RichRelevance Introduces Hyper-Personalization for Digital Marketing

Jan 15, 2019


BEST PRACTICES SERIES

RichRelevance, a provider of experience personalization, unveiled hyper-personalization with Deep Learning, the next tier of AI technology to drive digital growth, engagement, and revenue by staging compelling customer experiences across the commerce lifecycle. Hyper-Personalization helps define how digital business leaders will bridge marketing and commerce clouds to engage every customer as an individual—in real time, at global scale—and enhance the value of existing investments in both which focus on basic personalization.

Customers have so many ways to interact with a brand, but the current definition of personalization and the limits of current marketing technologies make it virtually impossible to carry on a consistent, seamless conversation across channels. Marketing clouds fall short because they focus on personalized campaigns—one-way interactions and probabilistic segments—and lack the native controls to configure for commerce. On the other side of the customer experience are the commerce clouds, which were primarily designed for transactions and offer rudimentary, rules-based personalization that doesn’t meet the needs of today’s consumer.

This gap is forcing brands and retailers to go beyond basic segment-based personalization as they look to create consistent, branded customer journeys. The need is Hyper-Personalization, which is different in kind and can only be achieved through three unique characteristics:

  • Individual, not just segments: A behavioral profile is created and updated in response to digital signals from every touchpoint, giving a 360° view of the customer—and allowing companies to address each customer as a segment of one.
  • Real-time context: The ability to detect context and recognize significant moments that combine probabilistic customer data with company-unique and customer provided “zero-party” data to build individual profiles to rationalize often disparate touchpoint-specific data and respond appropriately with real-time decisions, driving better relevance.
  • Deep Learning AI-driven decisioning: With the breadth of context across the entire customer lifecycle, a full spectrum of AI is required, including deep and machine learning. Hyper-personalization is designed to eliminate rules, discover patterns and centralize the experience decisioning across overlapping contexts, algorithmically picking the winning experience on a per session basis in real time for each individual.

Related Articles

A new platform designed to improve e-commerce conversion rates using machine learning has been unveiled.
BigCommerce merchants can now use AdRoll's growth platform to attract and engage customers; Yotpo users can integrate user-generated ratings and reviews seamlessly in their digital ads.