Netshoes is the leading sports and lifestyle online retailer in Latin America and one of the largest online retailers in the region. Netshoes aims to deliver to customers a convenient and intuitive online shopping experience across their three core brands – Netshoes, Shoestock and Zani.
Netshoes is in a highly dynamic business. This dynamic nature complicated their ability to drive the most revenue out of their search program. Inventory changes, price changes throughout the day, and special discounts applied randomly all required manual intervention to respond to those changes multiple times a day, taking valuable time and resources.
Kenshoo’s Portfolio Optimization (KPO) uses machine learning to optimize bidding based on a goal and constraints, shifting bids and budgets accordingly to achieve business goals. Coupled with Portfolio Plus, Netshoes could subset their products and bid to the value of that subset. But, KPO’s standard behavior is to run daily, and Netshoes needed to be able to automatically optimize more frequently to respond to the fluctuations that were occurring throughout the day.
Kenshoo’s Real-time Optimization (RTO) enabled Netshoes to adjust bids in response to changes on an hourly basis. And, Kenshoo’s Structure Optimization automatically grouped products by demand, allowing flexibility to bid more aggressively on hot products. The higher frequency of RTO and the automatic restructuring of product groups meant that Netshoes didn’t need to analyze results hourly and manually change bids when needed.
Kenshoo’s RTO has made Netshoes search campaigns more responsive. In the first three months after implementing RTO and Structure Optimization, Netshoes experienced an increase of roughly 20% revenue and 45% ROI.
It’s important to note that the prior quarter included the holiday season, so these results were above and beyond their seasonal peak. And, after implementing RTO, they’ve nearly eliminated manual bidding.