Automatically catalog all videos, episodes, genres, categories, and associated metadata to power machine learning algorithms. Capture referring source, viewer ratings, viewing history, etc. Catalog Information about the categories, year of release, title, genres, and more.

Having a recommendation engine lets you focus on every customer’s preferences equally. Whenever a new subscriber joins your OTT channel, he/she expect to find the content matching their preferences. A recommendation engine like Alie provides your customers with what they are looking for instead of showing them non-relevant content.

“Binge-watching," describes the habit where subscribers watch multiple episodes of a television show consecutively, unlike weekly tv programs of old times. Recommendation engines have a great role to play when it comes to binge-watching, better the quality of recommendations more the number of people who will watch the recommended content.

Subscribers will be glued to your streaming platform if they discover the relevant content on the go. Let us understand this with an example - If a subscriber is watching a final episode of a thriller series and finds another thriller series in the recommended content, then the subscriber is most likely to watch a trailer at least. Recommendation System like Alie with its number of data churning algorithms quickly understands the user’s choices and improves the overall content discovery experience.

If your content is targeted towards particular demography it’s always beneficial to consider the user traits of that demography such as - language, race, religion, and age. For example, if you are running a fitness-related app, it is important to consider the audience’s language, age, and other health parameters in your target demography. Alie provides pre-filters using which you can refine your recommendations for particular demography.