Video call quality has become business-critical
This past year has made it abundantly clear how fragile and finnicky video calls can be. Odds are, you too have been on countless calls where someone’s audio was garbled or cut out or their video froze.
It’s not so bad when your video quality falls off a cliff with friends on a virtual happy hour, but it’s downright painful when it’s your sales person trying give someone a demo or your support person helping an important customer — or whatever calls are most important for your organization. Video conferencing platforms like Zoom, Microsoft Teams and BlueJeans have become one of the most important applications a business runs.
We all know video call quality is a challenge, but the cause of the problem and the solution have been a bit more elusive. It can be easy to think that it’s a problem with the platform itself, the individual computer, or that you need to pay your ISP for more bandwidth. Those are rarely the problem, though.
Adding bandwidth doesn’t solve video quality issues
It might seem logical, but anyone who’s tried increasing their bandwidth to end call quality issues learns that’s not the ultimate solution. With video and VoIP calls, capacity isn’t the problem. Rather, it’s almost always issues like packet loss, jitter and latency.
The answer is ISP diversity and intelligent software built for site-to-cloud environments
To improve the underlying issues that impact video and audio quality — packet loss, jitter and latency — what you really need is ISP diversity and intelligent technology that will automatically manage your traffic to take advantage of your multiple circuits and ensure your sensitive traffic isn’t degraded by ISP congestion. With more than one internet connection, your traffic can automatically be identified, prioritized, and routed down the best path at any given moment. And whether you have one internet connection or two or more, your most sensitive and important traffic (e.g. video calls) can be prioritized over everything else with dynamic QoS.
Testing it out
We’ve heard from many of our customers that Bigleaf solves their video call issues — and we know it’s made a huge difference for our own company, because we have Bigleaf in our office and homes — but it’s not always clear why. So, we took a look at some data to help illustrate what Bigleaf does that improves video call quality.
To do that, we used the statistics dashboard within Microsoft Teams and did a side-by-side comparison. We held meetings with Microsoft Teams for over two weeks and collected all the performance data to see how things worked with Bigleaf doing what it does best. Then, a courageous Bigleaf employee disabled their Bigleaf device to collect the performance data for Microsoft Teams video calls without Bigleaf.
The difference was obvious — and painful — for that employee. In several meetings, their video calls were effectively unusable. No one could understand them, they appeared pixelated, and the audio cut out so they couldn’t understand what other people were saying. The quality was so noticeably worse that they couldn’t stand running that test as long, but they still collected five days of data of using Microsoft Teams without Bigleaf.
What the data looked like with an unoptimized internet connection
When you’re experiencing audio and video quality issues with some of your video calls, what’s happening behind the scenes? Here is the data from using Microsoft Teams with Bigleaf disabled:
|Metric from Microsoft Teams||Result without Bigleaf|
|Average video frame rate||18.5 frames per second|
|Average video low frame rate call percentage (the average percentage of call time where the frame rate is less than 7.5 frames per second)||44.6%|
|Average video local frame loss percentage (the average percentage of video frames lost as displayed to the user for streams)||27.5%|
|Average audio degradation (average network Mean Opinion Score degradation for streams, which represents how much the network loss and jitter have impacted the quality of received audio.)||0.55|
|Average overall network MOS (average network Mean Opinion Score for streams, which represents the average predicted quality of received audio factoring in network loss, jitter, and codec.)||3.74|
|Average packet loss||0.017|
A few things to point out here:
- Of all the time they were on a video call, 44.6% of the time — nearly half — their video frame rate was less than 7.5 frames per second. For comparison, the frame rate you will see on TV and in movies is typically 24, 30 or 60 frames per second.
- That MOS of 3.74 puts it into “fair” territory.
What the data looked like with Bigleaf
How did things look with Bigleaf in place? Here’s the data:
|Metric from Microsoft Teams||Result with Bigleaf|
|Average video frame rate||20.6 frames per second|
|Average video low frame rate call percentage (the average percentage of call time where the frame rate is less than 7.5 frames per second)||2.3%|
|Average video local frame loss percentage (the average percentage of video frames lost as displayed to the user for streams)||7.3%|
|Average audio degradation (average network Mean Opinion Score degradation for streams, which represents how much the network loss and jitter have impacted the quality of received audio.)||0.27|
|Average overall network MOS (average network Mean Opinion Score for streams, which represents the average predicted quality of received audio factoring in network loss, jitter, and codec.)||4.02|
|Average packet loss||0.01|
The Bigleaf difference
Putting that all together, here’s what things looked like before and after Bigleaf, and what that difference was.
|Metric from Microsoft Teams||Result without Bigleaf||Result with Bigleaf||Improvement with Bigleaf|
|Average video frame rate||18.5 frames per second||20.6 frames per second||11%|
|Average video low frame rate call percentage||44.6%||2.3%||95%|
|Average video local frame loss percentage||27.5%||7.3%||73%|
|Average audio degradation||0.55||0.27||51%|
|Average overall network MOS||3.74||4.02||28%|
|Average packet loss||0.017||0.01||41%|
Bigleaf optimizes ISP diversity and makes it simple
Historically, the technology used to make multiple internet connections work like one has been very expensive and complicated to set up.
Bigleaf changed all this. It’s as simple as connecting our plug-and-play router and letting the intelligent software automatically detect and adapt to internet performance and connectivity issues to keep your business-critical applications running smoothly.
Your most important traffic will automatically be prioritized and delivered over the best possible circuit at any given time. When one of your internet circuits has an outage, your applications will seamlessly failover to your other circuit because your IP address changing. This ensures that your applications won’t drop. And thanks to Bigleaf’s owned and operated Cloud Access Network, your traffic will never hit the open internet unprotected.
See the difference for yourself
If you use Microsoft Teams and Bigleaf and would like to replicate the test we did above, you can set up the Call Quality Dashboard following the instructions here to access all the data. And then you can unplug your Bigleaf device for as long as you can stand to compare your call quality stats with and without it. Honestly, we can’t say we recommend that part, though.
Better yet, check out your Bigleaf dashboard to see how much uptime you’ve gained and what Bigleaf has been doing to improve your internet connection and the quality of your voice and video calls, and all the other applications you rely on. You can see how many minutes or hours of additional internet uptime you’ve had thanks to Bigleaf, as well as how many minutes or hours you didn’t have degraded network performance or significant network problems that would have caused symptoms such as dropped calls.
Want to learn more about how Bigleaf could help your company or your clients? Contact us.