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Types of content

With the Personalization service, you can build different recommendation domains. You do this by splitting all the products into different types of content. There are several possible use cases for types of content, for example:

  • A publisher can track articles, pictures and videos as three different types.
  • A store can split all the products into food and non-food product groups.
  • An owner of several web stores can use a single account for all of them.

Based on the types of content concept, it's possible to make so-called cross content type recommendations (like "Users who watched this film also read this book" or "Users who bought these wallets also bought these belts").

Apart from the logical separation of the content domains, types of content provide another important advantage. You can use them to adjust recommendation weight if different types of products/content items aren't equally popular but must be recommended equally often. For example, on a content publisher's page, users watch videos less often than they read articles. If the most popular products were requested without splitting the types of content, there would most likely be no videos in the recommendation result. If articles and videos are split into different types of content, you can explicitly request popular videos and/or popular articles.

Here is a comparison of different approaches that you can take when defining types of content:

Use case Types of content solution (domain context) Attribute based sub-models (group context) Different Personalization service accounts
Cross-group recommendation requests are possible yes yes no
Products must belong to one group mandatory optional mandatory
Products can belong to multiple groups no yes no
Single recommendation request can contain products from different groups no yes no
Product can change the group it belongs to no yes no
Different types of content share the scenario and model configuration yes yes no

Types of content and scenarios

If multiple types of content are enabled in your configuration, for every scenario that should recommend a specific type, you must enable this output type. For more information about scenario configuration, seeĀ Configure scenarios.