How a CDP Recommends Personalized Content Using AI

How does the AI-driven Content Recommender work?

The AI-driven content recommender in Sitefinity Insight helps increase user engagement and conversions by suggesting relevant next steps based on individual behavior. By analyzing past visitor journeys and site content, the system delivers targeted content that guides users toward meaningful actions. This improves content relevance, keeps users engaged longer and increases the likelihood of conversion.

How does the AI-driven content recommender select personalized content?

The AI-driven content recommender in Sitefinity Insight selects the best next page to suggest to a visitor. It uses machine learning to analyze the content on your website and the journeys of visitors who have already converted. Based on this data, it builds a model to recommend content to users who have not yet converted.

What types of data are used to train the content recommender AI?

The recommender is trained on the behavior of converting visitors and the textual content of website pages. This includes analyzing user journeys and page content to determine which pages are most effective in driving conversions.

How does the system handle cold starts with new users and minimal data?

Sitefinity Insight requires a minimal number of conversions to train its AI content recommendation model. Without this data, recommendations may not be generated until enough interaction history is available.

Can recommendations adapt based on real-time user engagement?

Yes, Sitefinity Insight adjusts content recommendations in real time based on user engagement. The platform uses live interaction data to dynamically deliver personalized content during the session.