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流媒体分析:重点跟踪

了解更多关于流媒体分析的信息 流媒体东部.

阅读这段录音的完整文本:

史蒂夫·盖革: Key points to track in making your decisions about video preparation. Screen resolutions and those being presented based on the playback experiences are a core piece of this, 当我谈到这个的时候, the thing that I will really want everyone to focus on is that it's best to look at your data. Industry benchmarks will give you a good idea of directionally where to go but when you collect that via your own analytics tooling, when you pull in your own data you'll start to see the deviations that you have from those industry standards. 这意味着你的表现会有很大的不同, in your savings ultimately when you start to make decisions based off of that.

So the core thing here is don't encode resolutions that your users can't benefit from. So here we don't see really any 4K utilization so let's not produce any 4K renditions or serve those up to these customers. Scale factor is another thing that a lot of people don't consider but is a relatively important one. Really what we're looking at here is what resolution was delivered versus the detected resolution of the playback. And again, you're optimally going to match this and have no scale factor. If you're scaling video down that means that you're potentially wasting bits, 你有一个比你需要提供的更高的分辨率. Scaling video up means that your users aren't getting the ideal experience. 现在, 对此有一些警告, and sometimes you do want to be in a situation where you're scaling down video. But as a general rule, you want to really try and aim for this whenever it is possible.

Lastly we're going to take a look at bit rate in two different ways. 第一,不要生成用户无法观看的视频. You obviously have a pretty even trend here around that 900 kilobit mark here, so producing a three or four megabit rendition isn't going to do your users very much good; they'll never adapt up to it. You should also look at what we call a heat map or a density graph of what people are watching over time and look at the distribution of your users across those renditions.

So here in a different situation we have about a quarter of our viewers hitting the highest rendition of 4.8位, and we have folks that are going to be down into the 800 to 400 kilobits range, but there's this kind of odd stripe in the middle of that in this case we can track back down to zero rated or cap data plans. So there was a gap there in which we weren't going to have any viewership of that 1.21 megabit so maybe that's not something that you needed to produce.

So, ultimately I want to come back to one of the things that I mentioned earlier which is video codec support, 另一件你可以从分析中得到的东西. And here again the pervasiveness of AVC so great everybody can receive that. HEVC为19%,VP9为74%,AV1为55%. So the interesting fact here is if you remember what the plans were and what people were implementing again in a general rule is that they were doing way more HEVC than they were VP9. 但当你开始剥离数据并深入研究时, the actual addressable market for those codecs might be a little different.

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