>> Narrator: From the SiliconANGLE Media office in Boston, Massachusetts, it's theCUBE. Now here's your host, Dave Vellante. >> Hello, everyone and welcome to this week's episode of theCUBE InsightsPpowered by ETR. In this Breaking Analysis, I want to do some explanation. For the past four months, I've been sharing data from a company called Enterprise Technology Research, ETR. I've worked with the SiliconANGLE team to create a pure editorial product that blends the ETR dataset with insights that we've gleaned from theCUBE. We've been getting great engagement and I've been getting some questions that I wanted to address in today's episode. Let me first say that as a long time industry analyst, I've always valued data-based opinions, so when I met the folks at ETR, I became really intrigued and I thought working with them might be a good way to share some really awesome survey data and then blend it with context from theCUBE's huge observation space where we do, you know, 100 shows per year. Today I want to cover six things. The first thing I want to do is answer the question that I get most often which is who the heck are these guys? And I think it's really important to understand how and where ETR gets its data so I want to spend a little time on their methodology and dig into that a bit. And then next, I want to talk about this thing called net score. I refer to net score all the time. It's one of my favorite metrics and I'll show some examples and explain what it means and how I use it and I'll use real and current data on containers, VMware, I got some data on Oracle, AWS and HPE who just announced its earning. So there's actually content in this episode. It's not just a tutorial so stick with me here. And then I want to talk about the term market share and what that means in the parlance of ETR. I'm often asked what is the relationship between ETR and theCUBE so I obviously want to address that and if that doesn't answer all your questions, I can give you some ways to get more information. So first, who is ETR? Well ETR is a research company. Actually, it's a platform or a product that was built by a company called Aptiviti. The key advantage is they do primary market research, first party data, and they have a community of survey respondents that give them spending intentions data and they survey this base on a fairly regular basis. Currently, there are about 4,500 buyers in this survey base and in my experience, each quarter, about 1,000 or so respond to their requests for spending data. This group collectively represents nearly a trillion dollars in annual IT spending on enterprise tech and you can see here there's a nice mix of C-level execs, VPs, IT Management, but the respondents, they like to participate because those that do, well, they get access to the data in exchange for their information. Now there's no incentive for them to exaggerate their spending intentions. I mean it's not like, remember the old days of computer pubs where if you spend over a threshold, you get a free magazine? This is legit spending data, spending patterns that ETR vets with historical data. They also pay close attention to the income statements of public companies, attune their data and forecasts in a way that I'll address later and you can also see here that the data is global and it comprises a very strong mix of large organizations across virtually all industries and geographies. I mean it's North America heavy, but they've got representation all over the world and these guys have been at it for 10 years and they're serious data geeks. They have a team of stats folk, aka data scientists in today's terms who do some really cool things with the data like using regression analysis to compare their spending data with Wall Street consensus. Now they primarily, ETR serves Wall Street customers who are trying to gain an advantage, you know, ahead of earnings news coming out and they want to squint through the noise which is kind of what I'm trying to do here. ETR's founder, his name is Thomas Delvecchio and he's essentially created a survey panel on steroids. You know, when I worked at IDC, our Holy Grail was to create a panel and use it to track spending data. We never got there. It was too hard so what we did was we did spot surveys on hot topics like you know, data duplication last decade, to see where all the action was and then periodically, we do broader spending intention surveys. You know, but they weren't conducted on a formal quarterly cadence and what Delvecchio did is he flipped this model on its head. What I mean by that is ETR does regular quarterly broad-based spending surveys and then periodically, they drill down into the hot areas. The great thing about this model from my perspective is that you can run the analytics and do time series across the data. It's a way, way more powerful approach. Now there are other panels out there that you can tap into, but ETR's built a platform on top of what in my opinion is the best spending intentions data that I've ever seen and they've got a really nice SaaS product that allows me to cut the data by size of company, geography, market segment and I can answer questions like are containers killing VMware? And I can answer that question by slicing and dicing the data rather than having to field a completely separate survey. So what I want to do here is I want to take that example and drill into a key TR, key ETR metric that I use a lot which is called net score. Now net score represents the intensity of spend for a company. Higher net scores indicate a positive spend trajectory, and a lower net score indicates a flat or negative spend trajectory. So what I'm showing here is a cut from the ETR dataset and what I'm actually doing to answer that question that I just proposed, look at, so you see number one in the red, I'm filtering the ETR data by container platforms. So this is organizations that are spending on containers and you can see the number two there, the N is 541 organizations spending on containers and then number three, I cut the sample by VMware mentions. So out of the folks answering the survey for a given period, I want to isolate on those doing business with VMware and evaluate their spending. Notice number four, which is the net score. That's what I want you to focus on. Net score's a measure of spending momentum, as I said. So specifically for each ETR survey, ETR asks about spending. Are you adopting the platform as new? Are you spending more, spending the same or spending less? Or are you leaving the platform? And they essentially subtract the spending less from the spending more and calculate a net score and you can see in number five, the net score's over time and I superimpose these numbers with shared accounts that are mentioning VMware. Now remember, ETR allows for multiple responses of various VMware solutions so again, there are multiple responses in that shared end, but you can see that VMware's net score has hailed up around 33-34% over you know, a two-year period. So there's zero evidence that containers are hurting VMware today in this data. Now prior to 2018, by the way, I kind of ignore those spikes because the shared end is too low. It's like 12 mentions, but the rising number of shared accounts over time is yet another clear indicator of adoption between those container costumers and VMware spend. Now I can cut this by size of company, industry, a zillion different ways, but this is everyone in the dataset for the October survey. What I want to do now is take a look at what ETR calls market share. Market share in ETR language is a measure of pervasiveness. So they calculate this by taking the number of mentions of a vendor within a sector, they exclude replacements and they divide by the number of respondents within that sector. So what I'm showing here is an example using market share data for analytic databases. So focus on number one which takes the entire sample from the October survey and then number two and an N of 1,336 respondents. So we choose in number three, the data warehousing software segment and then select from the pull down AWS Redshift and compare that with Oracle within that sector. So you can see in the last two years that AWS has rapidly gained share. You can see in number four that the net scores where AWS has a way stronger spending momentum with 62% and negative 3% for Oracle. What I love about this dataset is the ease with which I can either call BS or validate a vendor's claim and get ahead of the market by combining the data that we collect on theCUBE and that we hear all the time with the ETR survey data. And remember, in last week's Breaking Analysis, I put up a view showing Snowflake which claims it continues to do well despite its apparent overlap with AWS Redshift and as you may recall, the ETR data clearly confirmed that Snowflake was thriving along with Redshift and eating away at Teradata's business. So it confirms their narrative. Let me share another example of how I use ETR market share. HPE just reported earnings yesterday and it missed its revenue targets and here's a chart that HPE presented as part of its earning package. Now at the highest level, HPE reports revenue across three major lines: intelligent edge, hybrid IT and financial services. Not picking on HPE, but you know, I can make this argument with pretty much any legacy computer company or any hardware company and now the narrative from these companies is we're investing in the new hot areas like edge and the world is hybrid and that's our opportunity and we are uniquely positioned and we see lots of repatriation from the cloud where people have moved to the cloud but have sort of cloud regrets and now are moving back to us. You hear this all the time from execs at these companies, but you sure don't see it in numbers. Look at the growth rate year over year in HPE's business. Edge and Hybrid IT are both shrinking in this example. Even when you adjust for currency and take out what HPE refers to as tier one sales to the big hyperscalers which is a business that HPE exited last year. Meanwhile, when you watch and you're looking at AWS and Azure numbers, they're growing at 35% for AWS, 59% year over year for Azure last quarter. Now the HPE narrative is we're focusing on margins and exiting low-value businesses and to be fair, that's true and it shows up in HPE's gross margins and operating profit and free cash flow. But I have an addition to the narrative: which is the cloud is eating away at that business and while repatriation most certainly happens, it's a figure that's not showing up on the income statement. So I look at the ETR data to answer the question how is the cloud impacting HPE's market share? So here's what I do. To answer that question, I filter the data, that I'm showing on this chart, and I select the cloud computing filter in the upper left from the pull down. I do a second filter right below, pulling down and selecting AWS, Azure and Google Cloud Platform. So there's 818 respondents in the ETR October survey that fit that criteria, cloud spenders, and then I click on the market share radio button and pull data in from January 2010 to the October '19 survey. In the October 2019 survey, you can see that the shared end shows 495 respondents that are also spending on HPE. So nearly 500 HPE responses within 800 cloud accounts. Look at the story. Like many, HPE came out of the downturn with a pent up demand. It announced the public cloud in 2011 which froze the market a little bit and by late 2014, the market clearly understood that that offering was a fail and HP exited the business in 2015 and you can see how the cloud is eating away at spending on HPE's products and you can see the net score of 10.9% in the red underscoring the headwinds that HPE is facing. Now of course, Antonio Neri, who's HP's CEO, he's doing what he has to do: cutting costs, focusing on higher margin opportunities, adopting an Azure service model, doing stock buy backs, but as I like to say, the data does not lie. Now where it really gets mind-blowing is when ETR runs regression models using Wall Street's estimates for a public company as an outcome variable and test that against the covariates and independent variables in its dataset. Now these act as predictors so not only using the data that tell the story of what happened in the past, but using it as a forecasting tool. Okay, so that's most of what I wanted to share with you today. There's a lot more, but let's leave it there for now. I want to address a relationship between theCUBE and ETR. We're essentially just friendlies. We currently have no commercial relationship. There's no money exchanging hands. There's no other incentives other than we're birds of a feather, so to speak. They give me access to their data and I use it weekly in these Breaking Analysis segments and we co-brand the content, theCUBE Insights Powered by ETR. So it's a beautiful fit between what we learn in theCUBE and this awesome dataset. Look, if you find this stuff useful, I encourage you, reach out to ETR. Their website is ETR.plus or just Google Enterprise Technology Research or you can hit me up on LinkedIn or Twitter. I'm @dvellante and I'd be happy to put you in touch. This is Dave Vellante signing out from this episode of Cube Insights Powered by ETR. Thanks for watching, everybody, and we'll see you next time. (upbeat music)