What streaming metrics define success of your platform?
Demand for streaming platforms has risen massively over the last few years. Over the last few years, companies such as Netflix, Amazon Prime, HBO, and Hulu have witnessed an increase in customers. Many traditional companies who had been ruling Television have also jumped on the digital bandwagon such as ESPN, NBC, and Sony. The concept of “cord-cutting,” which entails getting rid of your cable and replacing it with online video streaming subscription services, has become a phenomenon. Multiple big players are today now investing their time and resources into producing a high-quality live stream, thus it is an only logical step to start tracking some live streaming metrics that are expected to help you determine how successful the whole process is. You might also discover opportunities you hadn’t considered before. It also can help you figure out sections that need improvement or just be sure that you are on right track based on your data analysis. So in order to help you out, we have made a list of all the streaming metrics you should keep your eyes on if you are in this domain in order to measure your success-
Bit rate is perhaps the most important streaming metric to track because it allows you to gauge the quality of the video your users are watching. A higher average bit rate indicates a higher image quality. The bit rate specifies how many bits of video can be transmitted in a given amount of time. HDTV can have a bit rate of 8 to 15 Mbps, while standard-definition television has a bit rate of 3.5 Mbps. Netflix Super HD streams at a speed of approximately 6 Mbps. A higher bitrate in video allows for higher image quality in video output. Standard-definition video is typically 1-6 megabits per second, while high-quality web video is around 2 megabits per second. Kilobits per second, or kbps, is a common unit of measurement for mobile video.
A buffer is a type of temporary memory storage that stores data while it is being transferred from one location to another. It’s similar to an integer array. The fill method of the Buffer class inserts data into the buffer instance. If no offset or end value is specified, the entire buffer will be filled. This is significant because you want to know how long your users have to wait for a video to begin playing. They may leave before even a frame flashes on their retinas if they stare at that rotating circle for too long.
Due to extreme network congestion or insufficient processing power, lag is a slang term for a noticeable decrease in application speed. When network capacity is exceeded, the network forces a program to wait before sending or receiving data. The video will automatically start playing once the buffer is full. The viewer can watch the video at this point if the streaming is smooth and there is a good balance between download rate and bit rate. This, however, may not always be the case. The buffering can sometimes become excessive, and the playback will come to a halt. The amount of time you wait for the video to buffer before it starts playing is referred to as lag length. This streaming metric aids in the comprehension of the user’s experience as they begin to watch a video. The lag should not be much longer than the buffer fill time, but if it is, the video streaming quality is extremely poor and requires further investigation.
It refers to the total amount of data consumed by the viewer during the video streaming, which includes every second, minute, and hour. The importance of this value is quite high in order to comprehend and plan streaming infrastructure and capacity intake. You can make a rough estimate of the overall demand for the streamed data using play length. These data volumes are extremely useful in determining whether or not content quality requires improvement. This live streaming metric is also extremely useful for monetization, particularly in the advertising industry. Advertisers have a dire interest in placing ads if a large number of people are watching for an extended period of time, as their ads will most likely be strewn throughout the show.
When you have issues with network contention or an overloaded server, the player may run out of data at some point during the video’s playback, so it will pause and wait for data to be buffered. This has a negative impact on your user experience, so make sure this lag time is acceptable in terms of your SLA. Waiting time is technically referred to as lag ratio, and it is calculated by dividing the total waiting time in the video by the total time spent watching it. Even if there is never a single buffer through the video, the lag ratio is never zero because the initial buffer fill that occurs before the video starts remains. All efforts should be made, however, to keep the lag ratio as low as possible. Consider how many times you waited through the buffer period when you last watched a video. Three minutes of buffer time results in a lag ratio of 2.5 percent.
Desktop computers are being used less frequently to watch live streams these days, with mobile and OTT devices (such as ROKU and Apple TV) becoming more popular. Knowing how your audience watches can help you decide what to emphasise in your broadcast.
Some supplemental live stream content, such as a Twitter feed or a live sports data feed, for example, does not always translate well to mobile devices. If 80% of your viewers are watching your live stream on a mobile or OTT device, they may be missing out on an important part of the show. Knowing this, you can concentrate your efforts on getting as much of the supplemental information onto the video itself as possible, ensuring that your mobile and OTT viewers get everything they require to fully enjoy the experience. Furthermore, with more mobile viewers, you may want to consider lowering the stream’s quality. Mobile users have less bandwidth to work with, which means they’re more likely to experience buffering issues. Examining this live streaming metric is simply good practise for knowing where your viewers are, aside from those practical applications.
Consumers have certain expectations out streaming services, it is really important for platforms to focus on availability, consistency and high-quality. These factors are extremely crucial for any successful platform and requires a well-functioning data centre, high-throughput along with resilient networks and also consumer devices which are capable of handling both the video and other aspects. However, you don’t always get all of that, which is why technologies like Adaptive Bitrate Streaming were created. When the viewer’s device can’t receive or process the video fast enough, the server lowers the quality of the video it’s streaming. That’s why, if the quality of a video drops because your computer is busy with a virus scan, for example, that’s what’s going on. To ensure that the viewer’s video is not interrupted, the bit rate is adapting – it is being reduced. When adaptive bitrate streaming technologies are used, most load testing tools are unable to accurately measure the streaming metrics outlined above. So, even if your customers aren’t experiencing playback issues, they may be annoyed by fuzzy frames and muffled colours.
Consider the customer experience when they encounter poor video streaming performance and how much a brand can be harmed by it. Consumers abandon an online video if it does not load in two seconds, according to a survey conducted by UMASS Amherst. A disgruntled customer will tell 9-15 people about their negative experience. Around 13% of dissatisfied customers tell more than 20 people about their bad experience. One way to prevent crashes are “Content Delivery Networks”. They help you efficiently divide the whole load on multiple servers thus making them more capable of handling large streaming loads on special occasions. Video CDN devices are a large geographical dispersed networks of servers that are highly capable of delivering high quality videos to web-connected devices in real time and on demand. These specialised video streaming server networks use caching to speed up delivery by temporarily storing content on multiple servers throughout the video CDN. When a viewer makes a request, the video is delivered by a server cached near the user’s location. CDN can thus help you reduce lag length and lag ratio providing your viewers with a better streaming experience. Videos also tend to buffer faster for the webpages that have their caches stored on CDN servers.
There are many such technological advancement that can help you improve user experience and thus eventually increasing the chances if your success. For a business all the above factors are extremely crucial to keep an eye on as they are the measuring factors
Mogi’s Superior Transcoding Technique
Mogi I/O (www.mogiio.com) is an AI enabled Video & Image Delivery SaaS that helps Content Platforms to Improve Customer Engagement by enabling Buffer free Streaming Experience for the user through a patented multi-CDN upstream architecture called Mogi Streaming Engine, Enhanced experience through quality enhancement and compression of up to 50% both during transcoding itself and Deeper user insights through Advanced Video Analytics.
Mogi’s solutions are available end-to-end (Video Transcoding + Video Player + Mogi Streaming Engine (Multi-CDN delivery) + DRM + Video Analytics) or you can use individual products from the entire suite like just the Video Transcoding. Mogi also provides white label end-to-end plug n play solutions for OTT and Edtech Platforms, with Web, Android and iOS apps as well as a dedicated CMS for OTT and LMS for EdTech.
One of the best individual products we have is our Transcoding Architecture, which in a unique cluster based process, does the transcoding within 30% of the content length. The transcoding architecture’s result includes a highly compressed video of up to 50% with no loss in quality, and if you choose quality enhancement, a 40% compression with enhanced video quality.
The pricing for Transcoding is very competitive as well, and along with it you get a highly compressed output with the same or higher quality. This means not only your contractual pricing is low due to competitive pricing, your bandwidth consumption reduces, and user experiences increases multifold. It’s a win win for all of us (Users, Clients, Mogi).
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