Getting Personal with Recommendations

Allison Howen
by Allison Howen 12 Aug, 2015

Real-time Web personalization software provider Evergage has unveiled new recommendation capabilities for its platform.

The new capabilities come from Evergage Recommend, which is an integrated recommendation system that is a native part of a full testing, targeting and personalization solution. The offering incorporates dynamic suggestions of relevant products or pieces of content that will resonate with individual visitors. The system leverages deep behavioral analytics and insights, as well as aggregated browsing and past purchase behaviors of other visitors, to deliver suggestions based on visitors' expressed or implied preferences. This enables marketers to act upon customer intent and respond with the most relevant recommendations to improve the customer experience and increase conversions.

Additionally, Evergage Recommend gives marketers the ability to use pre-built algorithms, build their own algorithms by scratch or customize pre-built formulas by defining various parameters. Once created, marketers can deploy recommendations anywhere within a website.

"We strive to offer the most robust real-time personalization platform available today. A natural extension of that, Evergage Recommend was designed to work across industries and verticals - from the more obvious adopters such as retailers, to travel, financial services and publishing companies," said Karl Wirth, co-founder and CEO, Evergage. "This is an exciting new offering for our customers, and we're thrilled to provide a tightly integrated platform for making relevant recommendations that are uniquely tailored to each individual's experience."

It is important to note that Evergage Recommend aims to bridge the gap left by other recommendation solutions that operate in a silo and are cut off from testing, segmentation, customer data and analytics. In fact, the solution provides algorithm transparency so marketers can see the details and implications of their product or content recommendation strategies. Evergage also factors in individual visitor behavioral data, including time spent and overall engagement, to deliver highly targeted recommendations based on true intent and personal preferences. Moreover, the solution considers individual affinity, segment and survey response data, along with overall intent, in order to deliver more relevant and effective recommendations to visitors. Evergage Recommend also doesn't require companies to integrate with product or content catalogs via APIs. Instead, catalog data is collected in real time as visitors browse the site for better personalization. Lastly, the solution integrates with the core Evergage Platform and other modules.

"With Evergage Recommend, our Merchandising team can introduce relevant product recommendations with minimal effort," said Paul Kisicki, director of merchandising for Zumiez. "And because we're able to control and preview the algorithms driving recommendations, we're much more confident in what's being presented to shoppers based on their unique interests and preferences. Most importantly, the results have been validated by the measurable increase in sales of recommended products."