Increase Viewership With Better Search And Content Results
As the demand for over-the-top (OTT) video streaming services continues to rise, service providers are focusing on delivering personalized content, search functionalities, and recommendations to keep users engaged and satisfied. By leveraging sophisticated algorithms and data analysis techniques, OTT video streaming services can deliver highly personalized content recommendations and effective search results to each individual viewer, which can ultimately lead to increased engagement, retention, and revenue.
Increase streaming minutes with content personalization
Personalized content recommendations are one of the key features that enhance the OTT video streaming experience. Netflix is a prime example of a company that uses machine learning models to analyze the viewing history of users, the time of day, the device being used, and the user's location to predict what the user is likely to watch next and suggest relevant content. Netflix has reported that 80% of what its users watch is based on algorithmic recommendations, demonstrating the importance of content personalization to viewers.
Disney+ uses a "myriad of data points" and leverages machine learning to analyze user data and personalize content recommendations that aligns with the viewer's interests. Search and recommendations play a critical role in enhancing the OTT video viewing experience.
Keep your subscribers engaged with more relevant results
Effective search functionalities are also crucial for OTT video services to enable users to easily find content that matches their interests. Users can search for specific titles, actors, genres, and other criteria to find content that aligns with their preferences. Sometimes search responses are not fast enough to keep viewers interested - especially when they can’t find new or relevant content. The search functionality can also be enhanced with machine learning algorithms that analyze user queries and provide more accurate results.
Hyper distributed cloud for OTT Services
With its distributed architecture, Macrometa provides faster access to data by bringing compute resources closer to end-users, reducing latency and improving response times. Unlike a centralized cloud, which can become a bottleneck when handling large amounts of data traffic, Macrometa's hyper distributed cloud platform allows for easy scaling and high availability of data across multiple regions. This ensures that users can access data and content faster, even during peak usage times.
The platform includes advanced search functionality, which enables users to quickly and efficiently query large datasets using a range of search parameters. This makes it an ideal solution for OTT video service providers looking to manage and analyze large amounts of data in real-time.
In addition to its advanced search functionality, Macrometa's hyper distributed cloud platform can provide recommendation capabilities that leverage machine learning and data analysis techniques to provide highly personalized content recommendations to each individual viewer. By analyzing user viewing habits, preferences, and other data points, Macrometa can enable OTT services to suggest content that is relevant and engaging, keeping viewers satisfied and more likely to continue using their service.
Learn more today!
In today's fast-paced world, viewers have limited attention spans and won't wait for slow search or recommendation results. To keep them engaged and prevent them from leaving, OTT services need to use advanced search and real-time analytics and algorithms to provide them with accurate content recommendations. Contact a solutions expert to learn how Macrometa can help to speed up recommendations and searches and reduce administration time and costs.