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Curious about how your favourite streaming platforms work? It's not just about the content, it's about the tech behind the scenes. From AI-driven recommendations that know exactly what you want to watch, to smart compression and delivery systems that keep your streams smooth and crisp, cutting-edge technology is changing the game.
Let’s understand how to improve the video streaming with scalable delivery systems, real-time analytics and how to keep the streams smooth and sharp, ensuring they look great on any screen:
Compression methods using codecs like AV1 efficiently reduce video file sizes while maintaining quality. AV1 does this by analysing video data to find patterns and redundancies, such as storing only differences between similar frames. It also uses techniques like prediction and transformation to make data more compact. This results in smaller file sizes and high-quality videos, benefiting both streaming and storage.
Compression methods can be broadly categorized into two types: lossy and lossless. Each type has different techniques and applications.
1. Lossy compression
Lossy compression reduces file size by removing some of the data, which can lead to a loss of quality. It is often used for media where perfect fidelity is less critical.
2. Lossless compression
Lossless compression reduces file size without losing any data, ensuring that the original quality is preserved.
3. Hybrid methods
Some codecs use a combination of lossy and lossless techniques to achieve a balance between quality and file size:
To understand more about codecs and containers, read here.
Per-title encoding is a video compression method used by platforms like Netflix to improve streaming quality. Instead of using the same settings for all content, it adjusts compression based on each video's unique features, such as motion and resolution. For instance, a high-motion action film needs higher bitrates for clarity, while a slow-paced documentary can use lower bitrates. This approach has led to up to a 20% improvement in video quality and helps reduce bandwidth and storage costs by optimizing settings for each title.
Digital Rights Management (DRM) protects digital content from unauthorized access and piracy, helping creators and distributors control their intellectual property. DRM uses encryption to secure content and licensing to manage access and sharing.
For example, Netflix’s DRM adjusts access based on location or subscription tier. DRM has proven effective, reducing illegal downloads by up to 30% and contributing to increased revenue, with global box office revenue reaching $42.5 billion in 2022 partly due to DRM. DRM employs encryption (like AES-128), secure key exchange, and digital watermarking to prevent unauthorized distribution.
To understand more about DRM, read on here.
Content Delivery Networks (CDNs) are essential for successful OTT streaming in the US, providing both technical efficiency and cost benefits. CDNs distribute content across multiple servers located around the country, ensuring users receive content from the nearest server to reduce latency and buffering. For example, CDNs can handle millions of users and traffic spikes, such as during the Super Bowl, with speeds up to 60 terabits per second. They can cut streaming latency by 50% and improve video quality by 25%. CDNs use technologies like adaptive bitrate streaming, which adjusts video quality based on internet speed, and edge caching to enhance performance.
For more details on CDNs, check here.
A 2023 Deloitte report found that OTT platforms using advanced analytics experienced a 25% increase in user retention and a 20% boost in content recommendation accuracy. McKinsey's study showed personalized recommendations can increase viewing time by 30%. Fastpix analytics tools offer real-time data to optimize streaming quality and user experience.
Click here to read more details about video analytics.
Netflix uses Quality of Experience (QoE) to ensure a smooth and enjoyable streaming service. By analysing data on buffering, video resolution, and playback, Netflix adjusts streaming quality based on internet speed and device capabilities to prevent issues and maintain high satisfaction.
There are different types of factors related to QoE (Quality of Experience) that you should be aware of:
The image presents analytics on video quality and device usage from one of our recent tests with a regional OTT platform built with FastPix APIs. It shows a bar graph illustrating daily video resolution consumption, categorized into four ranges: up to 720p, 720p to 1080p, 1080p to 1440p, and above 1440p. There is a peak in consumption on September 2, particularly for resolutions between 1080p to 1440p and above 1440p.
The pie chart shows the views by device, where Android devices dominate with 62.45% (301 views) followed by desktop at 36.31% (175 views) while tablets and iOS contribute minimal fractions (0.62% and 0.41%, respectively). This serves to help users track video resolution and device analytics enabling them to optimize performance and costs based on user engagement.
It shows a video performance analytics dashboard highlighting several key metrics including a Quality of Experience (QoE) rating of 70/100 with individual scores for Playback success (77), Startup time (62), Smoothness (54), and Video quality (72). Key metrics also reveal a Playback failure percentage of 4.36%, video startup failure percentage of 0.16%, a buffer ratio of 41.07%, a video startup time of 0.26 seconds, and an average bitrate of 3.21 Mbps. Error analytics shows a total error percentage of 4.36% across 1,927 views, with error rates of 2.24% on the web, 4.69% on Android, and 33.33% on iOS.
To address such issues and improve QoE scores for enhanced video performance ultimately leading to better user experiences and higher engagement, consider exploring the guide on video optimization for the web.
It shows a video analytics dashboard that visualizes content performance over time. On the left, Views Analytics by Time/Day displays the distribution of video views throughout various days and hours. Darker shades indicate higher engagement periods. The right section lists "Top Performing Content" by views highlighting the most popular videos. The overall layout offers a quick snapshot of key content performance metrics making it easy to identify peak engagement and top-performing videos.
However, while these technologies lay a solid foundation, they are not enough on their own. To truly elevate your streaming service, integrating AI features are essential. AI can optimize content delivery, personalize user experiences, and streamline operations, propelling your OTT platform to new heights. To stay ahead in the competitive streaming landscape, you need to embrace both the core technologies and the transformation that AI can bring in.
Some streaming services seem to know exactly what you want to watch. All thanks to AI. From personalized recommendations to smooth, high-quality streams, AI and machine learning is making your viewing experience better than ever.
Personalized content recommendations with AI are all about using technology to suggest things you might like based on your past behaviour and preferences.
Let’s have a look on how this process works:
1. User data is collected
AI systems start by gathering information about you. This includes what you have liked, watched, or interacted with before. For example, if you often watch action movies, the system notices that.
2. Individual data gets processed
The collected data is then organized and analysed to understand your preferences. For example, if you like thrillers, the system learns that thrillers are your favourite.
3. Generating recommendations
Based on what the AI has learned, it creates a list of suggestions for you. If it knows you love action movies, it might recommend a new action movie you have not seen yet.
4. Feedback loop
After you interact with the recommendations (like watching or skipping them), the AI learns from this feedback to improve its suggestions in the future.
Content moderation, especially when dealing with NSFW (Not Safe for Work) content or profanity, is all about making sure that what people see online is appropriate and respectful.
When you search for videos online, there is a complex system working behind the scenes to find and show you the most relevant results.
Video summarization is the process of creating a shorter version of a video that captures its main points or highlights. This can be useful for quickly understanding the content without watching the entire video.
1. Video analysis
2. Content selection
3. Summarization techniques
4. Audio analysis
5. Summary generation
6. Feedback and improvement
Video chapters are a way to organize and navigate through different sections of a video, making it easier for viewers to find specific parts they are interested in.
Understanding video chapters
Creating chapters
Chapter metadata
Integrating chapters
Feedck and refinement
Content classification is the process of sorting and organizing content into different categories based on its characteristics. This can be applied to various types of content, including text, images, videos, and more.
Content classification streamlines content management by ensuring that audiences can easily access and discover the material that interests them. It involves several key processes:
Data collection: Gathers the information about the content, including titles, descriptions, genres, and viewer ratings.
Metadata tagging: Applies the tags to the content based on key characteristics, such as genre, themes, and target audience.
Algorithm analysis: Uses machine learning algorithms to analyse the content and automatically classify it. This may include natural language processing for scripts or image recognition for visuals.
Manual review: Ensures human moderators to review and refine classifications to ensure accuracy, especially for complex content.
Continuous learning: Updates the classification system regularly based on viewer feedback and viewing patterns to improve recommendations and accuracy.
User interaction: Allows users to filter or search for content based on classifications, enhancing their experience.
Click here to read our detailed blog on video classification with AI.
FastPix provides the technical infrastructure needed to support your OTT venture, offering advanced features like scalable storage, high-performance content delivery networks (CDNs), and seamless adaptive streaming. We can efficiently manage and store large volumes of content, ensuring that your platform can grow with increasing demand. Our high-performance multi-CDN networks minimize latency and provide fast, reliable access to your content globally, enhancing the user experience by reducing buffering and interruptions.
Additionally, FastPix’s seamless adaptive streaming technology ensures that your content is delivered in the best possible quality, regardless of the viewer’s internet speed or device. This adaptability is crucial for maintaining a smooth viewing experience, which is a key factor in user satisfaction and retention.
Moreover, with our video search and AI features, you can enhance content discovery and user interaction. This technology helps viewers find what they want quickly and easily. For more details, click here.
In-short our APIs reduce the time to market while you build your OTT platform. Getting started with FastPix will help you stay competitive in a crowded market, attract and retain viewers, and position your streaming service for long-term success.
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