Retailer Overstock.com Mines Decades of Data

We often hear that online retail is among the business sectors furthest along on its digital transformation and AI journeys. Overstock.com is a case in point.

The giant (2017 revenue: $1.75 billion) internet retailer, known mostly for furniture and home décor, has built out a digitized ecommerce environment that captures and analyzes the behavior of millions of monthly visitors to its website – behaviors such as adds and removals from shopping carts, product queries, product comparisons, time of days and so forth – amounting to billions of individual site events.

For Chris Robinson, a self-described “data enthusiast” and head of marketing data science at the Midvale, UT, company, Overstock.com’s enormous data stores is “where I knew I wanted to take my career…, e-commerce web log data is the playground we all dream of.”

Formed in 1999 during the dot-com boom, the company has captured two decades of customer data that Robinson and the company’s teams of data scientists, engineers and analysts mine for “actionable insights,” as they say in the analytics world. The team faced not only a formidable data science challenge, it’s also data science at scale.

“As a culture we made a deliberate decision to never be complacent,” Robinson said. “Fast is never fast enough. The rate at which our customers are becoming more sophisticated in terms of what they expect from their experience, and the rate the tech is changing, speed is key. We have to have horizontally scalable technologies that allow us to keep progressing, keep pushing and keep refining these processes, so we’re delivering more insights and delivering more personalized customer experiences in near real time.”

Read the full story here at sister website EnterpriseTech.com.