DoorDash’s Consumer Packaged Goods (CPG) business spans groceries, retail products, alcohol, electronics, pharmaceuticals, and more.
Tag Archives: Conferences and Research Papers
Smarter promotions with causal machine learning
In August 2025 at the KDD AI Conference in Toronto, Canada, we presented our published research, “Causal Machine Learning for Promotions: Industry Evidence and Applications.” In this paper, we describe a two-stage framework for improving promotion efficiency through causal machine learning – first by estimating each customer’s true response to different offers, and then by optimizing which promotions to deliver under practical business constraints.
Mind the Gap: Using LLMs to bridge behavioral silos in multi-vertical recommendations
A recap of our RecSys 2025 Paper: “Mind the Gap: Using LLMs to Bridge Behavioral Silos in Multi-Vertical Recommendations”
As DoorDash expands into more verticals, we see “behavioral silos”: most customers have a deep history in only a few categories.
Bridging Affordability, Familiarity, and Novelty: DoorDash’s LLM-assisted personalization framework
A recap of our KDD 2025 PARIS Workshop talk: “Affordability, Familiarity, and Novelty: An LLM-assisted Personalization Framework for Multi-Vertical Retail Discovery.”
Imagine a world where every shopping moment, from a last-minute grocery run to a weekend gifting spree, feels effortless, personalized, and just right for you.
Unleashing the power of large language models at DoorDash for a seamless shopping adventure
Photo: Courtesy of The AI Conference
Imagine a bustling marketplace where consumers seamlessly connect with local merchants to get everything from groceries to gifts delivered to their doorsteps.