the power of data
Thanks for this opportunity to present key findings and implications we see for broadband service providers from our recent analysis of broadband data usage. The fourth quarter of 2022 saw the year-end with a continuation of the new post-pandemic normal: elevated usage of broadband for work, school, and entertainment, at ever-increasing rates. In addition, after the first full year of the FCC launched Affordable Connectivity Program, or ACP, to support low-income households connecting to the internet, we’ve observed a clear usage pattern among households enrolled in the program, which has impact for providers. Now, with more connected devices in the home than ever before, as well as the need for work from home, stream entertainment, bandwidth demands of VR and gaming, gaming, gaming, the surge and the need for broadband continues unremitted. Last year we’ve hit milestone after milestone. For example, Netflix reported 231 million subscribers, a 4% increase year over year.
Meanwhile, Disney+ reached 161.8 million, albeit that’s a quarterly drop, but still a huge jump of 25% year over year from 129.8 million. The Super Bowl hit a milestone as the third-biggest television program of all time. The only telecast to ever have a larger audience has been two other Super Bowls. The dollars spent to reach subscribers over broadband is staggering and the implications and responsibilities of service providers are greater than ever. Indeed, we’ve seen the outcome from significant growth in broadband consumption and the potential for congestion. Fortunately, there are solutions available such as the kind that OpenVault provides, that enable broadband providers to identify and proactively improve network performance and approach subscribers with an upgrade package that will improve their user experience while also improving ARPU for you. During this discussion, you’ll hear about both the insights we’ve had and solutions that can help broadband providers.
Hi, I’m Larry Siegel and I’ll be serving as your host on today’s webinar. I’m going to talk a bit about our role in developing this groundbreaking report and then turn it over to our CEO and founder, Mark Trudeau, who will take us on a deep dive into the key findings and their implications for broadband providers. Especially on how they can take the same views we have on usage data and leverage that for improving subscriber satisfaction while increasing revenue for you. As we go through our key findings, if you have any questions, use the Q&A box. I’m sure by now we all know how to do this. We’ll answer the questions we can and provide follow up if we don’t get to your question. Just a bit about us, OpenVault is the only cloud-based solutions provider focused exclusively on improving the value of broadband providers’ networks with quick to deploy business enhancing tools built upon our unique ability to capture and analyze actual network and subscriber usage data in real time.
With our deep domain knowledge, we perform data analytics on billions of usage and network data points so that our solutions enable providers to improve network performance, discover new and improve existing revenue streams and enhance subscriber satisfaction. We’ve delivered this for over 10 years for broadband providers in North America, Latin America, and Europe. Now for this report, our tools gather broadband usage data generated by over 150 broadband provider customers in North America, Latin America and Europe. We create a holistic pool of data across millions of subscriber data usage records into which we execute a series of powerful analytic queries ranging from overall usage, tiered usage, plan migrations and geographic characteristics. These then yield insights which have implications for broadband providers. We share these insights and their implications for providers with our quarterly OpenVault Broadband Insights report, or OVBI, which is available for download on our website @openvault.com. Now, to get into what we found in the final quarter of 2022 and how that compares year over year, here is our OpenVault founder and CEO, Mark Trudeau.
Great, thank you Larry. I appreciate it. I think today we have some unique things to present to you. For those of you that have attended our webinars in the past, you’ll see some of the same metrics that you’ve seen before, albeit updated with the latest data. But also a couple of interesting observations that we made here towards the end of 2022. So we’ll get into all that, but usage continues to grow. Again, no surprise, this is kind of a broken record in a way, but we’ll give you the details of what that looks like. Providers are continuing to have success moving subscribers to higher speed tiers and that’s resulting in higher average revenue per unit or ARPU.
So we’re going to shine a light on that a little bit as well as we always do with our power users and specifically looking at gig speed tiers and how the adoption of those speed tiers is rapidly accelerating. Then for the first time, we’re going to take a deeper dive into what happened throughout Christmas day. Whether that was something that we observed that’s unique to this year or in the past, we’ll talk about that. But interesting to start looking at these days like Christmas Day, the Super Bowls. So we’ve started to really take a deep dive into looking at the impacts on the broadband networks of usage behavior on those specific types of days. So you’ll hear a little bit about that as well.
Thank you, Mark. Let’s get you involved, you, the attendees, and we’re going to launch our first poll. With 2022 ending the year with record numbers in usage, and you’re going to see some of them, what is your number one concern? Is it data-driven network planning? Is it addressing congestion within existing networks? Is it improving revenue among existing subscribers or basically, are they all number one concerns? All of these are number one concerns followed by addressing congestion and then improving revenue and then a little data-driven network planning. Now we continue as we get into this, the big picture on usage here is at the end of ’22, usage growth due to multiple accelerators are bringing usage and migration to speed tiers higher and higher than ever observed. Now let’s get into those numbers. Finally, here we go back to Mark.
Okay, thank you, Larry. So what we wanted to do with this OVBI is take a little bit of a different approach. We always showed a little bit on trending and things. In this case we went back five years to say, “Hey, what did things look like five years ago versus today?” You could see that certainly while we might have grown only just less than 10% year over year in terms of average usage per household, we’ve more than doubled where we were just five years ago. So usage does continue to grow and if we continue at this rate, we’re going to see usage per household approaching 650 gigabytes by the end of 2023. So again, continued growth, albeit the percentages are lower than we’ve seen in the past, but that’s because we’re certainly working off bigger denominators now and bigger levels since Covid. So no real surprise here, but continued growth.
Now, one of the things many of you know we like to look at is we have two types of billing programs that we observe. One is what we’d call flat rate or unlimited billing or the all-you-can-eat type of package plans that operators put forth. Other operators have chosen to deploy what we call usage-based billing, where they assign usage quotas per speed tier, and we have many customers that do both. So we’re able to compare and contrast what the usage profiles look like between those types of billing plans and operators that offer those billing plans. So historically we’ve seen a pretty big gap between the unlimited or flat rate billing usage versus usage based billing operators, in terms of just usage per household. Historically, the flat rate billing has always shown much higher usage per household, which makes sense. They’re not inhibited by quotas, they’re all you can eat, subscribers are not worried about overage fees or anything like that.
What we’re seeing though is if you could see now in fourth quarter 2022, that gap that we’ve seen historically is actually shrinking. To where now those subscribers on usage-based billing plans or operators happen to be using and approaching the same levels that we’re seeing with flat rate billing. There’s a few explanations for that we think that I’ll get into here in a bit. But there you see the breakdown. So right about 600 gigabytes for the flat rate billing and 581. So there’s still a bit of a gap, but it has narrowed. In terms of median usage, again, we’re seeing a bit higher median usage than we are average usage, if you remember the 9.4% from a couple slides ago. So again, an indicator that all subscribers are moving up and using more. It’s not just a few abusive customers dragging up the average. The median is actually growing faster than the mean. So that’s what that tells us. Again, you see there the median usage of flat rate billing and usage based billing operators.
Again, we’re seeing less of a gap and a pretty big growth rate you see there on the right between fourth quarter of ’21 and fourth quarter of ’22 up to 390 gigabytes. Again, approaching more closely where what we see with the flat rate billing.
Thank you, Mark. Now let’s talk about power users or subscribers who consume one terabyte or more of data per month. They have a profound impact on the network. And power [inaudible 00:11:00] 22.4 while flat rate billing power users was 9.1%, as we talked about. The power user category itself has seen astonishing growth in the past six years. Now, back to Mark with little more detail.
Thank you, Larry. Again, as Larry points out, we’re seeing 10 times the percentage of subscribers that are exceeding a terabyte of usage than we saw just five years ago. So continued growth there. In terms of the one terabyte plus users, where it’s really astonishing is just the growth of two terabytes plus. So what we call our superpower users. Now we’re seeing 3.4% of all subscribers are accumulating over two terabytes of usage, which five years ago or 10 years ago would’ve been just unheard of to even think about. We continue to change the definition of what we deem to be a power user, but now we’re looking at that two terabyte and north. That category is growing clearly very, very rapidly.
Now, let’s talk about provision speed tiers. The migration from lower to higher provision speed tiers is accelerating and the need to move subscribers to higher speed plans, especially the ones who are creating speed clipping issues, have never been more important. But how do you identify these users? More on that later, but for now, back to Mark for a closer look on changes we observed on provision speed tiers.
Yeah, so this directly correlates with increase in usage and we’ve said this numerous times in the past, we’ve done a lot of analysis around the correlation between speeds and usage. While we’re talking about gig speeds and we know most subscribers can never consume that much data and they don’t really have a need for that speed, it’s oftentimes more of a marketing spin than anything. But increases in speeds, that does impact the consumption levels, and there’s many, many reasons for that. Higher-quality video can be served up if the bandwidth is available. What that’s going to do is chew up more data. So the individual subscribers’ usage behavior might not change, but they are going to be consuming more data just because of things like higher quality video that can be served by that faster speed. So what we’re seeing here is the adoption of gig service has just exploded. We’re seeing 26% of subscribers now with gig service versus 12.2 just a year ago. So operators are doing a great job promoting the service and they’re certainly getting a lot of adoption at the gig level.
On the other hand, what we also observe is just a continued reduction in the slower bandwidth, slower speed tiers. Not a surprise, many operators are automatically moving subscribers to faster speed tiers, not even necessarily requiring an upgrade or any change to the pricing or anything like that. Just taking away those lower speed tiers because there’s been, and we continue to do it with our analytics, a lot of analysis around how many of those subscribers that might have signed up a few years ago for service, they might have subscribed to something like a 50 megabit per second tier, which may have been fast back then, their usage behavior has changed. The number of devices connected to the internet within their home has exploded. Again, higher quality devices, all of these things contribute to the fact that they need more bandwidth and they might not even realize it now. We always like to talk about with Covid, one of the opportunities that we saw was we’ve never seen a change in usage behavior like we did during the Covid years.
Operators need to really look at those subscribers that are provisioned at slower speeds but are using and consuming a ton of data because they are all upgrade candidates. They’re all going to be happier customers if they move to a faster speed tier, and the operator can get more ARPU, average revenue per unit, out of them as well. So big opportunity, and with the change that occurred during Covid to use of behavior, it’s really important to shine a light on that for operators. Again, same theme here. You are seeing, and in fact, if you go to the next slide, Larry, this dovetails right into the next one where we’re seeing over a third of subscribers on usage-based billing plans adopt gig service versus only 13.9% on flat rate billing. So this goes back to the delta that we saw in the gap shrinking between total usage consumption of usage-based billing subscribers versus flat rate billing. Because of the correlation between speed and usage, what we’re seeing is a couple of things here. We’re seeing a bigger adoption of the faster speeds with UBB.
Part of the reason for that is a lot of operators who provide gig service and use that as an upgrade path, they provide unlimited usage even in a usage-based billing environment. If subscribers move to gig service, they either get an extremely high quota that’s not even reachable or they get totally unlimited consumption levels, whereas the slower speeds will provide a quota. So there’s a lot of motivation for operators on UBB structures to upgrade to that gig level, and they’re doing it clearly, one out of every three customers. That is the exact thing that’s driving a usage explosion among this group as well, because now they’re not afraid of quotas, of overage fees, everything else. When they upgrade to the gig service, they’re getting the faster speed typically without a quota. So the result is their usage because of those higher speeds is catching up to the users on flat rate billing plan. So that’s the biggest explanation for why the gap is closing.
I think historically we’ve seen a pretty good delta between usage based billing has tended to curtail usage amongst many subscribers over the years. But again, I think due to the rating schemes, due to the fact that gig service is so popular, typically because there’s no more quotas assigned through the gig service, that’s contributing to the adoption rate, which is therefore contributing to huge usage growth among the UBB subscribers.
Thank you, Mark. Now we’d like to take a pause, think about what we saw and take another poll. Based on all the migration to higher speed tiers and the heavier usage, which of the following would interest you if you could leverage software to boost capacity of your existing network, identify subscribers who can benefit most from upgrade packages, predict future specific network capacity issues, take targeted action to abusive subscribers causing network congestion or none of the above? Thank you for your thoughts and your insight on that. Now, if you’re interested in creating an OpenVault door, like the one behind this father and daughter, let us know. We can get you in touch with a woodworker that we know. Now, let’s take a broader look at broadband usage distribution over the past six years. Close your eyes and think about it. What would you expect to see? Well open your eyes and here we go, Mark.
I think what this area chart really does is it just shows us the change in distribution amongst these different usage level tiers over the years. So on the bottom, these are the bigger consumption, the power users and superpower users that we spoke about a few slides ago. You see those growing pretty rapidly now over the last few years where the other categories on the orange and the blue tend to be shrinking a bit. You’re seeing fewer and fewer subscribers fall into those lower usage categories, which really is great for the industry. It tells us just how essential broadband is and the fact that it’s just pervasive and everybody needs it and everybody’s actually using it. So that’s an interesting trend that we continue to look at this obviously, and we will continue to as we move forward. As I mentioned up front, we took a look this year at Christmas day specifically. The way this analysis started is we just had some questions around some events, the World Cup for example, other events and the impact on networks that is event driven or special day driven, like Christmas Day.
We decided to take a look at hourly usage throughout Christmas day and compare that to some of the previous. Christmas was on a Sunday this year. We compared it to the previous couple of Sundays just to look at how different the usage patterns were on Christmas day versus those previous Sundays. So Larry, you’ll want to pull that up. What we see here, the orange line depicts usage on Christmas day compared to the previous two Sundays. I think the big takeaway here is we started seeing pretty high usage being consumed, starting probably as early as 9:00, 10:00 AM in the morning. If you just think about it anecdotally, it makes sense. A lot of subscribers are opening gifts and a lot of internet connected devices getting connected at that time. There’s probably family video Zoom calls going on, et cetera, et cetera. So it was interesting to see that you’re almost approaching the peak curve as early as 10:00 AM on this particular day. We did go a few years back actually to look and see if this trend was the same every Christmas day and it turns out it was.
I think it’s important to shine a light on these types of events or special days so that operators have an idea of what to expect. It’s part of the whole ability to predict the future and predict what that peak data, peak curve is that operators will need to support as we move forward here. So speaking of that, obviously operators build their network to support the peak hours, and it’s important to look at what is the growth of peak hour. Now, this doesn’t show percentages or anything because every operator is different and they’re different for a couple of reasons. One, how much is usage growing per subscriber and per household, and how successful have they been adding subscribers? Obviously just because average usage might increase, if you’re not getting subscriber growth, you’re not really going to be growing your peak curve as much as if you’re doing both, where you’re seeing an increase in usage per household and your increase in the number of households that need to be supported on your network.
That in fact, has a multiplier effect of course, on what that peak usage curve looks like and what operators need to support. So every operator’s different. I certainly encourage operators that are on the webinar here to make sure you’re looking at that type of data. Looking at things like over subscription, looking at total peak curve, all of those types of things. You have a history of usage, we know where you’ve come from and where you are today. That’s going to give us an opportunity to predict the future and when you’re going to have peak hour issues and you’re going to have congestion, that’s how this whole point about data-driven network planning.
Thank you, Mark. Now we’ll move away from Christmas Day and talk about the Affordability Connectivity Program or ACP. Over a year ago in January of ’22, the FCC launched this program to support low income households. For those who aren’t aware of the details of this, the program provides a $30 per month or $75 for tribal households, a subsidy that can be applied toward a monthly internet subscription. The program has a budget of $14 billion and replaced a similar Emergency Broadband Benefit or EBB program, launched during the pandemic. OpenVault was able to observe user-behavior of several thousand ACP participants during ’22 providing insight into the impact of the program. Without a doubt, ACP participants are taking advantage of the program and their bandwidth usage exceeds that of the broader population in most categories. Why do we think that is and what have we seen? Let’s go back to Mark for a closer look.
Again, when we dissect the subscriber base of these operators, we’re able to really isolate certain categories. ACP being one of them, we thought it was interesting, we started looking at this a few months ago. Just how does their usage behavior change? How is it different than the average subscriber? So when we originally presented this, we saw a pretty significant increase or delta between usage levels, and frankly, it surprised us. We were surprised to see that ACP subscribers had a higher usage profile than the average subscriber. As you can see here at this bottom chart, it continues. We continue to see, in this case, 17% more average usage amongst ACP subscribers than we do the average population. We have some theories behind that, which we’ll talk about. But quite a bit of a delta, we’re seeing over 100 gigabyte delta between those categories. You can look at upstream and downstream as well there, but then Larry’s highlighting the median usage, which we’re seeing a big, big delta there. 531 gigabytes is the median for ACP customers.
That’s approaching the average for all customers that we observe. So very, very significant delta there that we’re going to have to continue to keep an eye on. So that operators that are really leveraging the ACP program, they just need to be careful that they understand what the implications are for their network. Now, we didn’t see the same growth rate. We saw about 5% growth. We’ve seen about 5% growth actually over the last six months. It’s similar growth rate that we’re seeing year over year average, but 5% increase in usage per ACP household, a bit higher percentage of power users on ACP, which is obviously contributing to the higher average usage. Significant usage there by those program customers. Here we look at the average household index, we’ve shown this a few times. Again, just back to the nearly 600 gigabytes per house. You see the downstream and upstream breakdown there. You also see the average speed, and this would be the weighted average speeds of the subscribers that we’re analyzing here for our customers.
415 megabits per second is the average downstream speed. So significant speed increases across the board for the subscribers that we track for our operator providers. So in conclusion here, the demand for greater speeds continues. You’re seeing a significant migration to 500 meg or gig service. Operators are doing a great job promoting that, and that’s resulting in a great take rate and higher usage as a result. Power users are growing significantly as well. We’re going to see 650 gigabytes or close to it by the end of 2023, there’s no doubt per household. Specific segments of customers are important. We talked about ACP, really important to understand the details at a granular level of usage behavior. A good example is we’ve had many operators that have had huge congestion on their networks that we’ve observed, but yet they’re out there promoting gig service, for example, and in areas that are really congested.
So it’s important to have full visibility into both subscriber usage and behavior, connect marketing programs and campaigns with network health, be able to visualize and see all this in one place so that you can make smarter decisions around prioritizing where to promote gig service, for example. Areas where you might have excess capacity, that’s where you want to sell it. Because if you’re out there selling and upgrading customers where they’re paying you more money, you have to deliver those speeds. That’s where operators can get themselves in a bit of a bind if they’re not careful. Again, the ACP stuff, looking at peak time consumption is really, really key. The holiday season, I will say that I talked about the Super Bowl, even though it’s not technically part of the fourth quarter 2022 report. We did take a look at it and while Christmas day was clear, we saw higher usage levels during certain hours. Interestingly enough, during the Super Bowl in our initial analysis, we’ve seen about 10% less usage data being consumed during the Super Bowl than previous Sundays.
So the theory there is that a lot of people will congregate in bars and house parties and things like that where they’re not all at home the way they are on Christmas day. So if you just think about it logically, it does make some sense where there’s a spike during Christmas day, but there’s lower usage actually overall on an average household basis during the Super Bowl. So these are things we’re starting to take a closer look at and you’ll continue to see this in future OVBI’s as well.
Another theory is people just dislike the Philadelphia Eagles, I just wanted to mention that.
We have a lot of tools obviously to help operators with this, and we’re going to talk about a couple of those here real quick before we get to some Q&A. Our areas of focus are network management, optimization, monetization, helping operators identify upgrade candidates, move subscribers to plans that they actually need based on their usage behavior in engaging with subscribers, providing educational tools both to subscribers and to customer care organizations so that they can see the levels of consumption of operators. So we basically have a whole set of analytics solutions. I won’t go through all these, but we also have automated solutions, which based on what the data and the analytics are telling us, we take automated actions. That way the customer never sees an issue, for example. So through the use of these tools, the operators that we work with are making more money, they’re providing better service to their customers, more accurately and effectively doing their network planning.
So the nice thing about this as I mentioned earlier, a lot of times we see operators that work in silos, these different functional areas. Network engineering’s job is to keep the network healthy. But they’re not necessarily talking to product marketing who has maybe campaigns going to provide upgrades to customers. They need to know where there’s congestion or where there’s trouble spots in the network so that they can more accurately target and more effectively target customers for upgrades as an example. So it’s really neat to see how the data ends up being that trusted source in an organization that’s then leveraged across the organization in multiple functional areas. That’s the power of being able to collect all this data, aggregate it and make it available for analysis. I can’t tell you time and time again we enter these organizations through network engineering oftentimes, but once marketing or finance gets word that this data is available and it’s trusted because it’s coming directly from the network and none of this is survey data, this is all real data coming from the network, becomes very, very valuable within the organization to be used in multiple ways.
So we’ve got solutions really for all these functional areas. Everything we do is designed specifically on the broadband network to drive your revenue, reduce your CapEx and OpEx, and ultimately increase the profits on what is clearly now the most essential service that you offer. Between cord cutting and everything else, and during Covid, we certainly saw the essential nature of broadband. So that is our focus, helping you basically make a better business out of it.
Thank you, Mark. Now we did get some questions that came in and what we’d like to do before getting to them is to remind everyone here on the Zoom that if you would like to get a hard copy of this report, go to our website and you’ll be able to download it right away. In addition, check back on our site in the next day or so, and if you want to share this webinar with anyone, we’ll have a recording of that available to watch. So let’s get to some of those Q&As. Thank you for those who have sent in. The first one is actually, let’s just get back to the ACP. For ACP customers, do they tend to be cord cutters that run over-the-top streaming services and does that account for the Delta? Or if not, why do you think ACP users are outpacing your average user?
Great question. So we originally thought, and our working theory was that ACP customers, and we had heard this a anecdotally, that they were getting service, but then they were actually spending a little bit of money outside of the program to upgrade to faster speeds. Given the high correlation between speed and usage, we thought that that was really causing the delta. We’ve done some further analysis on that, which basically shows that that’s not the case. A lot of the ACP customers, the vast, vast majority of them are sticking with what they were provided by the operator, which is typically one to 200 megabits per second type of programs to take advantage of that ACP program. We’ve shifted our working theory to just what the person that asked the question mentions is, we believe that now these customers that are on the ACP program are probably either cord cutters or cord nevers.
That broadband is the only pipe going into their house, it’s the only service they have and that they’re consuming all content over the broadband pipe. That is what is contributing to that delta and that increase in usage over the average subscriber. Because remember the average subscriber, while there is cord cutting going on for the average subscriber, a lot of them still have traditional video plus broadband. So at least some amount of their content is being consumed with traditional linear video versus the broadband pipe. So that’s going to drag down the overall average for the vast majority of subscribers. We do think that that is probably the reason, we don’t have that definitively to state yet but we are going to look again. We’ve done this in the past at cord cuttings, we’ve done a study of cord cutters a while back and we saw a pretty massive delta in usage behavior.
Where once they cut the cord, the usage was significantly higher than the average multi-play subscriber. We’re going to try to dust that off and renew that analysis because the thought here is that we might find cord cutting usage to be very, very similar to ACP, which would support that theory that I just mentioned. Great question. We’re going to continue to keep our eye on it, but I think our working theories have shifted a little bit more towards what the person asked and the question was asking.
Thank you. Another question came in talking about congestion and constraint usage. Here’s the question. Are max speeds of less than a gigabyte or gig users, are the max speeds effectively constraining users who aren’t able to achieve desired objectives and therefore mitigate data usage behavior?
Well, I don’t know that gig service is if the subscriber’s able to get gig service, it’s probably not constraining them to do anything. I think there are other things that do constrain them. So how do you constrain usage if that’s, not necessarily that’s your goal, but if you have usage based billing in place, as I mentioned over time, we’ve looked at that a lot that has constrained usage, especially at the top power level tiers. Now, again, as many operators are moving to unlimited for the gig service, that’s becoming less of an issue and we’re seeing that gap close. Network congestion, certainly curtails usage as a network gets congested, there’s less and less available capacity. That will certainly limit what customers are able to consume and oftentimes, resulting in them not being able to get the speeds that they’re paying for. So that’s a big issue as well. I would say those are the biggest constraints, as well as just the pipe going into the house. We’ve talked a lot about gig service, but there’s still a lot of customers out there.
It’s that three out of every four customers that are on some speed lower than gig service. So they need to really be analyzed and looked at to see if their usage behavior is conducive to a faster speed tier. So that’s going to constrain customer usage as well. If they just simply don’t have a big enough pipe going into their home, given the recent changes in their own usage behavior, more devices in their home, et cetera, every subscriber should be looked at. They should be viewed as their own analysis unto themselves. How much usage are they consuming, what of the available bandwidth going into their home or how much of that are they actually consuming? We do a lot of analysis on calculating megabits per second versus what’s actually provisioned. As subscribers start to bump up against their provision speed, they’re a candidate for an upgrade and they’ll be a happier customer. There’ll be fewer phone calls into customer care, fewer truck rolls if that analysis is done and there’s some campaign around getting them to upgrade.
Thank you. That leads us to the next question, which you may have just answered, but out of respect to the people asking the questions here, I’ll ask it. You were able to look at data usage among specific subscribers. Does that mean your solutions can identify which subscribers are abusing their plans?
Absolutely. That’s a big part of what we do because those abusive subscribers can have a very negative effect on the network and basically ensure that no subscriber’s going to get what they’re paying for. So really important to understand in real-time and being able to take action on who those abusive subscribers are so that you can open up the pipe for everybody else. In an area of congestion, nobody is basically getting what they’re paying for. So if you identify those and our analysis shows it’s oftentimes one or two subscribers causing issues.
One or two abusive subscribers that are impacting 300 others in a negative way. So we can take action against that abusive customer to make the other 300 customers happy. That’s really important to be able to analyze it in real-time with accurate data and then have the actionable component in an automated way attached to that analysis. Because you can do the analysis, but then if it takes a manual effort to go deal with the issue, then that’s not going to work because by the time that fixes in, there’s no issue anymore. It’s important that it’s automated and in real-time.
Thanks. We have three more questions. We have a fiber hybrid network. Do your solutions work for fiber?
So I’m assuming that means fiber DOCSIS hybrid. We have a lot of customers that have what we don’t call hybrid networks with multiple types of access networks. We’re able to collect data from fiber networks as well, from OLTs, et cetera, and aggregate that data with what we’re getting off the DOCSIS network so that we can show you all the data and do all the analytics all in one place, which is really important for the upper. The other part of it is prioritizing fiber roll-outs and helping understand in the DOCSIS network where those priorities might want to be and providing the data and the analysis around that too. So there’s lots of uses once the data’s collected. We’ve worked very hard to build our library of collection capabilities and if we do come across a device we’ve never collected from before, it’s just a matter of giving us access to it and then we can usually turn that around pretty quickly. But the short answer to that question is yes, we’re very much access network agnostic from that perspective.
Thank you. Going back to UBB and FRB, you showed a narrowing of UBB and FRB usage. Will this difference eventually be inconsequential? And if so, what direction do you see for providers?
I think it really depends on where UBB goes in general. During Covid we saw relaxing of a lot of UBB programs. A lot of operators did not want to put limits on subscriber’s usage and overcharge them and things like that, that was the theory. A lot of them, many have continued to relax and in some cases do away with UBB. Others are still adamant that it makes a lot of sense. I can tell you that we do a lot of deployments for operators, some doing UBB, some doing unlimited. Historically, we’ve seen UBB providers have happier customers, higher net promoter scores. Usage has been curtailed a bit, especially at the power levels. So we’re proponents of the program because first of all, if it’s done right, it only impacts the abusive subscribers, which is what you want.
In doing so, it actually makes everybody else happy because as I mentioned before, when you can manage those abusive subscribers, you’re really improving the service for the vast majority of customers. So UBB is not just a revenue type of a tool that operators have. In fact, most of the revenue growth from UBB comes from upgrades. It does not come from subscribers blowing through their quotas. So there’s lots of positive benefits, but whether UBB continues to be something that operators offer or launch is yet to be seen. I think that as we’re seeing, at least with the current trend, there’s been enough relaxing and/or options for upgrading to unlimited plans or gig service. Or many operators have a package where if you spend $30 extra per month regardless of the package you’re on, you get unlimited usage.
Those types of programs have become so popular that’s all serving to again, make a lot of those plans unlimited anyway, which I think is resulting in this closing of the gap in usage. So for now at least I see that trend continuing. The one other thing I’ll say is with more bead funding, with more competition in the marketplace, many operators promote unlimited service. That’s a tough sell against if you’ve got quotas on your plan. So I think you’re seeing with increased competition, more of a reluctance to move to usage-based billing. Although those that already have it in place often say the only regret they ever have is waiting too long to deploy it. So that you have both schools of thought there.
Okay, our last question, a general question. What can you tell us about the sampling size or geography for the data that we use in our report and what we’re seeing today?
So while we do have customers in Latin and in Europe, we typically leave them out of the data sample that we use. It’s actually not really much of a sample. It’s the universe of millions and millions of subscribers that we’re collecting data from through our customers here in North America. So the sample size is significant, it’s statistically significant to the tune of literally millions and millions of subscribers worth of data. That includes both usage data as well as the provision speed data that we report on. ACP is a bit less of a sample set because obviously that’s a fairly still relatively new program. Not nearly where we’re talking about thousands and thousands of subscribers when we segment the ACP scenario versus millions for the universe of customers.
But everything we do is statistically significant. I would even submit that there’s not a ton of this type of data out there in the market. But wherever we do see it, whenever we see it, whether it’s Comcast reporting on it or somebody else, we see a lot of consistency with what we’re collecting and reporting on, which proves out to us that this should be considered representative of the industry. I think what’s unique about us is we’ve got now hard to believe, but almost 13 years of this data to fall back on. We’ve got a bit of a really solid history of data that we can pull from which lends itself to using that data for predictability. So that would be my answer to that one.
Thank you. That concludes our webinar. Again, go to our website, download the hard copy of the report, look for the video version shortly. Again, thank you for attending and have yourself a great rest of the day.