Learn how AI and ML are transforming programmatic media buying, from real-time bidding to new formats and channels, from first-party data to ethics and responsibility.

AI and machine learning are revolutionizing traditional workflows. While machine learning has long been established, AI represents a more advanced leap, enhancing tasks like generating ad copy, offering optimization insights, creating interactive dashboards, and summarizing reports. In programmatic advertising, automation is crucial. Despite progress, many tasks such as campaign setup and creative uploads remain manual. Leveraging AI and ML to automate these processes is essential. Focus should be on optimization, dedicating most of your time to in-depth analysis to efficiently meet client goals.

AI and ML revolutionize programmatic buying by enhancing targeting, real-time optimization, and predictive analytics. They enable dynamic creative optimization, automated buying, and fraud detection, ensuring ads reach the right audience efficiently. Personalization and advanced analytics improve engagement and ROI, while voice and visual search integration opens new channels. These technologies make advertising more precise, effective, and responsive, driving better results for advertisers and delivering more relevant experiences to consumers.

Last updated on Nov 8, 2024

How will AI and machine learning shape the future of programmatic media buying?

Programmatic media buying is the automated process of purchasing and placing digital ads across various platforms and channels, using data and algorithms to optimize performance and efficiency. It has revolutionized the online advertising industry, allowing marketers to reach their target audiences with more precision, speed, and scale than ever before. But how will the advances in artificial intelligence (AI) and machine learning (ML) shape the future of programmatic media buying? In this article, we will explore some of the key trends and implications of AI and ML for programmatic media buying, and what they mean for advertisers, publishers, and consumers.

1 The rise of real-time bidding

One of the main drivers of programmatic media buying is real-time bidding (RTB), which is a type of auction that allows advertisers to bid on individual ad impressions in milliseconds, based on the user's profile, behavior, and context. RTB enables advertisers to optimize their campaigns and budgets in real time, and to access a wide range of inventory across different platforms and devices. AI and ML are essential for RTB, as they enable the analysis of massive amounts of data, the creation of dynamic and personalized ads, and the prediction of user responses and outcomes. AI and ML also help to improve the quality and transparency of the RTB ecosystem, by detecting and preventing fraud, ensuring brand safety, and enhancing user privacy.

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2 The emergence of new formats and channels

Another trend that is shaping the future of programmatic media buying is the emergence of new formats and channels that offer more engaging and immersive experiences for users, such as video, audio, social, mobile, connected TV, and augmented reality. These formats and channels require more sophisticated and creative strategies and solutions from advertisers, who need to adapt their messages and designs to different screens, contexts, and preferences. AI and ML can help advertisers to create and deliver more relevant and effective ads, by using natural language processing, computer vision, voice recognition, and sentiment analysis. AI and ML can also help advertisers to measure and optimize their performance across different formats and channels, by using attribution models, cross-device tracking, and multi-touchpoint analysis.

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3 The shift to first-party data

A third trend that is influencing the future of programmatic media buying is the shift to first-party data, which is the data that is collected and owned by the advertiser or the publisher, such as website visits, app usage, purchase history, or loyalty programs. First-party data is becoming more valuable and important for programmatic media buying, as it provides more accurate and reliable insights into the user's identity, behavior, and preferences, and as it enables more compliance with the increasing regulations and restrictions on third-party data, such as cookies, identifiers, or consent. AI and ML can help advertisers and publishers to leverage their first-party data more effectively, by using data management platforms, customer data platforms, or data clean rooms. AI and ML can also help advertisers and publishers to enrich their first-party data with other sources, such as second-party data, contextual data, or synthetic data.

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4 The challenge of ethics and responsibility

A final trend that is impacting the future of programmatic media buying is the challenge of ethics and responsibility, which refers to the ethical and social implications of using AI and ML for programmatic media buying, such as the potential risks of bias, discrimination, manipulation, or harm. Ethics and responsibility are becoming more critical and relevant for programmatic media buying, as they affect the trust and reputation of the advertisers, publishers, and platforms, as well as the rights and expectations of the users and the society. AI and ML can help to address some of the ethical and social issues of programmatic media buying, by using principles, frameworks, and tools that promote fairness, accountability, transparency, and explainability. AI and ML can also help to foster a more ethical and responsible culture and practice of programmatic media buying, by involving diverse and inclusive stakeholders, engaging in dialogue and consultation, and adhering to codes and standards.

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Nikhil Kumar

Digital Marketer | Programmatic | Business Analytics Enthusiast | People Management
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AI and machine learning are revolutionizing traditional workflows. While machine learning has long been established, AI represents a more advanced leap, enhancing tasks like generating ad copy, offering optimization insights, creating interactive dashboards, and summarizing reports. In programmatic advertising, automation is crucial. Despite progress, many tasks such as campaign setup and creative uploads remain manual. Leveraging AI and ML to automate these processes is essential. Focus should be on optimization, dedicating most of your time to in-depth analysis to efficiently meet client goals.

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Seth Maloney

Data, Tech, Fun
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Without stogaps and human review it can take very few leaps for AI- and ML-based bidding and media buying to place ads in insensitive areas which drive down brand value and, more importantly, create harm to the audience. If an ethical framework is not placed front and center the harm caused by ad targeting can and will set an otherwise promising future for ad tech back years

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Saksham Arora

Regional Senior Manager | Digital Marketing
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AI and ML revolutionize programmatic buying by enhancing targeting, real-time optimization, and predictive analytics. They enable dynamic creative optimization, automated buying, and fraud detection, ensuring ads reach the right audience efficiently. Personalization and advanced analytics improve engagement and ROI, while voice and visual search integration opens new channels. These technologies make advertising more precise, effective, and responsive, driving better results for advertisers and delivering more relevant experiences to consumers.

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Dhairyashil Charane

Ad.Tech Professional | Programmatic Advertising | M&C Saatchi Performance | Ex-GroupM
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AI models are highly effective in identifying patterns of fraudulent activity. Machine learning can detect bots and invalid traffic early on, protecting advertisers from wasted spend and ensuring that ads are only shown to genuine audiences.

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How will AI and machine learning shape the future of programmatic media buying?

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1 The rise of real-time bidding

2 The emergence of new formats and channels

3 The shift to first-party data

4 The challenge of ethics and responsibility

5 Here’s what else to consider

Programmatic Media Buying

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