netshoes case study v2 -...

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CASE STUDY Netshoes Responds More Quickly to Business Changes BACKGROUND Netshoes is the leading sports and lifestyle online retailer in Lan America and one of the largest online retailers in the region. Netshoes aims to deliver to customers a convenient and intuive online shopping experience across their three core brands, Netshoes, Shoestock and Zani. CHALLENGE 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 intervenon to respond to those changes mulple mes a day, taking valuable me and resources. RESULTS SOLUTION Kenshoo’s Porolio Opmizer (KPO) uses machine learning to opmize bidding based on a goal and constraints, shiſting bids and budgets accordingly to achieve business goals. Coupled with Porolio 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 automacally opmize more frequently to respond to the fluctuaons that were occurring throughout the day. Kenshoo’s Real-me Opmizaon (RTO) enabled Netshoes to adjust bids in response to changes on an hourly basis. And, Kenshoo’s Structure Opmizaon automacally grouped products by demand, allowing flexibility to bid more aggressively on hot products. The higher frequency of RTO and the automac restructuring of product groups meant that Netshoes didn’t need to analyze results hourly and manually change bids when needed. “Kenshoo’s Real-me Opmizaon coupled with automated Structure Opmizaon is a huge me saver, allowing us to focus more on our macro strategies. Addionally, Kenshoo’s machine learning is smarter and faster than our manual bid opmizaons, driving higher revenue and ROI Allan Moa - Markeng Coordinator © 2017 Kenshoo | Kenshoo.com 20% 45% Increase in ROI Increase in Revenue Kenshoo’s RTO has made Netshoes search campaigns more responsive. In the first three months aſter implemenng RTO and Structure Opmizaon, 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, aſter implemenng RTO, they’ve nearly eliminated manual bidding.

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Page 1: netshoes case study v2 - Kenshookenshoo.com/wp-content/uploads/2017/11/Netshoes-Case-Study-v2.… · CASE STUDY Netshoes Responds More Quickly to Business Changes BACKGROUND Netshoes

CASE STUDY

Netshoes Responds More

Quickly to Business Changes

BACKGROUND

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 Zattini.

CHALLENGE

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.

RESULTS

SOLUTION

Kenshoo’s Portfolio Optimizer (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 Real-time Optimization coupled with automated Structure Optimization is a huge time saver, allowing us to focus more on our macro strategies. Additionally, Kenshoo’s machine learning is smarter and faster than our manual bid optimizations, driving higher revenue and ROI”

Allan Motta - Marketing Coordinator

© 2017 Kenshoo | Kenshoo.com

20% 45%Increase in ROIIncrease in Revenue

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.