Beyond Ad Space: How AI and First-Party Data are Redefining Publisher Revenue

For many modern media organizations, a frustrating paradox exists: they possess strong journalism, reputable brands, and loyal audiences, yet winning advertising revenue feels harder than ever. The challenge is no longer about producing high-quality content or driving raw traffic; it’s about converting audience trust and data into measurable business value.

At the WAN-IFRA Digital Media Asia conference in Manila, Anson Mok, Head of Data Development at United Daily News Group (UDN Group), outlined a strategic shift in how publishers must approach the AI era. For UDN Group, a media organization founded in 1951, AI has evolved from a technological experiment into a core commercial strategy. The goal is simple: move away from selling passive ad space and start delivering actionable business outcomes.

The Shift from Inventory to Insight

For decades, the publishing industry operated on an inventory-based model, selling ad placements based on volume. However, the advertising landscape has become increasingly performance-driven. Today’s advertisers demand precision, accountability, and speed, meaning that simply owning a “slot” on a webpage is no longer a sufficient value proposition.

Mok argues that true value now stems from insight, relevance, and a deep understanding of the audience. By repositioning data and AI as active growth drivers, UDN Group has shifted its focus toward delivering measurable commercial results. This approach has yielded significant performance gains; the company reported that targeted AI-supported advertising campaigns achieved click-through rates more than 230% higher than regular placements.

Between 2023 and 2025, this strategy saw significant adoption growth, with the company executing thousands of advertising cases across more than 136 different industry categories.

Humanizing Data: Moving Beyond Demographics

A critical component of this transformation is how publishers perceive their audience. Rather than viewing readers as mere impressions or data points, UDN Group treats them as people with complex behaviors, routines, and interests.

By utilizing first-party and zero-party data, publishers can build deeper profiles that go beyond basic demographics. Understanding the context of a user’s life—such as their shopping habits, travel interests, or lifestyle preferences—allows for more meaningful commercial strategies. For example:

• Fitness Campaigns: Analysis helps advertisers prioritize educational content and user retention.
• Apparel and Eyewear: AI identifies specific lifestyle scenarios that resonate most strongly with consumers.

In this model, audience understanding ceases to be just “editorial intelligence” and becomes “commercial infrastructure.”

The Four Pillars of AI Integration

To operationalize this vision, UDN Group organizes its AI strategy into four distinct functional areas. Each serves a specific purpose in the value chain, ensuring that technology supports business outcomes rather than existing for its own sake.

1. Interpretive AI

This layer focuses on analyzing fragmented audience behavior to identify meaningful patterns that would be invisible to human analysts.

2. Predictive AI

Predictive tools estimate audience responses and campaign performance, enabling advertisers to allocate their budgets more effectively and reduce waste.

3. Generative AI

Generative tools are used to increase operational speed, supporting knowledge organization, content planning, and the development of advertising proposals.

4. Agentic AI

Unlike generative AI, which focuses on content, agentic AI coordinates actions and workflows across different teams to streamline execution.

From Vendor to Strategic Partner

The ultimate goal of integrating AI and data is a fundamental change in the publisher’s role within the advertising ecosystem. Publishers must stop acting as vendors who sell ad space and start acting as long-term strategic partners for brands.

This shift requires building deep confidence with advertisers. Publishers must prove they can optimize campaigns intelligently and deliver results tied to clear outcomes. UDN Group achieves this by connecting audience signals across its entire ecosystem—including websites, apps, newsletters, and customer databases—to create a unified advertising infrastructure.

“Transformation is never about technology,” says Anson Mok. “It’s about people, mindset, and whether an organisation is truly ready to change.”

Key Takeaways for Modern Publishers

• Prioritize Outcomes over Inventory: Stop selling “space” and start selling measurable business results and audience insights.
• Leverage First-Party Data: Use zero-party and first-party data to understand user lifestyle and behavior, moving beyond basic demographics.
• Implement a Tiered AI Strategy: Use Interpretive, Predictive, Generative, and Agentic AI to handle different parts of the commercial and operational workflow.
• Focus on Connectivity: Success in the AI era depends on the ability to link trust with intelligence and insight with execution.

As the industry evolves, the publishers who survive and thrive will not be those with the most scale, but those with the best ability to connect. By linking audience trust with commercial intelligence, media organizations can reclaim their value in the AI-driven economy.