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Machine Learning Solution Optimizes Google Shopping Campaigns

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Criteo has introduced a new search solution following beta tests with leading retailers including Revolve Clothing, Teleflora and Camping World. The automated, end-to-end solution, powered by machine learning, is designed to systematically improve results from Google Shopping using predictive optimization across every aspect of a campaign.

Criteo Predictive Search continuously optimizes remarketing lists, campaign structure, campaign settings and bidding, allowing paid search marketers to:

            • Re-engage high-value users via behavioral targeting technology that programmatically sets bids based on each user’s propensity to make a purchase;

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            • Increase ROI with multi-dimensional bidding that reflects a granular understanding of product characteristics, performance history, user intent, device and user behavior; and

            • Consistently meet targets, even during seasonal and promotional peaks, with campaigns that automatically and accurately adapt.

“Google Shopping is a huge opportunity for retail marketers, with Shopping quickly becoming the biggest e-Commerce performance driver for retailers,” said Jason Lehmbeck, General Manager for Search at Criteo in a statement. “Yet the tools available are overly complex and time-consuming, and do not sufficiently help marketers connect with consumers who are actively shopping for their products. Our goal with Predictive Search is to eliminate the guesswork of managing Shopping Campaigns.”

Criteo Predictive Search is available immediately in the U.S., with further global availability to be added throughout 2017.

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