In April, I attended the Data Science Research Symposium at University of Massachusetts Amherst and gave a short talk highlighting Wayfair’s marketing data science projects. The full video and slides are below, but here’s an overview. Goals of marketing data science at Wayfair As the largest online retailer of furnishings…
At Wayfair, the data science teams collaborate with other partner teams to translate business problems into analytical frameworks, leverage data and machine learning to make robust predictions and recommendations, and build engineering architecture to scale up machine learning solutions. In a recent machine learning seminar at Northeastern University in Boston,…
Since I began my tenure at Wayfair as a data scientist, many PhD students and postdocs have reached out to ask for advice about the transition to data science in industry. After a fruitful collection of conversations, I’ve realized that there are popular misconceptions about what it means to be…
As data scientists, we face a variety of problem types. One of our critical challenges is identifying the proper methodological approach to solve each problem. By doing this, we avoid force-fitting the wrong tool to solve a problem, and we avoid having to reformulate a question to fit a specific…
At the beginning of February, I attended one of ACM’s premier conferences, WSDM 2018 in Los Angeles. Apart from the Hollywood-style banquet dinner on a boat, I was looking forward to the opportunity to talk through ideas with some of the brightest minds in the world from both academia and…
Right now, Wayfair has about 86,000 rugs available for purchase. On the first page of our rug category page, however, we only have room for the top 48. You see even fewer if you don’t happen to scroll or swipe down. When it comes to our customer’s experience, what we…
As Data Science has become increasingly important to Wayfair’s success, so has the quest to find great people to join our team – individuals who are intelligently connected to their work and constantly learn, study, experiment, and create. Hiring for and branding our data science initiatives is merely one element…
Multiple recommendation systems at Wayfair use collaborative filtering based models to understand user behavior and identify like-minded customers. Despite its success, collaborative filtering has a few significant drawbacks, such as the cold start problem and a limited scope of recommendable products. By leveraging image based product embeddings, Wayfair has created…
Wayfair offers a zillion things home, with one of the world’s largest online selections of furniture, home furnishings, décor and goods, including more than eight million products from over 10,000 suppliers. Wayfair’s expanding Visual Search team is leveraging deep learning and our expansive catalog of images to create an exciting…
At Wayfair, technology and data expertise enable data scientists to transform new web datasets into intelligent machine algorithms that re-imagine how traditional commerce works. In this post, we introduce how visual tools like Violin Plots amplify our data acumen to unlock deep insights. The savvy data scientist recognizes the value…
In this first blog post focused on marketing attribution & measurement, we share insights on how Wayfair has leveraged a unique combination of geographic splitting and optimization techniques to measure the performance of our various marketing channels Key article takeaways: Geographic splitting is a convenient and generally applicable tool…
