• June 20, 2018

RichRelevance Launches Xen AI

RichRelevance, a provider of experience personalization, today announced RichRelevance Xen AI to help companies blend human expertise and machine intelligence.

"Xen AI delivers on our vision to help companies grow their businesses by turning every digital interaction into a personalized, memorable experience," said Carl Theobald, president and CEO of RichRelevance, in a statement. "This is one of the most important and exciting launches in our company history and reinforces our commitment to continuous innovation. With Xen AI, our clients now have the world's most transparent, impactful personalization available in the market today."

Xen AI includes Experience Browser, Data Science Workbench, and Experience Optimizer and more than 300 strategies to help business leaders detect and respond to unlimited digital signals in real time, using a full spectrum of algorithms and multi-context AI to deliver mass personalization at scale.

The Experience Browser allows business users to visually inspect and analyze AI strategy alongside business performance trends and real-time product and profile insights, including real-time data on placements, products and strategies. The dashboard allows users to audit AI decisions, including profile, recommendation summary, segment, rules, and strategy evaluation.

Key features of Experience Browser include the following:

  • Dynamic segment and user graph inspection for individuals based on their behavior;
  • Rule selection evaluation by segment, context, type, etc.;
  • Overall placement performance for attribution, views, clicks, revenue, etc.;
  • Deep links to Experience Insights for drill-down reporting; and
  • Content performance rankings.

Business users can make adjustments and changes based on insight on the user graph data available to the AI and identify outdated, broken, or ineffectual rules.

With the new Data Science Workbench (DSW), RichRelevance provides a full lifecycle management system that allows data scientists and marketing technologists to deploy, test, and iterate experience personalization insights and strategies. Users can leverage and extend their data science, bring in data from any source, and incorporate custom models and strategies.

DSW Modules include the following:

  • Model Builder, allowing users to access RichRelevance's big data store of user behavior to create new models, micro-segmented decisioning, business rules that combine marketing, and commerce domains;
  • Model Importer: allowing users to bring offline analysis to life online and improve the testing and explainability of their existing algorithms by bringing their own work into RichRelevance Xen AI; and
  • Strategy Publisher, allowing users to deploy and run strategies at scale.

Xen AI also offers a two-tiered decisioning architecture. The first tier features a Strategy Library of more than 300 out-of-the-box personalization strategies, plus unlimited custom strategies through the Data Science Workbench. The second tier features Experience Optimizer, which leverages predictive strategies to dynamically and transparently assemble individualized experiences in real time. The Experience Optimizer is continuously testing to discover the best-performing algorithms for specific individuals and context as well as considering business rules to override the AI decisions in the final output.

Experience Insights are a set of analytics dashboards and new real-time reports that provide visibility and control over business performance delivered by the Experience Optimizer. They answer the following questions:

  • "How is my business performing?" with Sales, Cohort, Placement, Strategies, and Advanced Rules Merchandising Reports and Site Analytics;
  • "Who's shopping what products right now?" with real-time reports and APIs to embed this in other enterprise applications.

CRM Covers
for qualified subscribers
Subscribe Now Current Issue Past Issues

Related Articles

RichRelevance Introduces Hyper-Personalization for Digital Marketing

RichRelevance Hyper-Personalization combines artificial intelligence with deep learning.