According to the Internet Movie Database (aka IMDB), in May 2019 there were almost 6 million titles, including the episodes. If an average movie’s length is 60 minutes, a human being needs 6,000,000 hours or almost 685 years to watch them all. According to Stephen Follows website specializing in analyzing cinema- and movie-specific stats, in 2016 there were 736 films released in US cinemas, and that number keeps on increasing every year.
All these figures mean that it’s a real pain to find an interesting film to watch in the evening as it can take hours just to browse through a tiny piece of IMDB synopses. Of course, there are various sources housing movie and series reviews from reputable critics. But what is liked by others not always fits you.
Here we arrived at an important problem of the Content Era: how to get a reliable recommendation from those people you can trust?
One of the solutions to this problem is to use a movie rating recommendation site like Rotten Tomatoes or alike. The thing is that recommendations there are from people you don’t know and, respectively, you cannot trust their movie taste.
Our client elaborated the concept and vision of a software that would help to solve this problem and tasked DIGIS with its practical implementation. The client’s idea was to create a movie recommendations platform where you can discover great movies suitable for your likings from people you trust, that is from your friends, and that’s how Raters App was brought to life. DIGIS took a substantial part in the implementation of the Raters cognitive movie recommendation app.
The client wanted to provide the platform users with a sleek interface showing recommendations from other users. DIGIS has implemented this feature by building the Timeline. Similar to the analogous feature available in Facebook, Raters Timeline displays the history of recommendations for the movies you can like. It also shows activity of the user’s friends, i.e. which movies they rated/liked. Timeline provides the users with appropriate options to save the title for further watching or add the user’s own review on the movie.
One of the key features of the recommendations service is to be able to find a potentially interesting content by certain attributes. This why the client asked, and we added, a possibility to search for movies by their genre: Thriller, Horror, Comedy, Drama etc. The user chooses the genre and Raters brings to the screen the list of the highest rated movies of the selected genre. Thanks to the added internal connectivity with IMDB and Rotten Tomatoes, the search may cover their whole listings.
One of the most essential requirements of our client was to combine the movie recommender system with the social functions. The client wanted to provide users with the possibility to get opinions from people they trust most, i.e. their friends. Therefore, DIGIS implemented Facebook integration for the movie recommendations app, and now Raters user, after linking their FB accounts, are able to check out what their FB friends are up to in terms of movies.
The users can also make friends with other users of the Raters platform in order to get more accurate recommendations from a wider group of people.
Everyone likes to know when their favorite shows are on air or when new episodes of the top series are released. Exactly for this purpose we enriched Raters movie recommendation app with reminders and push notifications. Now, the users are reminded about air dates and times of the selected movies or series. The users also get push notifications informing them that their friends have just watched and rated some film.
We added AI+ML support to make the recommendations more targeted and accurate. The movie recommendation system learns what users like and what their friends like and adjusts their Timelines accordingly. The platform utilizes AI to provide users with better selections of films. AI algorithms also make in-platform search faster and flexible, when needed.
People like to share their good feelings with friends or other people. So we made Raters the world’s first platform to recommend films to two or more people. What a user needs to do when hunting for a movie to watch is just to tag a friend and they will now both receive recommendations for those movies they are likely to enjoy.
This movie recommendation system case study was drafted to familiarize potential customers with the key features of a good movie recommendations software. Before commencing the project our client and us analyzed multiple opinions of users of the competitor recommendations platform in order to build a product that would be free of all user-specified disadvantages. We wanted - and, in fact, managed - to create a solution that would ensure an unprecedented degree of recommendations targeting and confidence, making the full use of the users’ social network profiles. We also added AI+ML functionality to allow for the platform self-development and improvement through proprietary algorithms. As a result, the Raters platform, according to our client, is a one-of-the-kind product that ensures extreme user experience by providing virtually 100% accurate recommendations on the movies.
DIGIS welcomes businesses and individuals flirting with the idea to build a recommendations platform, to reach out to us for receiving a comprehensive assistance relative to the actions needed to create a superior quality and monetizable recommendations solution.