing digital media campaigns as it can perform tasks quickly and accurately. However, it is important to remember that AI can never fully replace human skills in terms of business objectives and overall insight detection. AI is just a tool, and therefore it is important for marketing professionals to use their knowledge and skills to guide and supervise its use. AI cannot replace human creativity and innovation, which are crucial for the long-term success of any marketing campaign.

Both artificial intelligence and human ability are complementary to each other to maximize results. AI is not the future; it is the present and a valuable tool to support the management of digital media campaigns, but it should not be seen as a single and definitive solution.

At Globant, our media buying and digital marketing specialists focus on maximizing the available resources to achieve each client’s goals. This includes the use of tools such as real-time reports and customized dashboards, as well as the creation of communication pieces that are backed by specific insights about the target audience. We strive to stay updated on the latest trends and technologies to effectively and efficiently plan each media campaign.