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Aislinn
Mallon
Head of CRM, Engagement
The Guardian
Aislinn has been working in CRM marketing for the past 15 years, with experience at brands such as Marks and Spencer, Photobox, and now the Guardian. Over that time, she has developed a passion for using data and insight to craft campaigns and experiences that truly feel personal. Aislinn believe great marketing is part science, part storytelling, and I’m fortunate to work in a space where both get to shine. When I’m not deep in CRM strategy, you’ll find Aislinn with a coffee in hand, reading a book, planning my next trip, or heading to a gig. She's happiest when I’m out in nature, so chat to her at the summit if you have any recommendations for good hiking spots around London.
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03 December 2025 12:05 - 12:35
Fireside chat - From brand to bottom line: How The Guardian rebuilt CRM for a data-driven future
When The Guardian’s CRM team began its transformation, it was a small, brand-led function with limited martech infrastructure and a shrinking contactable base. Fast forward to 2025, and that same team is now a core revenue engine—powering engagement, retention, and subscriptions through a scalable first-party data strategy. In this fireside conversation, you'll hear directly from the Heads of CRM Revenue and Engagement at The Guardian as they unpack how they redefined CRM from the ground up. You’ll learn how they tackled permissions and privacy challenges, broadened communication scope, and successfully onboarded a CDP to activate data in smarter, more targeted ways. Whether you’re starting with a lean team or navigating cross-functional constraints, this session offers a practical blueprint for building a more agile and impactful CRM strategy. Key takeaways include: - How to evolve from a brand-focused CRM model to one that directly drives revenue - What it really takes to activate first-party data—ethically and at scale - Lessons from implementing a CDP and reworking comms permissions - How to structure a small team for high-impact collaboration across marketing, data, and product