The adoption of video analytics solutions for streaming is growing at a rapid pace as the online video industry evolves and matures. Actionable video insights provide a crucial competitive edge in a time of steep competition between platforms, helping businesses improve their user experience and continue delivering growth.
In this comprehensive guide on video analytics for streaming, we examine essential aspects surrounding this integral part of modern streaming strategies. Join us as we dive into the core of what video analytics solutions are, the importance of Quality of Experience (QoE) and Quality of Service (QoS), and how to choose the right video analytics tool to meet your business’ needs.
What is video analytics?
Video analytics is a type of video measurement software that analyzes video streams to extract useful insights about the quality of the video playback and the viewer’s experience. It evaluates data points such as average bitrate, buffer ratio, join time, playtime, or in-stream errors to provide video streaming services with a precise picture of how their video content performs at the end-user level.
Thanks to video analytics, streaming providers can assess in real-time various aspects of Quality of Experience (QoE) and Quality of Service (QoS). These measure the viewer’s subjective opinion of a service, as well as the objective levels of service and network performance. Through the systematic interpretation of QoE and QoS metrics, streaming services can preemptively address potential issues and mitigate recurring ones, improving the overall viewer experience and satisfaction.
What is Quality of Experience (QoE) and Quality of Service (QoS)
Quality of Experience (QoE) refers to the subjective experience of your streaming service’s end user. This can be measured by tracking how video playback performance or UI/UX design impact user behavior, satisfaction, and tolerance. By monitoring QoE, you can understand how video buffering or certain app features affect your users’ behavior and respond to it.
Meanwhile, Quality of Service (QoS) refers to the monitoring of quality-related metrics such as throughput, errors, or latency across the entire content delivery chain — from ingestion to the end device. Tracking QoS helps you identify technical issues impacting your users’ experience and determine their root causes to improve platform performance and customer satisfaction.
Both QoE and QoS should be front and center in your efforts to measure and optimize your service’s quality. It is vital that you connect these two quality dimensions to minimize the financial impact of failures and proactively manage user satisfaction. For example, by measuring only the Quality of Service, you can evaluate the health of your infrastructure, but you cannot determine which of these issues might have an impact on the customer side of things. That’s an important distinction, as, often, apparently important Quality of Service issues have no impact on the end user and therefore are not a high priority. Equipped with both network and user information, you can identify the areas you should improve first and spend your money efficiently.
The need for video analytics: Why QoE and QoS are so important
As competition in the streaming industry intensifies, the quality of content alone is no longer the sole determining factor for success. A smooth, consistent, and high-quality streaming experience has become equally important. With so many services and content options available, anything falling short of a seamless viewing experience will cause your users to drop off and move on to your competitors. We are living in a viewers market, and that means ensuring a high-end QoE and QoS is a must.
Investing in QoE and QoS is a long-term strategy that requires continuous monitoring and improvement, but the rewards are long-lasting customer loyalty and competitive advantage. However, the impact of streaming quality can also be observed in the short term.
NPAW data shows that the quality of video streaming significantly influences user engagement. Our latest Video Streaming Industry Report showed that higher buffering times result in fewer minutes of video consumed per user, while higher video bitrates encourage viewers to watch more titles per day.
The key video analytics metrics for streaming
So, what are the key streaming quality metrics tracked by video analytics solutions?
There are several service, app performance, and user behavior metrics that can help you assess QoE and QoS and make the necessary adjustments in real-time. These need to be approached holistically, taking into account that they are all interconnected, each one of them constituting a piece of the streaming quality puzzle.
Key quality metrics include:
- Average bitrate: The basis of video quality, it measures the amount of video data transferred per second and is reflective of the video quality being sent to the end-user device
- Latency: the amount of time it takes for a single frame of video to transfer from the camera to the display. This delay can range widely, from several minutes to milliseconds, and is key to the streaming of live events like sports competitions
- Frame Rate: the number of images consecutively displayed each second. The higher the frame rate, the higher the quality and the better the experience
- Buffer Ratio: the time users experience buffering during content streaming. Buffering is when content stalls in the middle of playback due to a buffer underrun
- Join Time: a metric measuring the amount of time from when the video player is initiated (either via user action or by autoplay) to when the first video content frame is played.
- Exit Before Video Start (EBVS): represents video connection attempts without registered errors that have terminated before the first frame of the video has been displayed. EBVS is directly related to Join Time — the higher the Join Time, the higher the chances that the user will exit the video before it starts.
- Errors: there are many types of streaming errors causing streaming to crash that can be tracked. The main two types are start-up error crashes and in-stream error crashes
- Average Effective Playtime: refers to the aggregate number of hours being streamed on the platform. These hours are computed without considering the Join Time, Buffer Time, Ads Time, or Pause Time
- Average Completion rate: a percentage showing the number of plays that reached the end of the video. This metric is a good indicator of how satisfied your users are with a piece of content or your streaming experience throughout a single play
Download our white paper to learn all about measuring video streaming quality.
Why Google Analytics is not enough for video analysis
If your business revolves around online video streaming, then you need to be aware of the limitations of using Google Analytics alone to measure your streaming performance.
Google Analytics is a great tool for assessing website engagement, but it falls short in tackling video-specific metrics. The primary data it reports revolves around website visits, time on site, page views, or bounce rates instead of focusing on granular video data. Crucial video streaming metrics like buffering times, start failures, quality of experience, viewer engagement hours, or the user’s device type are not captured by Google Analytics. Hence, a video analytics solution becomes imperative for streaming providers to attain accurate metrics related to their video content.
In a nutshell, if you want to have a deep understanding of how your video content is performing and how your audience is engaging with it, supplementing or substituting Google Analytics with a dedicated video analytics solution would be a wise move. Video analytics paints a more comprehensive picture, opening the door to improved content, service, and strategies providing an invaluable competitive advantage in the fast-moving online video streaming market.
How to choose the right video analytics tool
Not all video analytics tools are equal, and you need to choose the right data platform for your business needs. Platform scalability, flexibility and customization, real-time data, and AI-powered insights are critical features that can help you make the most of your data to boost service performance.
Another crucial aspect when it comes to video analytics for streaming is making sure you are choosing a holistic analytics solution that covers your entire video business, with both video and application insights. Traditional analytics solutions that only focus on isolated aspects of the viewing experience are not sufficient, as pain points in both the app and video experience affect user satisfaction. Having a tool that correlates business and video insights also establishes one source of truth across teams and helps improve efficiencies and interdepartmental synergies.
Data privacy and security are also of critical importance in a time of tightening data regulations. When choosing a video analytics solution, you need to make sure the tool is compliant with GDPR and the latest laws for the protection of collected and analyzed personal data. Looking for a provider that is ISO 27001 or ISO 27701 certified is a great way of ensuring that.
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