This article is co-authored by Trevor LaViale, Machine Learning Solutions Engineer at Arize AI

Wayfair is a company that believes growth is built on a strong global presence. Localization is a key element in successfully establishing ourselves in many markets and achieving the desired growth.

Wayfair brings products to life through digitally created imagery enabled by ML/AI sciences. Over the last several years, we’ve been investing in building 3D capabilities to achieve this at both a scale and cost not possible with traditional photography. Creation of these 3D renders requires significant computation (rendering) capabilities. In May 2022, Wayfair embarked on a Public Cloud Tech transformation journey from our own on-premise data center to the Google Cloud (GCP) which significantly added to our GCP operating costs.

“Griffin” learns from millions of customer interactions daily to continuously improve customer experience and engagement.

Last month I attended the Zinnov Confluence – India Edition. For anyone not familiar with the event, it delivers a forum for global brands to share their experiences and perspectives around disruptive technologies, new digital business models, and leadership paradigms that can help bring India’s incredible technology ecosystem into the global community.

I recently had the pleasure of speaking at Transform 2023 in San Francisco, an event dedicated solely to an innovation that has taken the industry by storm, Generative AI. It was a great event that attracted speakers from a variety of iconic brands, including Google, Johnson & Johnson, Walmart, Fidelity Investments, eBay, FedEx Dataworks, McDonald's Corp, Intel, and the list goes on.

As a scientist at Wayfair, Sachin Chhabra is helping fulfill the company’s mission of enabling customers to create their own sense of home. To this end, Chhabra utilizes state of the art machine learning techniques to surface relevant product recommendations to customers.

We recently celebrated International Women’s Month. What does this mean to you? How did you celebrate it?

One of our missions at Wayfair is to help our 22 million customers find the products they are looking for. For example, when a customer searches for a “modern yellow sofa” on Wayfair, we want to show the most relevant options from the tens of thousands of sofas available in our catalog. To do that, it is important to have a strong understanding of the products we sell. We use machine learning algorithms to analyze and understand the descriptive information (e.g. color, shape) of over 40 million products provided by more than 20 thousand suppliers in our catalog.

How Wayfair leverages Graph Neural Networks to thwart account-hopping fraudsters

Last week I participated on a panel at the Milken Institute Global Conference. It was a fantastic event featuring more than 200 sessions, including mine, “Retail Renaissance: Businesses Embracing Technology, Sustainability, and Innovation.”

In early April, Wayfair introduced the Digital Design Studio in our AllModern Dedham store. The Digital Design Studio (DDS) is a photorealistic interactive experience that lets customers explore Wayfair’s endless catalog by designing 3D furniture arrangements with product cards. Creating this tool was a collaborative effort between Wayfair Next (our R&D group tasked with exploring various emerging tech use cases), Physical Retail, Visual Merchandising, Creative, 3D, and many other Wayfair teams.

Geo experimentation unlocks incrementality testing when customer-level experimentation is not possible.

How to make deliveries faster without touching any packages

Let’s look at how we at Wayfair use custom embedding models to capture complex customer behavior patterns for advanced Fraud prevention.

Search relevance – the relationship between users’ queries and the products returned in search results – is one of the most important performance indicators for ecommerce storefronts. However, the sheer volume of the data makes evaluating and improving search relevance a difficult proposition. To give just one example, the Wayfair catalog has millions of products, which makes it difficult to create relevance-focused evaluation datasets manually.

Dive into the ways Wayfair’s data scientists are using Vertex AI to improve model productionization, serving, and operational readiness velocity.

Wayfair works with over 25,000 suppliers to sell more than 30 million products in a variety of styles from classic to contemporary at compelling price points. In order to create a frictionless shopping experience, we need to enable customers to explore our massive catalog efficiently, and find the right products that help them create their unique sense of home.

OverviewAs Wayfair technology teams begin their replatforming journeys, more engineers will make decisions for their single purpose database. Choosing the right database technology is one of the most important decisions you can make when building a new microservice. If you realize down the line that you have made the wrong choice, migrating to another database can be a costly and risky procedure. We committed to Google as our cloud platform provider, and they offer multiple robust database options. Learning enough about all of them to make an informed decision can be a steep hill to climb; therefore, we set out to streamline this process, and provide our teams with a guide to help make these decisions.

To B2B, or not B2B, that is the question.

A closer look at engineering’s role in Wayfair’s design system, Homebase

Last October, at the Lesbians Who Tech in San Francisco, I had the opportunity to speak to a packed house about navigating a career in technology. Whether you’re an aspiring technologist or a seasoned veteran, career navigation is essential in this sector, where unprecedented evolutions and disruptive shifts in innovation require us to plot our course carefully. This is especially the case in the areas of software and algorithms.

Wayfair has tens of millions of products that serve the needs of over 33 million customers. Each of our customers have nuanced preferences as they buy products to help them create their own unique sense of home. Our search and recommender systems play an important role in helping customers find these products as quickly and conveniently as possible.

According to Colin Gray, a growing number of economists are being drawn to the prospect of carrying out interesting work at technology companies like Wayfair.

You’ll be hard-pressed to find a business area that’s garnered more attention over the last 2+ years than the supply chain. Just recently, Wayfair CTO Fiona Tan spoke about the supply chain at the FORTUNE Brainstorm A.I. 2022 event in San Francisco, where the focus was, you guessed it, artificial intelligence (AI). More specifically, how businesses are shifting from dabbling in A.I. to putting it into the hands of every worker.

Not too long ago, Wayfair came to a crossroads with our aging 20-year-old, commercial off-the-shelf (COTS) EDI platform, which was not only slow but could not handle the critical new data formats used by our businesses as well as our suppliers and partners.

Testing is the critical part of software development. Unit testing is usually where it starts. That’s because it is quick and easy to get started and builds the safeguard to protect the future code changes to ensure they are inline with the corner cases. It is also much easier to maintain. The biggest advantage of unit tests comes from forcing the developers to write modularized and testable code.

(This article originally appeared on Medium)

Over thirty million customers from around the world shop on Wayfair to look for furniture that helps them create their unique sense of home. Wayfair serves a variety of webpages catered to niche customer sub-segments and help customers discover new products – these include pages with advice for people buying “twin futons,” or “nursery chairs with removable cushions.”

Feature Toggles (sometimes referred to as Feature Flags) have revolutionized software development by allowing features within a software product to be enabled individually or disabled at any point, even after they’ve been rolled out to customers. Feature Toggles at Wayfair boost productivity and provide teams with complete control over when and how to make new capabilities available to end users.