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Ad Operations

Revolutionizing Ad Operations: Harnessing the Power of AI for Publishers

Learn about prompt engineering's role in maximizing AI's potential, leveraging GitHub CoPilot for coding efficiency, and harnessing ChatGPT's data analysis capabilities for header bidding and GAM.

Josh Robins
Apr 3, 2024

Publishers constantly seek ways to optimize their ad operations for increased efficiency and revenue. Although integrating artificial intelligence (AI) into ad operations is still in its early stages, it’s proving to be a game-changer.

In this blog post, we'll dive into how publishers can use AI to transform their ad operations, focusing on prompt engineering, utilizing GitHub CoPilot for enhanced coding productivity, and tapping into the capabilities of ChatGPT for insightful data analysis for header bidding & GAM.

The Importance of Prompt Engineering

Prompt engineering is the foundation of effective AI utilization, enabling publishers to harness the full potential of AI models. At Aditude, we understand that crafting precise and relevant prompts is crucial for obtaining accurate and valuable insights. By formulating well-structured prompts, publishers can guide AI models to generate meaningful responses catering to their needs.

Regarding ad operations, ChatGPT allows publishers to ask nuanced questions about their advertising strategies, auction dynamics, and revenue metrics. 

“You are to act as an Ad operations Expert specializing in header bidding and display ads. I will pose questions to you regarding increasing various metrics. You are to provide actionable A/B tests that I will be able to implement.”

The above prompt will give the model contextual information, enabling it to generate responses from more relevant information in ad ops rather than answering the question broadly from all of its knowledge. Without this context, the model may give you answers about optimization concerning other fields, such as SEO or broader page performance.

Automating Manual Processes in Ad Ops

AI excels at automating repetitive and time-consuming tasks, and ad ops is no exception. Header bidding and Google Ad Manager (GAM) are integral components of a publisher's revenue optimization strategy, and automating manual processes in these areas can significantly enhance efficiency.

AI-driven algorithms can analyze vast datasets and identify patterns, leading to more effective monetization. By automating the auction optimization process, publishers can maximize revenue while minimizing operational overhead.

GitHub CoPilot: A Coding Productivity Revolution

Coding is at the core of ad operations, and we know that publishers always look for ways to boost coding productivity. GitHub CoPilot, powered by AI, is a groundbreaking tool that can revolutionize the coding experience. By assisting developers in writing code snippets and suggesting entire functions, CoPilot accelerates the development process, reducing coding errors and enhancing overall productivity.

What sets it apart is that it’s predictive of your codebase and trained on your data. Translate your comments into code: “Can you write me a snippet that takes an ad slot and tracks the viewability in the console?” Write out all your steps in the comments, and Github can help you devise a solution—this pairs programming with AI. 

At Aditude, we recognize the importance of efficient coding practices in ad operations. Implementing GitHub CoPilot can save valuable time, allowing developers to focus on more strategic aspects of ad optimization. Whether it's automating the creation of line items or ad targeting, CoPilot can be a valuable ally in the coding journey.

ChatGPT for In-Depth Data Analysis

If coding is at the core of ad ops, data is the backbone. Publishers generate billions of data points daily. Analyzing this data manually can be overwhelming and time-consuming. ChatGPT, amongst other models, with its natural language processing capabilities, offers a novel approach to data analysis by allowing publishers to ask questions in plain English.

By interfacing with ChatGPT and other AI models, publishers can inquire about specific data points, trends, or anomalies in their ad revenue data. For example, asking questions like "Can you provide some variables that might be worth split testing from this ad unit level data (CSV)?"

The expected output from ChatGPT and other models could suggest you test lazy loading by ad unit as your next optimization task.


Integrating AI into ad operations streamlines processes and unlocks new possibilities for revenue optimization and strategic decision-making. At Aditude, we advocate for the thoughtful implementation of AI tools such as ChatGPT, GitHub CoPilot, and business intelligence to empower publishers in their quest for improved ad revenue generation.

Publishers can position themselves at the forefront of innovation by embracing prompt engineering, using GitHub CoPilot for coding productivity, and utilizing ChatGPT for data analysis.

As the industry continues to evolve, collaboration between publishers and AI technologies will undoubtedly shape the future of ad operations. I think it's important to note that AI is as powerful as it is today, but with how fast it’s improving, it's essential to pay attention to the upgrades that come out to improve continuously.

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