Agentic Personalisation of Cross-Channel Marketing Experiences
June 19, 2025 Β· Declared Dead Β· π ACM Conference on Recommender Systems
"No code URL or promise found in abstract"
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Authors
Sami Abboud, Eleanor Hanna, Olivier Jeunen, Vineesha Raheja, Schaun Wheeler
arXiv ID
2506.16429
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.IR,
cs.LG
Citations
3
Venue
ACM Conference on Recommender Systems
Last Checked
4 months ago
Abstract
Consumer applications provide ample opportunities to surface and communicate various forms of content to users. From promotional campaigns for new features or subscriptions, to evergreen nudges for engagement, or personalised recommendations; across e-mails, push notifications, and in-app surfaces. The conventional approach to orchestration for communication relies heavily on labour-intensive manual marketer work, and inhibits effective personalisation of content, timing, frequency, and copy-writing. We formulate this task under a sequential decision-making framework, where we aim to optimise a modular decision-making policy that maximises incremental engagement for any funnel event. Our approach leverages a Difference-in-Differences design for Individual Treatment Effect estimation, and Thompson sampling to balance the explore-exploit trade-off. We present results from a multi-service application, where our methodology has resulted in significant increases to a variety of goal events across several product features, and is currently deployed across 150 million users.
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