Wayfair Tech Blog

Modularization Blog Post Diagram (2).jpg

App Modularization at Wayfair: How we unlocked our code and Android and iOS teams at scale

Why we decided to modularize

Data Scientists can group products with similar materials to enable 3D artists

Machine learning to aid 3D modeling at Wayfair

High-quality lifestyle imagery is core to Wayfair’s ability to merchandise its catalog effectively and help customers shop confidently. Creating lifestyle images through 3D models enables rapid production of product visual merchandising at scale, drives simultaneous reduction in cost and speed to produce imagery, and unlocks new ways (e.g. AR, VR) for customers to engage with products. Early tests show 3D-generated images can provide high quality visual detail of our products and increase conversion rates for flagship brands (main products in Wayfair’s portfolio and to which customers most relate or identify Wayfair). Therefore, producing 3D models quickly and accurately is key to further reducing 3D imagery costs and driving revenue. In this blog, we will introduce how machine learning is utilized to aid 3D modeling at Wayfair.

Wayfair Tech Blog

The Road to the Cloud — Part 3: Streamlining the Workflows

As our journey continues, we have already covered testing at a smaller scale, learning throughout the process, and setting our ambitious goal to move Wayfair Storefront to the cloud!

Flow diagram of recommender model generating recommendations for sponsored ads, pdp abandonment emails, post order emails, retargeting

Wayfair Tech Blog

Two Birds, One Stone: Hedwig, A Random-Walk Based Algorithm for Substitutable and Complementary Furniture Recommendations

At Wayfair, we recommend millions of products across all styles and budgets. Because of the scale of our catalog, we constantly ask ourselves: how can we help our customers find the right products efficiently while discovering exciting complements to fill out their space?

Wayfair Tech Blog

Open Source `Extra-Model`: Semantic Groupings for Better Customer Feedback

Wayfair is an international company with a presence in multiple countries: US, Canada, UK, and Germany. And where our UK customer might look to purchase a “heater”, our US customer might use the term “radiator” to describe the same thing. We want to ensure we’re able to understand that both customers are referring to the same item and interpret feedback left by customers in the form of product reviews correctly.

Wayfair Tech Blog

The Road to the Cloud — Part 2: Plan and Go Big

In the previous installment, we talked about testing smaller components first, expanding the scope gradually, and learning more about the platform of choice in the process.

Wayfair Tech Blog

DS Hackathon Spotlight: The Voice of Wayfair in a Generative Text Model

In early August, the Data Science (DS) team put on their first DS-wide hackathon. The global hackathon event brought together Boston and Berlin based data scientists for one day of hacking and demos. The event challenged teams to think big about how algorithms can transform Wayfair’s business and help unveil unseen possibilities. Some successful tools and products on our site, like our Visual Search tool, started as hackathon projects! The hackathon is a fun challenge to try out new methods or algorithms, explore a different part of the business, and collaborate with team members across disciplines.

Wayfair Tech Blog

The Road to the Cloud — Part 1: Test and Learn

Have you ever wondered how engineering teams tackle the challenge of ensuring reliability and performance amid increasing site traffic? If so, I hope the information in this four-part series will be of interest to you.

A photograph of Wayfair Engineer Adam Carlson smiling at the camera with his hands in his pockets.

Wayfair Tech Blog, Tech & Innovation, Community Engagement, Workplace

How a Wayfair Engineer's Side Project is Making a Big Impact

During the Presidential campaign season in America, it can be almost impossible to escape the near constant coverage and conversations surrounding the premiere candidates and their positions on the issues. However, as voters look further down the ballot, they’ll find lesser-known candidates in local races who don’t receive the same kind of national attention that Presidential candidates do. As a result, voters may find themselves uninformed on those candidates' views and unsure of who they’d prefer to vote for.