Trending recommendations lists

  • Article

Trending lists in Intelligent Recommendations enable browsing a content catalog using algorithmic charts sorted by information such as total sales, sum of clicks, release date, or a combination of different metrics. You can further scope trending lists to specific time windows and aggregations to surface the most popular or best-selling products to users. We currently support three base types of trending lists:

  • New
  • Trending
  • Popular

Trending lists provide the following capabilities:

  • Flexible filtering schema, so you can filter lists to specific categories or other metadata, focusing on items of interest

  • Personalization, so you can increase the item's relevance and supply a better match based on a user’s history or preferences

This article describes several trending lists scenarios you can use in Intelligent Recommendations. These scenarios are flexible, so you can modify them according to your business needs.

You can tailor a Popular chart to focus on basic consumption, overall popularity, or revenue. Intelligent Recommendations supports metrics such as sales figures, usage counts, game play counts, time spent with content, and more.

Examples of popular products:

  • Most popular restaurants

  • Best-selling shoes for women

  • Most viewed videos or articles

With the New and rising releases chart, you can highlight a specific subset of products by using various time-based or time plus popularity-based metrics to surface new or trending items.

Examples of trending items:

  • New releases in movies

  • New arrivals for clothing

  • Trending coats

  • Trending music videos

  • Trending articles for this topic

See also

Fine-tune results
Use personalized recommendations lists
Provide item-based recommendations lists