Programmatic advertising: Is the death of targeted advertising near?

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  Quantumrun Foresight
• October 9, 2023

Insight summary

Programmatic advertising automates the digital ad buying process, using machine learning and AI for quick and targeted placements. Despite its rapid growth and high spending—reaching $14.9 billion globally—there's a gap in understanding among those who use it, making it a sort of technological "black box." Consumer privacy concerns are affecting its expansion, leading companies like Apple and Google to limit data tracking. Implications include the potential for increased societal division through targeted ads, challenges around data privacy, shifts in advertising strategies, and a rise in regulation.

Programmatic advertising context

Programmatic advertising is the automated process of bidding and positioning ads on a designated platform. Traditional ad placement involves a lengthy and intricate bargaining procedure, bidding, proposals, and contracts. Conversely, PA simplifies the process into a matter of seconds by implementing machine learning and artificial intelligence (ML/AI) to manage the buying and positioning of digital ads.

According to a 2021 study published in Computers in Human Behavior journal, by utilizing the "digital footprint" of web users through cookies to locate audiences and distribute ads to them, PA has amassed spending of USD 1.1 billion in the UK alone and approximately USD 14.9 billion globally. In 2015, almost half of all digital advertisements were traded programmatically, with forecasts indicating that this figure will rise to over 80 percent in the mid-term. Additionally, new forms of media and industries are venturing into the programmatic arena, such as loyalty programs, apps, gaming, film, and television.

Despite the swift expansion of programmatic advertising, there is a significant discrepancy between its growth and the proficiency, knowledge, and understanding of those who utilize it. The speed of its development and capabilities and its technical intricacy have proven to be daunting and uninviting for many. As a result, PA is still viewed as a "black box" of technologies. 

Disruptive impact

One of the main challenges of PA is the privacy concerns of consumers. With the increasing number of data breaches and the growing awareness of using cookies to track online behavior, consumers have become more skeptical about sharing their data with companies. This trend has increased the demand for transparency and control over personal data. Consequently, companies are facing challenges in their efforts to collect and use customer data for advertising purposes.

In response to consumer privacy concerns, major tech companies like Apple and Google have introduced features that limit the use of cookies on their devices and operating systems. For example, Apple's Intelligent Tracking Prevention (ITP) and Google's Privacy Sandbox aim to protect users' privacy by reducing the amount of data shared with advertisers. Google has also announced that it plans to discontinue third-party cookies by the end of 2024, which has raised concerns among advertisers about the future of targeted advertising.

To address these challenges, companies may need to adopt alternative advertising strategies. One such approach is to leverage AI/ML technologies to deliver personalized advertising without relying on cookies. By analyzing large volumes of data from various sources, AI/ML can help marketers identify patterns and trends that can be used to predict customer behavior and preferences. 

Implications of programmatic advertising

Wider implications of programmatic advertising may include: 

• A divide between groups based on socioeconomic status, race, religion, and other factors, as certain groups are targeted more frequently than others. Additionally, PA may contribute to spreading fake news, as it can target audiences based on their interests and beliefs.


• More sophisticated and efficient advertising strategies, but also more concerns about privacy and data protection.


• Increased polarization and division, as political groups can target specific audiences with tailored messaging that reinforces their beliefs.


• As more businesses adopt PA, it can lead to increased energy consumption and carbon emissions due to the increasing reliance on data centers.


• The automation of many advertising tasks, such as ad placement and optimization. 


• Increased regulation and potential limitations on how advertisers can use consumer data.


• Increased cross-border advertising campaigns and potential cultural clashes as different groups are exposed to different advertising messages.

Questions to consider

• If you work in marketing or digital strategy, how is your company preparing for the loss of cookies?


• How can the advertising agency create campaigns that are effective and ethical?