Method for Determining Popularity of Video on Demand Content
Original Publication Date: 2008-Apr-28
Included in the Prior Art Database: 2008-Apr-28
A method and discovery process is described herein whereby users are led to make satisfying choices from a large number of available titles in a Video-On-Demand (VOD) library, while minimizing post-decision regret and averting feelings of loss when selecting less popular titles. The present solution provides a variety of ways for a user to gather additional information of less popular titles once a user views information of a popular title in a VOD storefront. It mixes the use of stand-alone information along with group influence to provide a sophisticated approach to search, discovery, and navigation to encourage users to purchase less popular titles.
Video-on-demand (VOD) libraries contain a growing amount of movie and television titles that are available to users. A title, as described herein, is any media file that may contain a video and/or audio component. Although there is a growing trend toward more VOD title choices, this is not necessarily correlated with increasing user satisfaction. That is, users desire a greater number of choices but are typically satisfied with just some choices and may actually become less satisfied with more choices. Today’s online VOD capabilities further provide a user the ability to search any title at any given time. The availability of millions of titles presents a user with an overabundance of choices that requires the user to search for titles of interest using inadequate filtering mechanisms such as lists, menus, and tables.
Due to the aforementioned problems, a need exists to provide a discovery process whereby users are led to make satisfying choices from a large number of available titles in a VOD library. One method of increasing the relevancy of search results is to have a measure of popularity associated with the results, such as is utilized in Internet search queries. However, for VOD content there is currently no precise way to determine the popularity of titles.
The present solution utilizes two dimensions to determine the popularity of VOD titles. One dimension is static and the other dimension is dynamic. The static dimension includes elements that exist during a movie/TV program’s theatrical release, such as media expenditures, screen showings, critics’ rating, Star Power, sequels, genre, MPAA/TV rating, and distributor information. The static dimension also includes elements determined by the sequential nature of movies/TV programs. On the other hand, the dynamic dimension is real-time and based on the seasonality/timing and usage of titles within the system. For example, war movies may be more popular around Memorial Day, and if a particular user has already viewed a particular title, its popularity value should drop when presented to that particular user. Lists of VOD titles presented to a user may be statically created (e.g., children movies) or dynamically created (e.g., through a search) but a list’s contents should always be presented by a popularity index.
A Popularity Index, as described herein, can take a variety of information such as the abovementioned static and dynamic elements to provide a rank or value to a particular title. Since users will identify popular content more readily than less popular content, any lists presented to the user should be sorted by a Popularity Index....