Digital age consumers expect businesses to know their choices, likes and dislikes and tailor services or products according to their preferences. Most global brands nowadays are focusing on personalizing customer experience to gain maximum user engagement on their platforms. The streaming industry has rapidly grown and has quickly acquired the limelight in the marketplace. It provides us almost unlimited content in an affordable monthly, quarterly, or annual subscription plan. With remote work culture cutting down the commute time of employees, most of the individuals are spending much time watching content online on different OTT platforms. Here comes the need of personalized recommendations for streaming industry. To become a top player in the streaming industry a platform needs to provide personalized recommendations according to the preferences and interests of a user.
However, users often demonstrate unpredictable streaming patterns which are tough to capture just through a manual survey. Different users have different tastes depending upon their demographics, personalities, cultural differences, and recommending content matching all these parameters can quickly become a complex task.
A Recommendation Engine is a set of algorithms that interfaces with existing content and sorts content according to the titles and prioritizes content based on the user’s interests.
Importance of personalized recommendations for streaming industry
As the name suggests, personalization means one on one experience, where all offerings are tailored according to user behavior and interactions. Delivering a personalized experience makes users feel special and valuable as well as allows them to feel that the service is exclusively designed for them and as a result it improves organic engagement.
Integration and application of recommendation engines have been bringing billions of revenues to streaming businesses. With different types of filtering such as content, collaborative and hybrid, the pace of doing business is changing. Today, most of the popular OTT platforms such as Netflix, YouTube, and Spotify are using recommendation systems. This is helping customers get a better value for their buck. With the advancement in machine learning, we can securely articulate, it will make customer retention and loyalty better than ever.
It is also vital for OTT platforms to integrate recommendation engines because it helps users navigate through a content catalog efficiently. The recommender system will build a persona for every user based on the interaction with the service, their choice of content as well as extensive metadata.
Suggest the Right content at the right time to your audience
Content is powerful and it has the power to make or break the overall experience and relationship of a user with your platform. When you suggest the right content at the right time it will help increase customer engagement on your platform and also enhance the user experience significantly.
Benefits of using content recommendation system for the streaming industry
Augmented content consumption –
Users are completely unaware of what to watch next. They always rely upon recommendations from social media or read online reviews to know what to watch online. A recommendation system helps users watch content that they wouldn’t have considered before! As a result, streaming businesses can easily boost content consumption and drive revenues via the subscription model.
Enhanced catalog finding –
It’s obvious that users always don’t know what they want and the recommendation system allows users to watch movies that they wouldn’t have searched for. The recommendation is nothing but a content discovery procedure and by identifying a user’s profile, an OTT platform can suggest movies and guide the user to find out more content in the catalog or library.
Retargeting Users –
Using recommendation system streaming platforms can also feed content suggestions through notifications, emails, social media feeds and re-target users via different channels. It acts as a game-changer in marketing campaigns and helps drive engagement.
The use of personalized recommendations in the OTT industry is limitless. It offers a personalized experience to users while browsing their favorite streaming media platform. Personalized experience makes users feel special and valuable and in turn brings more revenue to businesses.
Improve user engagement with Alie’s Personalized recommendations
Alie is a recommendation system that is designed to provide users a personalized experience by suggesting their preferred content on their favorite streaming platform. It is AI-powered and its unique machine learning algorithms are intended to analyze users’ data and recommend personalized content in real-time. Start a 14-days free trial and gain insights on how it can help your business offer a personalized experience to end-users.