RichRelevance Recommend

Product Overview
RichRelevance Recommend collects data and uses a powerful machine-learning engine to select the most relevant, data-driven product recommendations for each customer interaction, across all touchpoints—web, mobile, email, in-store and call center.

• Build ensemble recommendations by leveraging product attribute and compatibility data from trusted third party sources such as CNET DataSource™.
• Deliver recommendations optimized for limited screen sizes to drive maximum conversion for your mobile experience.
• Empower your data scientists to define new strategies and test them against 125+ of our road-tested strategies.
• Give your customers the power to specify their preferences and use that data to tailor their individual recommendations.
• Graph a single view of your customer across sessions, devices and channels by storing customer data on our cloud without relying on cookies to deliver unified recommendations.
• Once King of the Hill Decisioning determines the most effective algorithm for your recommendation, the King of the Hill Optimizer uses Gaussian Process Regression (aka Kriging) to fine-tune weights and parameters that optimize the selected algorithm for the greatest customer interaction and potential revenue.
• Our machine learning engine constantly tests and evaluates recommendation performance to identify and deliver the most effective algorithm for each customer interaction based on your specific business KPIs.
• Send customer and product data from any cloud, app or device

Imagine if every recommendation you presented matched your customers’ taste, as if curated by a personal shopper or stylist.