Alie’s “Most Viewed” recommendations rely on other user's views. Alie uses content-based filtering to understand what type of content/items most users viewed in a particular category and recommends them to the audience. For Ex. If a large number of users have already seen the “Avengers” in the “Action” genre, then Avengers will be shown as one of the recommendations to new users if they search for Action Movies.
“Most Viewed” Recommendations are driven by the volume of events because views are most common, and therefore the system will train quicker when compared to cart additions cart and purchases.
Alie’s “Most Viewed” recommendations are a great fit for Video Streaming Platforms. The concept of “Views” is popularized by Youtube, more the number of views more revenue a publisher will earn. Most Viewed Recommendations can be used appropriately along with other filters to drive more views on your content. For Ex. Use demographic filters to drive curiosity - “Most Viewed in NY Area in last 30 days”, Use categories “Most Viewed in Horror Category”, apply real-time filter and call it “Trending Now”, etc.
Alie’s “Most Viewed” recommendations can also be used for Ecommerce Platforms. Users on the ecommerce platforms browse or view many items before making a final purchase, based on such views recommendations can be made for other users. For Ex. If a user wants to purchase a mobile phone under $1000 then, he will be shown the most viewed mobile phones priced under $1000 as recommendations.
"Alie’s “Most Viewed” recommendations can also be used for other industry segments, where end-users engage with content/products/items and make purchases. Users on news/blogging platforms browse or read many articles daily, users on the gaming platform browse, play or purchase games, users on the real estate platforms browse information on properties.