AI was meant to make marketing sharper and faster - better targeting, better personalisation, quicker decisions. But for many marketing teams, the results are still falling short of the ambition.
The problem is rarely the AI itself. It is the customer data beneath it: fragmented identities, inconsistent consent, disconnected platforms and multiple versions of the truth. These are not new challenges, but AI is making them much harder to ignore. Without trusted, connected data, even the most advanced technology will struggle to deliver reliable outcomes.
In this webinar, we will be joined by Melinda Carter, Head of Customer Data & Engineering at Hearst UK, who will share candid accounts of how they are addressing these challenges in practice. She will discuss where they started, the barriers they encountered and how they built support across the business while continuing to demonstrate value, rather than waiting for a perfect data environment.
Head of Customer Data & Engineering, Hearst UK
Responsible for Hearst UK’s customer data, spanning analytics, data platforms, and engineering. This includes ownership of our customer data platform, data architecture and engineering roadmap, as well as managing our external engineering partners to deliver reliable data products.
VP, UK Data Practice Lead, Merkle
Responsible for designing, delivering, and scaling modern data and engineering solutions for clients across retail, travel, finance, transport, and entertainment. My role spans strategy, engineering, and execution; ensuring data & engineering foundations are fit for AI, customer experience, and long-term business value.
