Header Bidding allows publishers to increase their ad revenue in programmatic trading, but its management and optimisation is complex. Selecting the right partners, optimising pricing strategies, and managing technical settings require continuous work and expertise. Simply monitoring performance is insufficient – data must be translated into meaningful insights and better decisions. This is where artificial intelligence (AI) can be a significant help, providing real-time analysis and recommendations that assist publishers in making better decisions.
The Most Common Challenges of Header Bidding for Publishers
While Header Bidding increases competition and enables better ad revenue, its management can also bring challenges:
- Technical complexity: Implementing Prebid and Header Bidding requires adding JavaScript code to the website’s header. The system must function seamlessly with different ad partners, which requires ongoing maintenance.
- Increased page load times: The simultaneous participation of multiple partners in the auction can slow down page loading times. Each additional partner adds extra JavaScript requests, which can impact the user experience.
- Data management challenges: The Header Bidding process generates vast amounts of data from different sources, such as SSPs and ad networks. Combining and analysing this data to get a comprehensive overview can be difficult, leading to inefficiencies in ad inventory management.
How AI Helps Simplify Header Bidding Management and Optimisation
AI can help publishers make Header Bidding more manageable and profitable. AI can analyze massive datasets in real time and provide solutions to questions such as:
Are there technical conflicts in the auction process? – AI can detect potential issues, such as misconfigured SSPs, missing Prebid modules, or performance challenges.
How can I reduce page load times without impacting ad revenue? – AI can analyse ad loading times and suggest solutions, such as implementing lazy loading or server-side implementation.
How do different SSPs affect auction performance? – AI can compare different SSPs' latency and fill rates, recommending which partners generate the best results.
An AI assistant speeds up analysis and reduces the need for manual data processing, allowing teams to focus on decision-making rather than just reviewing reports.
How Relevant Yield and Relevant AI Help Manage Header Bidding and Optimise Performance?
Many publishers use various tools to manage header bidding and optimise performance. One option is Relevant Yield’s HB Manager, which simplifies the implementation and management of Prebid across both websites and apps. In addition to management, Relevant Yield’s HB Analytics module provides real-time analytics for monitoring Header Bidding performance. In practice, optimisations can be made directly in HB Manager, and their effects can be tracked in the HB Analytics module.
The system is complemented by Relevant AI, an integrated assistant utilising Header Bidding implementation and data to identify technical challenges and suggest solutions. Additionally, it has a vast knowledge base, enabling it to answer even more technical "how-to" questions. AI can, for example, detect misconfigured SSPs, identify performance issues, and provide optimisation recommendations. It speeds up decision-making with natural language processing – users can directly ask about auction efficiency or factors affecting performance, and AI provides answers in seconds without manually going through reports.
AI is an intelligent additional layer, directly bringing AI-driven insights into the Relevant Yield platform, streamlining decision-making and optimisation. This enables more agile management, faster optimisation cycles, and ultimately, better revenue for publishers.
The Best Partner for Managing Header Bidding
AI assistants do not replace experts but enhance their ability to utilise data and discover new opportunities. AI not only analyses data but also makes it more understandable and actionable. Relevant AI enables faster decision-making, reduces manual work, and brings AI-powered insights directly into the Relevant Yield platform. This means more agile management, faster optimisation cycles, and ultimately, higher ad revenue for publishers.
The efficiency of Header Bidding relies on fast decision-making and optimised trading – and AI makes both even better.