diff --git a/docs/html/training/tv/discovery/recommendations.jd b/docs/html/training/tv/discovery/recommendations.jd index a74ee5683699f..ffe33f28bb000 100644 --- a/docs/html/training/tv/discovery/recommendations.jd +++ b/docs/html/training/tv/discovery/recommendations.jd @@ -10,6 +10,7 @@ trainingnavtop=true
Recommendations help users quickly find the content and apps they enjoy. Creating +recommendations that are high-quality and relevant to users is an important factor in creating a +great user experience with your TV app. For this reason, you should carefully consider what +recommendations you present to the user and manage them closely.
+ +When you create recommendations, you should link users back to incomplete viewing activities or +suggest activities that extend that to related content. Here are some specific type of +recommendations you should consider:
+ +For more information on how to design recommendation cards for the best user experience, see +Recommendation Row in the Android TV Design Spec.
+ +When refreshing recommendations, don't just remove and repost them, because doing so causes +the recommendations to appear at the end of the recommendations row. Once a content item, such as a +movie, has been played, +remove it from the recommendations.
+ +You can customize recommendation cards to convey branding information, by setting user interface +elements such as the card's foreground and background image, color, app icon, title, and subtitle. +To learn more, see +Recommendation Row in the Android TV Design Spec.
+Base your recommendations on user behavior and data such as play lists, wish lists, and associated -content. When refreshing recommendations, don't just remove and repost them, because doing so causes -the recommendations to appear at the end of the recommendations row. Once a content item, such as a -movie, has been played, -remove it from the recommendations.
- -The order of an app's recommendations is preserved according to the order in which the app -provides them. The framework interleaves app recommendations based on recommendation quality, -as measured by user behavior. Better recommendations make an app's recommendations more likely -to appear near the front of the list.
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