Evergage Adds Recommendation Tech to Personalization Platform | eWeek

Evergage Adds Recommendation Tech to Personalization Platform

evergage and marketing
Écrit par
Nathan Eddy
Nathan Eddy
Aug 13, 2015
2 minute read
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Evergage announced the debut of Recommend, an integrated recommendation system that is a native part of a full testing, targeting and personalization solution.

The offering builds on the foundational real-time personalization capabilities of the Evergage platform, incorporating dynamic suggestions of pertinent products or pieces of content.

Leveraging behavioral analytics and insights, Evergage Recommend delivers suggestions based on visitors’ expressed or implied preferences, as well as the aggregated browsing and past purchase behaviors of other visitors.

“We identified a number of unmet needs with existing recommendation engines,” Andy Zimmerman, chief marketing officer of Evergage, told eWEEK. “For example, many solutions lack the ability to give customers more control over their recommendation strategies, base recommendations not only on popularity but also on unique individual visitor behaviors, and enable companies outside of the retail industry to deliver content, not just product, recommendations.”

In conversations with customers and prospects, Zimmerman said he learned that in using existing recommendation solutions, they typically struggled with algorithms not displaying relevant product offerings, the ability to target recommendations to individual users or user segments, and product feed delays causing recommendations to promote out-of-stock items.

“When setting out to develop Recommend, our goal was to provide marketers with complete transparency and autonomy over their recommendation strategies,” he said. “Our philosophy is that marketers—without requiring IT or developers—should be able to build, preview, test, adjust and deploy the most optimal recommendation strategies.”

Recommend is designed to give marketers greater flexibility and control with the ability to utilize prebuilt algorithms, build their own from scratch or customize prebuilt formulas by defining various parameters.

Once created, recommendations can be deployed anywhere in a website by a marketer, not just placed in fixed positions.

Evergage also provides transparency so marketers can see the details and implications of their product or content recommendation strategies, modify them or create new ones from scratch.

In addition, the solution does not require companies to integrate with product or content catalogs through APIs.

Instead, catalog data is collected in real time as visitors browse the site, so it can be used instantly for personalized recommendations.

“From the marketer’s perspective, being able to access campaign-reporting details from anywhere is important,” Zimmerman noted. “Evergage on the Go is our new mobile app that allows [users] to quickly access campaign statistics—including how their recommendations are performing—right from their iPhones.”

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