Tulia offers insight into Wayfair’s ML-driven decision-making processes, how they implement AI and ML for preventative problem-solving and predictive maintenance, and how they use data enrichment and customization to help customers navigate the inspirational (and sometimes overwhelming) world of home decor.
Wayfair uses AI and machine learning (ML) technology to interpret what its customers want, connect them with products nearby, and ensure that the products they see online look and feel the same as the ones that ultimately arrive in their homes. With a background in engineering and a passion for all things STEM, Wayfair’s Director of Machine Learning, Tulia Plumettaz, is an innate problem-solver.In this episode, she offers some insight into Wayfair’s ML-driven decision-making processes, how they implement AI and ML for preventative problem-solving and predictive maintenance, and how they use data enrichment and customization to help customers navigate the inspirational (and sometimes overwhelming) world of home decor. We also discuss the culture of experimentation at Wayfair and Tulia’s advice for those looking to build a career in machine learning.Key Points From This Episode:
Tweetables:“ a very broad field at the intersection between mathematics, computer science, and economics that to solve real-life applications.” — Tulia Plumettaz “All the decision making, from which channel should I bring you in to how do I bring you back if you’re taking your sweet time to make a decision to what we show you when you , it’s all -driven.” — Tulia Plumettaz “We want to be in a place , as early as possible, before problems are even exposed to our customers, we’re able to detect them.” — Tulia Plumettaz “We have the challenge of making you buy something that you would traditionally feel, sit , and touch virtually, from the comfort of your sofa. How do we do that? enrichment of information.” — Tulia Plumettaz “We knew that making it easier to navigate this very inspirational space was going to require customization.” — Tulia Plumettaz “At its core, it’s an exploit-and-explore process with a lot of hypothesis testing. Testing is at the core of being able to say: this new version is better than version.” — Tulia Plumettaz