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Personalization Hub Manual / Version 2301

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3.1.2 Architectural Overview

CoreMedia Adaptive Personalization is a collection of building blocks intended to assist you in leveraging the versatility of the CAE to implement dynamic and personalized content delivery. The basic idea is that each request to the site by a visitor is associated with context data and that this data is used to determine what is to be delivered to the visitor.

Contexts represent arbitrary things about the user and his environment, such as the user's current interests, the location from which the user accesses the site, and the device used. A context can also contain general information such as the current date and time or the day of the week.

To determine the content to be delivered, CoreMedia Adaptive Personalization provides the implementation of a rule-based approach ("select some specific content if the context data fulfills some requirements") as well as an extension to the search engine integration that allows using context data within search queries.

Architectural overview

Figure 3.2. Architectural overview


To configure rule-based personalization and define customer segments, CoreMedia Adaptive Personalization includes CoreMedia Studio components that provide corresponding editing functionality for editors. All configurations are stored within document properties which are freely configurable - you are not required to use the predefined content types.

Within the CAE, you evaluate rules in a Content Bean implementation using the SelectionRuleProcessor. The processor expects to be supplied with a collection of user contexts, which may include all customer segments for which the defined conditions are satisfied by the user.

Not shown in the diagram above is the search engine extension. It provides a query preprocessor that allows you to add macro calls within query strings and evaluate these macros at time of search. For example, if you define a macro userSegments that looks up and returns the set of segments the user is a member of and tag your content with segment names which are indexed in field segments, you can search for all documents tagged with the segments of the user via the query segments:userSegments().

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