Episerver Content Recommendations automatically generates a personalized content feed for each visitor based on the individual's site activity.
How it works
Content Recommendations uses Natural Language Processing (NLP) to understand the meaning of each piece of content at a granular level and builds a real-time interest profile for each visitor based on their interactions with the NLP-generated topics. Content Recommendations uses this information to recommend articles, blog posts, or other specified content sections that are most relevant to the visitor's interest profile.
- The following image shows topics generated from a single piece of content automatically via Natural Language Processing (NLP).
- The following image shows a click stream of an individual based on site activity.
- The following image shows an interest profile of the same individual expressed as topics.
- Expose necessary metadata (such as og:image) on content pages that are eligible for recommendations.
- Install the tracking script on a site to activate content processing and interest profiling.
- Set up sections and corresponding flows attached to the widget delivery.
- Set up delivery of the widget with the assigned section.
- Install content block on a page.
- Test and launch content recommendations.
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Last updated: Mar 06, 2020