What Makes Criteo's Engine Hum? Product Recommendations | Criteo
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What Makes Criteo’s Engine Hum? Product Recommendations

 

It’s a digital marketer’s constant problem: After shoppers leave your site, bringing them back to finish a purchase can be challenging. You need to deliver custom product recommendations designed to catch each shopper’s attention. So how can you do it? What tools and technologies are available so you can optimize your offerings to maximize sales?

Criteo’s Engine is a sleek, finely tuned solution that can give your shoppers the nudge they need. In this three-part series, we’re taking a look at the components that make up the Criteo Engine, including Predictive BiddingProduct Recommendations, and Kinetic Design.

While product recommendations are among brands’ most vital tools today, the Criteo Engine takes it a step further. Criteo’s Product Recommendations build on the capabilities of Predictive Bidding to highlight the items that have the best chance of capturing your shoppers’ attention and spurring a purchase.

Why Most “Recommendations” Are Limited

Product recommendations are a standard feature across most retargeting solutions. However, most are limited in their scope.

Your standard solution might generate an ad for the product someone viewed on your site or even “recommend” the best selling products. However, these aren’t the most optimal “recommendations” because they don’t consider your shopper’s intent.

While it’s important to remind potential shoppers of the item they looked at, they may have clicked away because it was ultimately not the product they wanted or were prepared to buy right then and there. Perhaps they’re interested in your top selling items, but those just aren’t quite what they’re looking for. While you may never know why they don’t convert, by using what you know about shopper intent data from similar purchases, you can still make better recommendations and increase the likelihood of conversion.

The Criteo Difference

Recommendations of previously viewed products are no doubt powerful, but they’re only the first step. Criteo’s Product Recommendations build on this with more intuitive, machine-learning based insights. By analyzing information from over 1.2 billion monthly shoppers, Criteo’s Product Recommendations technology is able to hone in on the items that will most interest your shoppers — including those they haven’t even seen yet.

Criteo’s Product Recommendations leverage details about each shopper’s previous interactions, your most popular merchandise, and the actions of similar shoppers to pinpoint their intent. The engine then recommends other items that will be the most enticing on a shopper-by-shopper basis. In this way, the feature makes recommendations that span your entire inventory catalog, and has the power to considerably drive up the sales of new items.


Product Recommendations use insights from shopper intent signals to serve up items most likely to convert.

The ability to include products that shoppers haven’t looked at in the past is what makes Criteo’s Product Recommendations so unique. No other solution has the sophisticated ability to predict the ideal product for each individual, providing an unparalleled level of personalized service.

Check out the next part in this series where we’ll delve into Kinetic Design, the feature that makes custom, optimized, automated ads possible.

What Makes Criteo’s Engine Hum, The Series:

Predictive Bidding
Product Recommendations
Kinetic Design

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