Improving Customer Relevance Through AI-Powered Text Recommendations

Eva Maria Schmidt
February 6, 2020

Many of our clients, especially in retail and eCommerce, have seen the tremendous value of surfacing Artificial Intelligence (AI)-powered product recommendations as they engage with consumers day-to-day. However, we would be remiss to undersestimate the need for such a capability across many other industries that we service; companies that may not necessarily be in the business of selling “products” but rather, content or other types of services.

Introducing: Text-Based Algorithm

This week, we announced the launch of a text-based algorithm as part of the Smart Content functionality within our AI-powered engine, Marigold Recommendations. This new capability leverages Natural Language Processing (NLP) to enable clients to deliver recommendations based on text.

The text-based similarity engine actively looks at a customer’s content consumption behavior and recommends similar content. Leveraging AI-powered content analytics, keywords in previously viewed text are rated and compared to keywords within the company’s larger content catalog. When there is a strong enough match, the relevant content is surfaced and recommended to the consumer in near real-time, not calculated overnight like many solutions.

This is a truly powerful and game-changing capability that will empower companies to drive deeper engagement, and deliver relevant and personalized experiences for a wide-range of industries, including publishing and media, travel and hospitality, as well as financial services, among many others. A few examples:

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