I also got a chance to watch the stream online. If not, it'll be posted, and you can watch it on demand. I've got some of the same content that I shared in the keynote. I'm gonna swizzle it a little bit to give you more of the investor take on it, to try and keep it fresh and for those who haven't had a chance to see the keynote. I wanted to walk through the basic New Relic strategy. It all starts with the customer problem we're trying to solve. This is part of a real difference in how we see the observability category as a whole. If you look at our competitors and New Relic from the past, you see that what engineering teams struggle with every day. Whenever I go talk to a CIO or a CTO, they talk about this tool proliferation problem, where every one of their engineering organizations, they have a mobile team, they have a infrastructure team, they have an app team, they have a cloud team. Each of them has, you know, best of breed tools that they've purchased over the last decade for monitoring. Those tools have worked very well in solving that monitoring use case for that team and their particular area of technology. The issue is all those teams now have to work in concert together to rally around customer problems or business issues. When they get on the same phone or in Zoom or whatever they're using to communicate and trying to fix the business, they're running into issues because they're not looking at the same data. They're not looking at the same tool. They've got silos between them because of this approach to observability that we've sort of backed into from a suite, you know, from a series of à la carte or best of breed monitoring tools now getting bundled together. That was what New Relic did over the last, you know, five years. We acquired and we built a logging product and an infra product and a mobile product. Our competitors have done the same. Our approach going forward, though, is very different than what we see others doing. By the way, I already mentioned the problem with that approach of these kind of bundle of monitoring products and calling that an observability platform. It doesn't really solve the problem. It still leads to slower response times as engineers try to, you know, correlate the data in their heads or over Zoom. It's exploding budgets. I talk to customers who spend tens of millions of dollars on observability, you know, $20 million, $30 million plus, annually across multiple vendors to try and, you know, wrangle this problem. It reduces innovation velocity because engineers are constantly just firefighting, trying to get systems under control rather than spending their time where they want on innovation. Our approach is fundamentally different. The hard work that we did over the last couple of years was to separate the tools from the data, standardize on a single unified hyperscale data platform. We're the only observability provider to do this, where we can ingest all types of telemetry data, events, logs, metrics, and traces, at massive scale, multi-tenant system, one API, one query language, and we run and operate that in the public cloud now entirely. We announced today doing that now on Microsoft and offering customers a choice of where they want their data stored. AWS, Microsoft will be the options this year. Of course, ultimately, we plan to be multi-cloud and offered on Google as well. But this is a real technical moat for us, a real differentiated advantage. Because we run and operate this thing at massive scale, we pass along the economies of scale onto our customers. We offer basically a cost plus model. It's been $0.25 per GB. We're now raising the price because our costs have gone up to $0.30 per GB for the standard price point. That's the underlying Telemetry Data Platform. On top of that, we offer one integrated product called Full Stack Observability. It includes all of the tools that previously you'd have to buy individually, à la carte, from either New Relic or from competitors to service every one of those engineering teams, whether it's your infra team, your app services team, your mobile team, browser front end teams, et cetera. You can get it all from New Relic, and it's all for one price and in one experience. We moved to this platform model because we believe observability is becoming a standard engineering practice. Every organization will need to have an observability platform in order to run their digital systems at scale. We see them standardizing. We want to optimize for that. We've skated to where the puck is going effectively by optimizing our product, our architecture, and our business model, which we'll talk about in just a minute. Sometimes investors ask me, like, "Has this ever been done before? Like, where have you seen this kind of approach work?" I'll point to two really quick examples that maybe trigger something in your mind. Think about, like, 30 years ago, maybe longer, when spreadsheets were a thing that only, like, geeks in finance did, and presentations were, like, something that only marketers did. Then there were word processors, WordPerfect, you know, that only, I don't know, certain secretaries used or whatever. Right there were these best-of-breed tools, Lotus 1-2-3, WordPerfect. Microsoft came around and said, "No, productivity software applies to everyone, from students to knowledge workers of all types." They brought together a bundle called Microsoft Office, and not only expanded, you know, the usage of productivity tools, but they brought it together into one platform that interoperates across those applications. Similarly, if you think about the iPhone, 14 years ago, it launched. Am I getting that right? Think about life before the iPhone. You maybe had one of those little cameras that you'd carry around and plug into your computer to download the photos, to package up in an email to send to your parents or friends. You'd have a pager, at least if you were in engineering. I don't know if analysts had pagers. You'd have a computer to type emails, and now you have a single all-in-one device that does all of that. You probably don't have a separate camera. You probably don't have a separate pager. Hopefully, not. You don't use your computer maybe as much as you used to because you can do so much of it on your phone. It's an all-in-one approach. It's democratized access to all of those applications. Similarly, we are optimizing for observability across all engineering teams and democratizing access to that data. That effectively is then the New Relic promise. We want all teams, all tools, all data in one platform for one price. It's why the business model transformation has been so critical because we want to set up for our customers standardizing on New Relic. I talked about this in the keynote as well. A lot of companies, you know, think about observability as a really static thing. You collect all this data. You can analyze the data. We think about it differently. We're trying to power action with engineers, and not just in the reactive sense around production issues when they're blowing up, but across the software life cycle. If you saw the demos today, fantastic examples where, you know, we've brought telemetry data all the way up into the development environment, so engineers can see right next to their code how that code is performing in production in real time. They can see errors coming off of, you know, the production systems being thrown by their code and walk through the stack trace and see exactly where the lines of code are that are failing. We want to empower engineers with data as they plan, as they architect and write code, as they deploy code, and of course, when they're troubleshooting production environments, help them take action with that data. Internally in the company, we talk about our mission all the time. Every all-hands meeting, a lot of our operational meetings, it's sort of our pledge of allegiance, if you will. This is the ethos of the company. We repeat it so often. We want to be a source of truth for every engineer to make decisions every day with data, not opinions, at every stage of the software life cycle. You look at the green words there because they're the most important words. Every engineer. Today, observability is a specialized practice. Only very small number of engineers actually use our tools, whether it's New Relic or Datadog or Dynatrace. It's a fraction of engineering. Think of it like 10% of engineering today. Every day, that's not a truth today. This data set, again, specialized production engineers troubleshooting. They may not be on call. For one week a month, they may go on call. The other three weeks, they're not, or maybe it's once a quarter. The data set is really isolated to these reactive use cases. We're taking that data set and bringing it throughout the life cycle, so they use it every day and every stage of the software life cycle. There's sort of three things that we feel we do different and are unique to New Relic. The first I've already talked about, our hyperscale data platform. $0.25, now $0.30 per GB, all data sources, all data types. Our all-in-one user experience. We've brought all those tools together. You may be a mobile dev, and you may be looking at your mobile applications, but you can see how that mobile application calls services underneath it, how those services are hosted on infrastructure underneath that. You can see where the infrastructure lies in the public cloud, and you can trace all the way through from infrastructure to your application, the health of the entire stack. Again, unique to New Relic. As a full stack user, you pay once for that opportunity, for that data, and you see all of the data across all of the systems. Third, our consumption model. We're the first to pioneer, in this category at least, a consumption approach to observability. We priced it on two things, users and data, which I think I'll talk about in just a second. We feel consumption is really important for kind of three reasons. First, we chose really simple meters because customers talk to us all the time about how hard it is to plan and budget for observability. If you look at the pricing meters out there, they're all over the place. Again, because of those vertical siloed apps, they charge one thing for infrastructure, a different thing for APM, a different thing for logs, a different thing for mobile. We have just two price levers, user and data. The number of users provisioned, the amount of data you send. Second reason we feel it's really important is, another thing customers complain about all the time is shelfware and penalties. Our competitors use this to, you know, really wrangle customers, get as much money out of customers as they can, which creates unhealthy relationships, and I would assert, not a long-term sustainable business. We want a long-term sustainable business, and we believe consumption is at the heart of that. When you're only paying for what you consume, you feel better about your consumption and your spend. Third, we believe this all-in-one platform approach we have allows customers to standardize more easily on New Relic. You heard that today in spades. You know, you heard it from McDonald's now using the full platform, Capital One, Verizon, LinkedIn, Foot Locker, all talked about how they've moved from APM to now using APM infrastructure, browser, mobile, et cetera. They're expanding their usage to just standardize on New Relic. Sometimes investors ask how do you scale the business? How do you grow? If you only have those two price levers, is there really enough TAM in users and data to grow to a competitive revenue growth level? I'd say absolutely yes. You think about the drivers of expanding paid users. First, we're introducing new capabilities all the time, and most of our customers don't even use all the capabilities we already have in the platform. They came into us through APM, but I think we announced in the investor letter, only 15% of our total customers use the top four at the beginning of FY 2022. We were able to move that to 25% using the top four at the end of the year, but we still got 75% of our base not using all of the top four. As we drive adoption in the product and through our sales force across more teams, more capabilities, they get added, and we expand our paid user base. Second, engineering teams continue to grow at a pretty rapid rate. There's not enough engineering capacity to meet the demand, and most businesses are always hiring. Every time they hire more engineers, that's more people for us to sell into, users to capture. Third, as I mentioned earlier, observability is really a new practice. It's really isolated to that production use case, primarily 10% of engineering, think of that as a rough number. You know, more broadly, I'd say it's even less than that. It's, you know, 2%, maybe 1% or 2% of the total professional engineering community engages in observability today. IDC reports about 25 million professional developers, and that's going to expand to 34 million by 2025. It's pretty easy to do a TAM on that. You multiply that by, you know, our published retail price points per month, starts at $99, and goes up. You see there's lots of TAM there. On the data side, we charge, you know, starting June 1, $0.30 per GB for our standard data SKU. We also announced, if you heard the keynote, a $0.50 price option. How much data is there to capture in this space? The answer is really easy. There's gobs of data. There's so much data that even at our low price point, which is significantly less expensive, incremental cost per gigabyte, than competitors, customers still are choosy about how much data they send us and where they send it, because they could send us incredible amounts. We have several levers there as well, though, to drive data growth. The first is around data model innovation. The one thing to remember about this space is we give our customers agents, which they then deploy into their applications or infrastructure. Those agents define a data model that then expresses what data gets sent back to us. As we identify new opportunities to give customers insights, we expand that data model. It increases the data sent back to us. We, you know, customers get the value, we reap the rewards in revenue. In terms of customer infrastructure, that's also always expanding. Look at the growth of public cloud. When a customer moves to public cloud, they scale out as their business grows. Once again, that instrumentation grows, and we also get paid based on that. Customers embracing more of our platform. Many customers, again, through the keynote you saw, came to us through APM, but have expanded usage and therefore expanding their observability commitment to us. Finally, customers instrumenting more. We talked about the cost per gigabyte being four to five times cheaper, incremental cost versus competitors. That allows them to scale their instrumentation across more hosts, collect more logs, and therefore spend more with us than they would be able to do with a competitor. I already referenced this from the investor letter. Platform adoption is growing. Last year alone across our customer base, 15%-26%, actually, at the end of the year. If you look at just customers who commit to us $25,000 and above, the rate is actually even higher. It started about 36% and now about 50% of those customers using the top four capabilities of the platform to some degree. Could be early engagement. Most often it's not ubiquitously deployed. Even if they've started sending us logs, for example, they're likely not sending us the majority of their logs yet. They're ramping that up. That's really healthy across APM, infrastructure, logs, and browser. Those are our top four, 50% of our largest customers using all of those. Competitors do publish similar metrics, so if you wanna compare us to Datadog, you can look that up and see how we're faring actually very well. This all-in-one platform approach that we have been taking the last six quarters or so is resonating with customers in terms of expanding the platform adoption. I shared this as well at the keynote. Our data growth is growing faster than ever. I think last year we reported around 50% year-over-year data growth. As you can see, that's continuing to accelerate even since the IPO. Data ingest. I also shared some remarks around pricing with our customers. We have been delivering tons of innovation over the last two years since we introduced this model with no price increases. Our prices are going up, and we are effective June 1st, increasing the standard data price to $0.30 per GB. Investors ask me often, "When does that take effect? How quickly will that hit the top line?" The answer is, it doesn't take effect for most of our largest customers, where most of the revenue comes until their renewal because they have a contract with a committed price to us already. We go through the renewals throughout the fiscal year. Most of our renewals happen in the back half of the fiscal year, Q3 and Q4. Really, the majority of whatever revenue increases we get from this will show up in Q4 and then FY 2024. For new customers starting out on the platform today, that starts at $0.30, and we roll forward with that. We also found opportunity in a lot of the customer requests we were getting from some of our largest customers for introducing a new Data Plus offering. This takes capabilities that customers have been able to purchase à la carte and bundles them together with a discount to incentivize adopting the higher priced SKU. It bundles built-in extended retention, higher query limits, long-running queries, streaming export, other things like that. New capabilities of the platform increasingly will require the Data Plus SKU as well. That is also available June 1st. I'm really proud of the product organization, the innovation they've brought to the market this last fiscal year. I mean, we announced so many groundbreaking capabilities from Errors Inbox to Pixie to CodeStream, all of which you saw demoed today. Today was kind of a revelation of innovation as well. Many new capabilities announced, which we were pretty excited by, and customers seem to be responding well. The results of all that work to shift to the platform model, to get customers into consumption to drive adoption, has resulted in several impressive secondary metrics that we've been sharing. First one here probably looks familiar if you've followed us for a while. It's our active paid customer accounts. We have been decelerating, declining there over the last several years. FY 2022, we turned the corner. The first chart there shows, you know, we grew about 700 paid accounts, net of churn in the fiscal year. If you look at the right chart that shows active accounts over 100,000, you see that we increased that number significantly over the past two years in FY 2022. More larger customers growing faster than ever. Also, we've been talking about the business model transformation over the last six quarters. You can see with the orange line the rate at which we've been able to drive that. Again, I am so proud of the team for getting through this so quickly. It's not easy to move $800 million in revenue from a legacy business to a new business model, but we're 87% of the way there, effectively complete. We'll finish it as customers in the long tail or multi-year contracts come up for renewal. The vast majority of revenue is now in the consumption model. Allows us to be really single-minded in driving consumption growth for the business versus having to be split between two businesses that we're trying to balance. Sometimes, investors ask me, you know, "How do you think about this vision of full lifecycle observability?" You know, capabilities like CodeStream and the potential there for driving ubiquity of observability practice across millions of engineers. I guess I characterize the story in kind of three chapters. We just finished chapter one, which was landing the platform, that common hyperscale data platform, all-in-one observability tools, for all engineers under a consumption model. That was chapter one. We migrated the business. Now we're in the platform adoption phase. That's chapter two. This is now helping our customers realize the full value of the platform to expanding, paying those incremental costs to standardize on New Relic and reaping the benefits of hard cost savings and productivity improvements and satisfaction for their engineering organization. That phase will probably last a few years across 15,000 growing customers and cements us well as we incubate and drive adoption to the third phase, which is the full life cycle observability phase. You already see our innovations in this phase happening underway with projects like CodeStream. Security announcement we made today is another example of beyond operate phase. But those longer leading investments have longer adoption cycles. It takes time to get the product market fit to drive adoption into engineering communities that haven't practiced observability before. That ultimately leads to unlocking the TAM, where we can start to talk about millions of users, multi-billion dollar business that we're working towards. All right. With that, let me turn it over to Manav Khurana, our Chief Product Officer. He's gonna walk through the go-to-market approach to New Relic and how we grow the business. Manav. Thanks, Bill. All right. Hi, everybody. As introduction, I'm an engineer who loves business. As New Relic's chief growth officer, I cannot think of a better role, a better job for somebody like me, because I get to engineer our go-to-market to be a deterministic and optimized machine. See, I oversee a number of product engineering, sales, and marketing teams at the company, which is different than most other companies, and it is by design. It's by design because I spend my day aligning our product to our go-to-market and our go-to-market to our product. This is what people call product-led growth. It's the fundamental principle of PLG. Let me explain. You see, Bill earlier talked about our mission, about every engineer, every day, every stage of the software life cycle. We bring that mission to life in our go-to-market through a three-stage machine with multiple steps in each. It all starts with engineer mindshare, getting every engineer in this world to understand what they can do with data and what problems they can solve. Feeding that interest into our product-led growth machine, our product-led growth initiatives that result in new paid customers. Going from there to our cohort or to our customer part and cohort maturation process to drive platform adoption. Which leads to data and users growing among our existing customers. To platform network effects that are fundamentally baked into our platform and are even getting better that feeds back the engineer mindshare. Let me walk you through each one of these, starting with engineer mindshare. Now, this concept of engineer mindshare for me is there's many, many ways to get every engineer in the world to think about data. For us, it is all focused on the three reasons why New Relic exists, the three reasons why New Relic is different. Bill talked about how our data-centric approach, our hyperscale data platform is very unique in the market, and it is. The way that comes through for our customers, though, is how they can use New Relic across their entire tech stack, some things that are maybe 10, 15 years old and some things that are bleeding edge. They can get data from each component in their software stack and bring it into New Relic. To make that happen, my team has been accelerating the number of integrations we have with other tech vendors, and we call them quick start, and I think we are up at close to 470-480 now integrations which are one-click approaches for our customers to instrument and collect data about their entire tech stack. Now, it solved the customer problem, but it also gives us a new marketing partner 'cause every time we introduce a new integration, we just don't talk about it. Our partners are also excited to talk about it to their customers, which gives our customers and every engineer more education about the problems they can solve with New Relic, creating that interest. The second differentiator that Bill talked about was this all-in-one platform, this all-in-one user experience. Bill talked about how we are accelerating or our product teams have been accelerating the innovation and how much they are shipping for our customers and solving more and more problems. Well, each time we ship a new capability, major or minor, this last year we have built a launch machine and go-to-market that properly and concretely explains what is this new product capability, who can benefit from it, and how, and brings that to market. Every time we do that, we end up reaching more and more engineers because the surface area of the problems they can solve with New Relic gets wider and deeper. That creates more interest and more people interested in the problems that they can solve with New Relic. The third differentiator that Bill talked about was our unique business model and our unique pricing model. I'm just going to say it plainly, our customers get more value with New Relic than they would with any other platform in the market. Very easily quantifiable, and we have done that. We've taken off our gloves and made that very, very clear. Our customers have taken notice. They see how New Relic in their environment gives them more value and saves them money that they can apply to other projects. They're openly talking about it. A few of them are even here today. As they talk about it, their peers and their company and other companies hear about it. The perception of New Relic providing more value is spreading. I hear it every day when I talk to customers who are just starting their journey with New Relic. They come because they know that New Relic offers more value. Now, focusing our energy on driving mind share and on those three differentiators ultimately creates one metric for me that I care about internally a lot, which is how many new engineers are coming to our site. Not total. How many new that do not have an account with New Relic are coming in. 'Cause that is the potential energy that we have that we can then convert into solving greater problems and turning them into paid customers. That process is our product-led growth initiative that converts the interest on our sites, measured by number of new people coming in, into new paid customers. We do that with our self-service free tier funnel. Now, some of you may remember this from about 20 months ago. We introduced an industry first. We're the only observability provider in the market that has a perpetual free tier, where an engineer can sign up for New Relic and get access to the entire platform without a trial type time ticker on their head. They can use all the capabilities up to a certain point for free. After that, if they keep wanting to use it, they add a credit card and become a pay-go customer. We've been showing you those metrics every quarter. Well, that whole journey is completely automated in our product. It is truly self-service. Engineers come to our site. We see how many of them are signing up for our free tier funnel. We see how many of them are not just signing up, but installing New Relic in their environment by themselves without any human from New Relic helping them. How many of them are using the data they're now collecting to solve their problems in their environment on their own, and how many of them are then adding a credit card on their own and start to become paying customers in our pay-go program? All of this is an incredibly efficient go-to-market approach that gives us the ability to convert that mindshare into paying customers. You've seen this chart before, and you've seen this for many quarters now. This chart shows you how many cumulative pay-go customers we have, and it is accelerating. It is accelerating for a number of reasons. Number one, we're getting more customer, more engineer mindshare. Number two, the product experience gets better every day. The engineers on my team are maniacal about looking at every stage of our product experience, understanding how many people are clicking on it and how many people are getting the job done. Wherever there is friction, they're building a better product experience so more customers get through to the next stage. Each of those improvements compounds over time and ultimately ends up creating a pay-go customer, which increases the bar charts here on their own without any human intervention. We expect that to continue to get better over the coming months and years because we can see that in the instrumentation every stage of it. Now, one thing that we learned over the last year is that there are some customers in our free tier funnel who are not yet paying customers, who install New Relic in their environment on their own, but need a little help from the moment they have tried New Relic in their environment, used it, to becoming a paid customer. Things like, you know, how much am I going to pay? What is the best practice here? There are some questions people still have. To overcome that problem, earlier this calendar year, we experimented with an inside sales program, a very efficient model of humans who are knowledgeable in New Relic, know what other customers are doing, and provide that light touch to help our customers at scale. That inside sales group has been taking the interest coming in from the self-service product as well as inbound requests that we hear on our website and helping customers through their journey and giving us even more pay-go customers at the end. It's been just about a couple of months since we've been running that. The early results are impressive, and we're scaling that program now based on the data that we see. One data point I'll share with you is that customers that got help from our inside sales program are spending three times more in the first month than the customers who did not get any help from a human at New Relic. Just that fact alone, the increase in average deal size in the first month alone, more than pays for this very efficient inside sales program. Okay. The third thing that we are doing here is investing this year in helping our partners increase our reach and help their customers adopt New Relic. These are cloud partners, these are technical solution providers, and these are managed services providers. Many of you heard about the Microsoft partnership this morning, where they are making New Relic available inside the Azure portal, and they are able to give their customers the ability to pay for New Relic using Microsoft Azure credits. That's an example of what that third funnel is, and it's gonna add and compound to the number of paying customers we see. This program is very, very new, and it's gonna take a little bit of time. We'll keep you updated on how that goes. Okay. Through these three funnels, that is, every stage is instrumented and we're continuing to make it better, we get new paid customers. The next part of the go-to-market machine or the next stage of the go-to-market machine is how do we help each customer that has become a paid customer adopt a very efficient model, realize their full potential, solve all the problems they could be solving with New Relic and expand. Ultimately for them, they get more value, and for us, we see an expansion in the number of users and the amount of data that are provisioned on New Relic. Well, we do that through a cohort graduation model. Our go-to-market teams over the last year have figured out that if we start at the $50,000 a year consumption run rate level, and we assign what we call a customer pod, a salesperson and a sales engineer to that customer to help them understand all their use cases that they can solve with New Relic and help our customers adopt New Relic in their level of maturity and improve their observability practices, that they start to use more and more of New Relic much faster than they would have on their own. Everywhere we have a pod, we see customers growing their usage faster, growing their consumption run rate faster. We have different variations of investment depending on the size of the customer and the level of usage that they have, which makes fiscal sense for us, and actually, the customers also expect a higher level of service. How does this come through? Traditionally, this concept of go to market with sales and sales engineering is a very bespoke, very unstandardized process. Well, some of my peers in the company are very operationally oriented now, where they have broken down this stage into multiple steps and standardized on those steps. Which roughly breaks down into two parts, set of steps that help our customers commit, and a set of steps that help our customers consume and increase their consumption and our CRR as a result of it, right. As an example, when our sellers take a value-based selling approach, they're able to help our customers, our champions and our customers justify the value of New Relic to their finance teams, to their business teams. One example of that is a very large retailer who went from a low six-figure commitment to a seven-figure commitment because our sales team was able to help our champions understand how they were saving. They were getting $70 million of value from New Relic and the way they were using New Relic and the use cases they had. One, it takes courage, it takes a lot of work to get there, and the team was able to do that. More importantly, that value selling, that quantification, helped the finance teams at our customers and the engineering teams at our customers understand why they should be increasing their investment and what return they get. Often 10 times more than what they pay New Relic. Okay. Another example, now in the consumption part of this diagram, is how our sales engineers help engineering teams at our customers solve for more use cases and adopt New Relic as a technology and as a practice in their environment. The one example I would give you there is an e-commerce company that is now consuming at a 7-figure CRR, consumption run rate, which is four times larger than what they had committed just six months previous. That happened because our sales engineering team was able to understand what each engineering team needed to do, create a specific value realization plan, onboarded that team to solve their problems. When those engineering teams are solving their own problems and creating better customer outcomes, that customer is actually really happy about it because they're getting much, much more value from New Relic than they had initially predicted. Even though they're consuming four times more than their commit, it is a very welcome change for them because they're able to create more outcomes for themselves. Okay. This obviously is a really, really important area for all of us, and we are looking at many leading indicators, many metrics internally every day to make sure we are progressing customers through each stage and they are getting more value, so that they can increase their commitments and they can increase their consumption. Okay. The last part of the go-to-market machine is how do we take customers who have all their engineers or a large number of their engineers using New Relic every day and use that to create more engineering mindshare. Now, there's something that's just inherently true about New Relic. Now, even before we went to the platform model and added the ability for every engineer to look at the data that they care about, the reason why engineers loved New Relic was because it was the best platform to arrive at an insight at depth, right? That's what engineers use New Relic for, to understand what really is happening. How is my code working in production? The problem that my customer is seeing, why is that happening, right? Well, the thing with insights, the natural human behavior when one arrives at an insight is to share it with other people, to share the light bulb that just went on. I talk to about 100 customers a year, and usually customers that are new to us and is entering our free tier funnel. I ask them, "Hey, how did you hear about New Relic? What led you to even start thinking about New Relic as a platform that you wanna try out?" Nine times out of ten, they tell me that they either were using New Relic at a previous job or in a previous project, or somebody shared a data point with them that came from New Relic, right? Naturally, there are these network effects that are happening. Well, this year, I'm very excited about the work the product and engineering teams are doing to make that natural flow into a more deliberate flow. With the collaboration capabilities that were introduced this morning, our customers, engineers that are customers, have a really easy way to share the insights that they get with their teams and others outside their teams, so everybody can benefit from that insight and solve problems. Well, that's great for the customer and for us, but also it creates more mindshare. I'm looking forward to tracking this and giving you updates on this as we get those capabilities out. Bill talked about this morning our new incentive, the Observability for All incentive, which helps our customers give New Relic access to every engineer in their company in advance of those customers realizing the commercial value and an incentive that bridges the gap. Well, the thing that does is it takes away all the friction that exists in every engineer taking advantage of New Relic, solving problems with data, and helps further accelerate the network effects to gain even more mindshare. Right. Put together the three parts of our go-to-market machine, the three stages: engineer mindshare, new paid customers, and user and data expansion. Each stage has multiple steps that are all instrumented. We look at those metrics every day. I look at them every day with my teams. Then we as an executive team come together every week to see how we are doing and turn the knobs necessary to make this even more deterministic and even more optimized. Okay. That's all I had with that. I'll pass it over to Kristy. Thanks so much, Manav. Can I have the. I only have one slide. I loved your intro, and I loved how you said you're an engineer who loves business. Wish I could say the same. I'm a business person who loves business. I've spent my whole career in the roles I've been in because I find business has a unique ability to just solve tough problems. When you're solving those problems alongside your customers, you're creating a ton of value for them and for their customers. I think I have the most fun job today, which is, I'm gonna interview three of our awesome customers, so you can hear straight from them how we are solving problems for them, working alongside them, and creating value for them and their customers. Thrilled to welcome up Steve Evans, the Vice President of Engineering Services at Chegg. Mark Huber, the Senior Director of Engineering Enablement at Cox Automotive. And then Tommy Harke, who's here, Vice President of Engineering and Architecture at Vault Health. Join me up here in the comfy chairs. Excited to chat with you. You each have a mic. Sounds like at least yours works, Steve. All right. Good test. Well, thanks so much for taking the time to spend with us today. I think you are skipping one of the keynotes to be here, so I really do appreciate it, and hope you're enjoying your time at FutureStack. First, for the folks here and on the phone, can you just spend a minute or two describing the business that you're in and then focusing on the digital aspect and why that's so critical? Maybe we'll start with you, Tommy. Hello. Okay. Vault Health. We're a distributed clinical trials company. That's clinical research, clinical testing, and clinical trials. Over the past two to three years, we're a startup, so we're not very old at all, but we're a leading COVID testing provider in the U.S. If you're from Minnesota or New Jersey or you travel to Hawaii, etc., you pretty much had to take a Vault COVID test, PCR test, spit test, and that type of thing. We grew really, really fast. Did 12 million tests over the past year on that side of things too. That's kind of where we're at on that side of things. COVID testing, now we're distributing clinical trials. Getting to a space that's very regulated, FDA compliant, HIPAA, et cetera, that sort of stuff. We're using New Relic from a HIPAA compliance still, on that front. It just works really well for us. Yep. Super fast scale, and super important to have that, compliance and, security. Great. Thanks. Mark, did you wanna introduce Cox Automotive? My name is Mark Huber. I'm from Cox Automotive, part of the Cox family of companies. We're based out of Atlanta, Georgia, but we have team members all over the country and all over the world, actually. The mission of Cox Automotive is to transform the way the world buys, sells, owns, and uses cars, in our world. We hit the entire automotive space, the entire life cycle of automotive from how consumers buy and sell and shop cars. Brands you might recognize like Autotrader.com, Kelley Blue Book are part of our family. A whole host of other parts of our organization that if you're not in the automotive industry, you probably don't recognize, like Dealertrack. Everything from how you finance and lend, you know, how we do lending for cars, how a consumer gets credit to make a car purchase, we facilitate those transactions. A huge part of our business is also the Manheim auto auction space. All of the wholesale auto auctions between car dealerships, all over the world, is also part of our family. We like to say, you know, for over 48% of every automotive dealer website out there is powered by our Dealer.com products. Over 20,000 dealerships use our Dealertrack unified lending platform to do financing for consumers. We are doing a lot of new investments in the mobility space. Everything from how people are moving to, not just traditional leasing models, but you know, essentially renting models for cars, and how we service those fleets of vehicles and facilitate that industry. Really, you know, we're taking a data platform play approach in our industry as well, so that partners can build off of the unique full life cycle of data that we have about vehicles. New work in the telematics space, new work in the service space is also really interesting. Exciting. A lot of your growth and your history has come through acquisition too. There's a complexity inherent in that that New Relic helps you with as well. Yeah. Over 65 acquisitions spanning back to the Manheim acquisition in 1968. Okay. Steve, tell us a little bit about Chegg. I'm from Chegg. We're an EdT ech focused on the higher Ed Market, so we provide a suite of learning services for primarily undergrad students. It ranges from flashcard tooling to math solver tool. Our bread and butter is a service called Chegg Study. Think of it as online Q&A, subscription-based model, and you get primarily experts in India with PhDs and master's advising students on helping them study for particular topics. We're in the process of expanding into skills-based learning for I kind of talk about it as like, usually it's the retail employee who wants to go on to do something next, like information security happens to be the most popular one. We have done 30 acquisitions, and we're only 15 years old, so I think we win per year. All right. Solid. Great. I imagine that's reasonably low stakes. The higher Ed students preparing for a big exam. If your site is out, I'm sure you don't hear about that at all. It's not a COVID test. Sometimes they act like it is, so. I love it. Why don't we start with how did you decide to use New Relic? Maybe Tommy again, we'll start with you, 'cause I think you represent some of what Manav was talking about you joined Vault Health about just over a year ago. Maybe talk about how you decided to standardize on New Relic. New Relic, even my previous company that was BTS, we used New Relic extensively on that front. What's been talked about today was Observability for All. That's something that our motto always has been from how we build engineering teams that I've been a part of. We always want everybody to be using New Relic, understand our application, understand that once you put something into production, how it actually functions, how to actually monitor it, you know, when that failure response time goes up, error rate goes up, et cetera. That's the model that we build right now. Even everybody that we onboard, all new engineers, associate to senior, their first day is actually getting into New Relic, looking at the application profile, understand how to use it, right? That's how they're gonna be better engineers in the first place, right? Your return on investment and training of these engineers is significant when they start seeing this information and seeing how things run compared to just saying, "Hey, come a part of this team. You have to do this work. How this functions, you don't need to know about that at all," right? That's kind of the culture that we've always been trying to build. Likewise at Vault, one of our core values is an excellent customer experience, and that's kind of across the business, doesn't matter. Likewise, talking about COVID testing, it's if one person has an issue, right, that's stopping them from their trip to Aruba or something like that, right? Getting on a plane possibly. Every customer matters, every error matters in our platform, and New Relic helps us significantly with that. Great. Mark, you have a unique role in terms of, defining and then extending observability across all the different Cox Automotive properties. Maybe talk a little bit about how you decided to use New Relic as the standard, to help you do that. Maybe first start and explain what your role and maybe what CORE is. Sure. At Cox Automotive, my organization is called Engineering Enablement, and we serve approximately 500 different software development teams across the organization. That history of acquisition has sort of naturally, you know, creates a fragmented organization. With the objectives that we have going to market, more and more, you know, our customers don't wanna buy one product or that other product or that other product. They want to buy the Cox Automotive product. We have a new need to collaborate across engineering teams that literally do not know each other, have never met each other before. My organization serves to provide and bring them together, the tools, the practices, the technology, the culture, right? Of what it is to operate as one large engineering organization. One of the real challenges is the sort of the vast disparity in maturity of all these different engineering teams that have come together over years of acquisition. We have partnered with other parts of our organization, our operations center, our site reliability practice. We formed what we call the CORE program, Cox Auto Observability and Resiliency Engineering. It is about improving the practice and the discipline of how we operate across the business, right? It is people, process, and technology, right? New Relic, through all those acquisitions, became very clear that it had the engineering mind share already, right? Just purely logistically speaking, there were already dozens upon dozens of instances out there of New Relic happening, but none of them could communicate. None of them could share the data. They were literally unorganized, right? Our organization came together to bring those accounts together, bring that data together, make it accessible. We saw a kind of network effect happen, right? When teams try to deliver products to market, the ability to literally go in and see each other's systems, see each other's activity made it possible for these teams to collaborate and to deliver solutions. The CORE program is there to sort of pour gasoline on that fire that we saw start with that. Now we are trying to make it not just an available tool, but the, you know, the standard tool. There are other tools in our area that are directly competitive with it. You know, we took a long, hard look at, you know, the quality of the tool itself, and we realized it's not about the quality of the tool itself, it's about that network effect when teams get to collaborate on a common tool, right? We're trying to maximize that opportunity for collaboration through the availability of the tool. Thanks, Mark. Steve, I love your story about choosing to opt into New Relic as opposed to just taking it as a given. Yeah. I've been at Chegg for almost five years now, and we were a New Relic shop when I showed up. I don't know why they picked New Relic before I got there, but For very good reasons. Obviously, we had a bit of a thesis. I showed up. We were fairly immature, you know. We're a growing company. We essentially had a thesis that at the time New Relic was the most expensive, and it was the oldest, so it's probably the best, but we're not sure we need something that's the most powerful, right? We use the Ferrari on 101 analogy a lot. We were going down this road of learning the tool better, getting in a better place. We had some resiliency issues we were dealing with. Probably around, I think around 2018, we kind of looked at the market and we said, "Okay, do we either need to double down on our investment in New Relic, meaning, you know, education, knowledge of the tool, how to use it, or are we going to go double down somewhere else?" We looked around, and we really got to the place where New Relic was not the most expensive, which I was actually surprised by. We didn't find anything that just blew us away. The real differentiator for us, it was funny, the presentation earlier about the account executives and the sales engineers. That's been a make or break difference for us. I 100% see like, it really resonated with me, that part of the presentation. Because we've really gone from an organization that I think about the beginning where it was something bad happens, we looked at some stuff in New Relic, we fixed it, we argued about what happened later, et cetera. To something bad happens, we have a data-driven conversation about what happened and how we fixed it and then how, you know, what happened usually. And then the journey has just continued, and we talk a lot about now shifting left. Our developers spend more time in New Relic on non-production services in the development phase and the testing phase, which then just translates to a better experience for ultimately our students. That's really why we've been a New Relic customer. Why we've continued to be a New Relic customer. I wanna second that point. You know, our account team has, I consider them sort of part of the product that we purchase, right? They have gone above and beyond to align themselves to our CORE program. They spend time on making sure those objectives are successful, not the usage of the tool. The objectives become successful when we use the tool well, but they're spending a lot of time cycles on our success, not our bottom line and our invoicing tool. My account team's better. That's awesome. I was gonna go there eventually, but I love how passionate you are about the account team, so you're sort of bringing it up proactively, 'cause I think that speaks to the quality of the relationship and the quality of the value we're creating. When you take that customer success first lens, just how effective it is to create that value. But I do wanna talk a little bit about the earlier presentation with Bill Staples, where this morning we talked a lot about how the value of the all-in-one platform, giving users access to all the products. Can you talk a little bit about what products you use, and then, you know, how you experience that all-in-one platform of, you know, when there's a new product to tack on and how you make that decision? Any one of you can go. I'll start. I maintain that I gave New Relic the idea to do the all-in-one model. I'm really confident about that, I'm gonna take it to my grave. I'm pretty sure we said it during the press release. Well, you didn't, and my lawyers will be talking to you. Before New Relic had logging, we were on a different logging provider, and we had challenges. We were one of the first customers to move to the logging platform along with the consumption-based model. It's been excellent for us because for a couple reasons. First of all, it was not a difficult decision to move to logging because we knew it would be good enough. We didn't have to get into the, is it better than our current solution? We knew that we would get the synergies. I can't believe I used that word. We would get that. We talked a lot about the swivel effect. Great business word. Of engineers going from the New Relic console to our logging console to the New Relic. You know, having to go back and forth. We knew even if the logging platform itself was 10% not as good as the place we came from, who all they did was logging, so that was reasonable to assume. We knew that them being connected would improve the experience for the engineer. Then the second piece was, at the time, and one of the reasons we were kinda looking at the broader market at one point was, you know, you guys started on APM and infrastructure came later. The infrastructure product, especially in 2018, it just wasn't as good as some others in the market. With the all-in-one model, it became this, the ROI didn't have to be as high, right? Over the years, as the product's gotten better, we've started using it more as it's added more value for us. I also really like how it really creates a symbiotic relationship where I give you more data, you make a better, like, you can make me a better product with that data. We're no longer in this like, "Oh, I'd love to try this out, but we're gonna have to do the zero dollar PO for a three-month." Like, it just solves so many logistical problems. Let's just say like, "Eh, let's, you know, let's try this out, and then we'll figure out what works for us, what doesn't work for us. We can have conversations around it. It's less of this, "Oh, let's talk about a possibility here on a slide deck," and more of like, "Well, let's just turn it on and use it for a bit and see how it goes. That's great. Tommy, I'd love to hear from you too. You've got a growing number of engineers using it, a bunch of different personas. You're a power user of our Errors Inbox tool. A lot of what we talk about is we've got this unified Telemetry Data Platform, which we have all of these verticals that are tied together and then these horizontals that help see across. Maybe tell us a little bit about how you use the New Relic products you use. Yeah. Errors Inbox is huge for us. Once that came out, it was like a godsend for our SRE, CRE team, et cetera, across the board. We use that from like a, more of a shift left standpoint, right? Before even going to production, our QA environment, stage environment, we're monitoring Errors Inbox, and that has to be clean or triaged, et cetera. Likewise, daily routine for production, we do daily releases, et cetera. Errors Inbox has been awesome from that point of view. Beforehand, it was scattered all over the place. It doesn't really group things together nicely. Now you can say, "Hey, this one's being acknowledged and being tracked by XYZ," whatever it might be. Helped out our process so much better on that front. Outside of that, APM is awesome. I've had so many good experiences with New Relic, with APM. I've been using New Relic for like eight years, and I can identify issues within 15 seconds, right? And have a resolution for things that are happening. We have an awesome story about over the past six months, dealing with a vendor of ours, actually. We actually installed New Relic on their machine, going to our account, and we fixed their performance issue on their database in 15 minutes without knowing anything about their database schema, anything like that in between. We fixed the issue for one of our 3PLs that we were dealing with, and they were just having all kinds of issues. Just really cool things that just you can tell somebody about how to do this, how to install it. You can talk about agent installation. Boom, out there, look at the stuff. Oh, SQL Server, you're doing this wrong, your index is here, et cetera. Boom, fixed. Out the door, right? It's just a really cool story to see on that side of things. Synthetics, you know, we use Synthetics, APM, Logs, Errors Inbox. Those are kind of the four main infra also. But all great tools, all fit the developer life cycle, right? Giving an X-ray vision into our application across the board. That's like the way we like to think of it by New Relic, right? The X-ray machine, you can see, you can drill down into anything you want to, external services, et cetera. U.S. East 2. If U.S. East 1 went out, a couple times over the past six months, you can look at external services. Oh yeah, this app must be running on U.S. East one right here or something like that because our content falls out or something like that, right? High visibility, and you know, just like that, what's going on with your application and respond and give a great customer experience too. Great. Mark, anything else to add in terms of the products you use? You mentioned that you use, I think, pretty much all of them, is how you put it. And it's sort of opt-in on a team-by-team basis, right? Yeah. You know, to his point, at a scale of hundreds of development teams on different products, the needs are different, right? My organization built to serve those teams, we can offer, you know, the full suite of tools, and they come, and they use what they need. From a management model, you know, to be able to just have them pick it up, there's no PO, there's no licensing, there's no activating a new product. It is just there, and we start consuming. It's highly aligned with the way we wanna think about the investment for a new business strategy, right? This consumption model reminds me a lot of the same things that made public cloud itself successful, right? Whichever one you pick, right? Cox Automotive is an all-in AWS shop, but we have work in Azure and GCP too. This idea that I have a new product idea, I wanna experiment, I wanna iterate, and I just wanna start paying the cost of goods sold to do an experiment in a lean startup sort of thinking style. When I find out that's a terrible product idea, I want to stop spending, right? This lets me align that business strategy with the cost of exploring that new space and stopping. You know, we had an executive business review with you guys recently, and our team that manages the finances around this came to the table and said, "We get an overage invoice every month from New Relic, and we are very happy about that because we pay what we are committed to consume, and then we pay more as we consume more, and we pay less as we consume less," right? That line has not trended down, and we see that overage bill every month, and we're happy to see it 'cause we know every dollar on that invoice is some value tied to some business strategy. That's awesome. That was gonna be my next question, so thanks for leading out there, which is, you know, and when you and I talked about it, I think I used the term how do you defend the cost if it's ever asked? You said that implies there's some contention and it's not. You know, I'd love to hear, we heard from you. Anything else to add, feel free. Steve or Tommy, any how do you think about, you know, you spend a certain amount on New Relic and the value you get from that, and whether you can quantify it or how you make that choice? Yeah. From my point of view, it's engineers are very expensive in the first place, right? When you are paying somebody hundreds of thousands of dollars, possibly, et cetera, it's pretty easy to justify the cost when you can say you can debug something for 30 seconds or five minutes rather than trying to go from tool A to B, C, going around in circles, trying to figure out what's going on. Before you know it, that's three hours gone, right? That's your entire productivity gone. This is usually gonna be your SRE people that are highly paid, or you have senior engineers that you want to be implementing code, not debugging things in production. Those types of things, that's huge value, huge value gained on that side of things. That's kind of the easy way to say to justify the cost of paying $300 a month for a user, per user, right? If you figure out how many times you escalate in kind of debugging things in production or stage or dev, whatever environment, it definitely pays for itself. We experienced almost the reverse example of that story, right? Everyone talked about, "Oh, I use this tool, and I found the problem in five minutes," right? We have a team who was not adopting New Relic, and they were on one of the competitive products. They had an outage that took them about three to four hours to solve. They sat down. They happened to be instrumented with New Relic but did not use it during that outage. They sat down with our account team. We walked back through the timeline and the data and the history. Without having, like, you know, staged it, they used the tools, they went through Lookout, and in five minutes they found the root cause afterwards. Our team did that with us too. Lookout's another example of the horizontal that helps tie across. Yeah. Now that team, having seen the opportunity they missed during that incident and knowing just how bad, financially, that incident cost them, they have now become high adopters of New Relic and replaced that other product. It's a great story. I wish it had happened the other way and you didn't experience the outage. Did we. Thanks for that. The simple answer, about six months after I joined the company, we had an outage that had a top-line revenue impact larger than our New Relic bill a few times over. That's like the super simple example, right? This was early in our journey and so that hasn't happened since because we then invested in not just having the tool but knowing how to use the tool and incorporating it into the development life cycle, et cetera. I think, you know, the fuzzier answer here is I would predict it improves a developer's efficiency by at least 10%. When you factor in a fifth of our company is technical, they're generally speaking the highest paid individuals. Like, it's pretty simple math to say, you know, spending this to improve productivity by 10% is a bit of a no-brainer. That's great. Last question I had, you've both already answered. Tommy, you didn't have a chance to sing the praises of your account team, but even pulling up a level, you know, Manav talks a lot about value creation plans and the joint implementation plan and how you know, we help support your objectives. I'd love to hear some stories about how your account teams have supported you on the journey. Yeah. For Vault Health, our accounts is a little bit different, right? We grew from five engineers to 90 engineers within a year, right? That's pretty big growth for a small company and trying to get everybody contributing at the right fashion, et cetera. Our volume is very small, right? When you talk about data ingest and paying for that, it's hard to justify cost for Vault Health to pay this much money for all these users with very little ingest, on that side of things. Our account team was excellent on that side of things. Just trying to scope the budget for us, trying to get the right price for us, right value for us across the board, and just understanding our use case, our growth, our needs that we want to, saying that we're going to grow this much and laughing in our face like, "You're not going to grow this much at all in a year," or anything like that. You know, doing it, and Jackie did awesome for us, just helping us out. We have a plan now that fits our needs, our wants, and kind of fits our mold of what we want with Observability for All, right? We want everybody using New Relic, and account team did excellent job understanding our use case and You've also got a significant number of core users as well, so kind of working across those price points. Yep, yep, for sure. Thanks. Anything else to add to those or anything? Closing remarks. I'll just say thank you so much for investing the time here, but more importantly, for being such strong partners for us and for spending the time with us today. Thanks for telling our story. Thank you. All right. Now we're gonna have Mark Sachleben then come up. Good. Okay. Thank you. I guess keeping with the introductions, I actually was an engineer, but not that kind of engineer. of engineer. I was a fluid engineer. Now I'm a finance person, but I guess I'd really say I'm a numbers person who loves business. Thanks very much to the customers, and thank you all for coming to join us today. Appreciate you taking the time to hear more about our story. I'm gonna go through some numbers since I'm a numbers person, and some of which you've seen. I'll go through pretty quickly and then give a little bit more color on some of the slides. First thing I wanna go through is revenue growth. Top line growth. Very excited to say that as you've heard, we were able to accelerate revenue growth last year in fiscal 2022 from 11% in fiscal 2021 to 17.5% in fiscal 2022. That's a great achievement for us. We're thrilled about it. It's a great, you know, sets us on a great trajectory for our hitting our next milestone, which we put out there as market rate growth in the intermediate term. That's the next milestone. We certainly expect to get beyond that. But this sets us up well on that trajectory. As you know, we just reported our Q4 full year results for last quarter. A week ago, we came up and we talked about what we did for the quarter and for the year. If you think back to a year ago, if you had told us or if we had talked internally and said, "We're gonna deliver 17.5% growth coming off a couple quarters where we had been under sub-10% growth," I think we all would have been really excited. We delivered that, and you know what? We are all really excited. We're not satisfied, but we're really excited because we know we have more work to do, but we feel like we're on a good trajectory. You know, we've gone through a lot over the last couple of years. You've heard about, we've talked about this migration, the change. We've changed our, you know, our business model. We moved to the platform. We've also migrated out of our own data centers. Tremendous amount of change, and change is hard. As we're going through this, a lot of times we talk to investors, we hear from investors, and they say, "You know, we talk to all these customers, we get all these market data points, and it seems like your product's doing great. It seems like you're doing very well, but the headline numbers haven't caught up with where we see you." I think we feel that same way. We feel like the headline numbers aren't quite there. What we've been doing over the course of this year, and we're doing more today, is to give you some of the secondary metrics to show some of those trends as to how we feel, how we're doing and what we're doing. Those secondary metrics are pointing in a good direction. You know, we feel like we're making real good progress that way. In spite of the fact that I'm a numbers person, I think when I look back at fiscal 2022, one of the things that I think was actually biggest for us in the long term wasn't even, you know, it's kind of a, it's more of an intangible, and that is the mind shift that we made from our old business model to our new business model. I had an earlier conversation today where I equated it, and I think it's really interesting analogy. It's like learning a foreign language. Like, the first thing you do, I studied French, so the first thing I was starting to learn French and, you know, they say something in French, I translate it in my mind in English. I kind of, "Okay, how am I doing this?" All right. I say it back to them, you know, and then I hope I didn't just order a shoe for dinner or something. You know, it's that type of thing. When I think of when we started talking about a consumption model, I did the same thing in my head. This is a couple of years ago now because we've been at it for a while, but I would immediately think of subscription metrics, kind of trying to find a comparable in a consumption model, do the translation, and then see how they equated. That's on the finance team. The product team went through the same thing. The sales organization, they used to sell commitments. They got paid on commitments. That was their life. Now they sell consumption. They get paid on consumption. That's their life. What I feel like is we have made the transition from doing that translation in our head to really thinking about it. We're thinking in that foreign language. We're thinking in the language of consumption. We're operating it as a business as a platform and with a consumption mindset. I think Manav, Kristy, and Bill, Peter probably all agree, at this point, we dream consumption. I think we have made that transition. Yeah, that's right. We also gave guidance for fiscal 2023. You know, given where we are, we feel comfortable and we're confident that we're on a nice path. We're gonna be able to continue that acceleration on the top line. From the bottom-line standpoint, we have said that we're gonna have a loss in Q1, a size of $23 million-$25 million dollar loss in Q1 and roughly the same loss for the year. You do that math, it's nice and easy. That says over the course of the nine months following Q1, we'll be break even for the year. Now, this is a little different than the guidance we had talked about, or not guidance, but the indications we'd given earlier. You know, we felt like we should be a little conservative here given a couple factors. One, we had the best onboarding quarter we've ever had in Q4. Great news. Everyone's, you know. It's a real tough environment to hire. That was great news. Second, we had our lowest attrition rates of the year in Q4. Again, attrition is a significant problem. Companies are talking about it all around, the Great Resignation, all that. That was great. Unfortunately, it is a tough hiring environment, and we're seeing inflation, we're seeing wage inflation. When you look at our income statement, we're a software company, two-thirds plus of our expenses are compensation. You know, if you're looking at merit increases and compensation, that's 2% or 3% above what you thought. You do that math, and you realize that starts to eat into your income statement. We factored that into our guide for the year. Also, we are looking at accelerating, bringing forward a lot of our hiring for this year. When we look out, we wanna bring people on board. We're able to hire now. Let's do it. Let's get them on board. That way, it's more likely we'll be able to meet our ambitious goals for the year. Here's the chart on revenue growth. You can see the last eight quarters of revenue growth. The first four quarters were generally governed by our subscription model, and we had a certain pattern where a lot of you know our big renewal quarters were Q3, Q4. You know, that's where you got your increase, et cetera. You got a bigger increase in revenue in Q1 and Q4 and Q1. We are now on a subscription model. During this transition, converting consumption to revenue, there's a lot of nuance in that accounting. I won't get into it, but it meant that it was a little bit lumpy. You can see in Q2, we had a big increase in revenue. Then it was a little variable throughout the course of the year, when in fact, when you look at our underlying consumption patterns, they were more consistent. I'll show those in just a minute. I put this up here just to show that during this transition period, things were a little lumpy. I'd encourage people to look at, you know, 12-month or four-quarter periods of time, 12-month period of time to see how we're doing during this transition. As we go forward, we think consumption, the translation from consumption to revenue is going to be much more correlated. As we get through this, things like compares and things like that'll will make more sense. As we go through this year, the Q2 compare, for instance, is gonna be tough, right? Because we had such a big Q2 last year where we had some catch-up revenue and things like that. Let's look at our underlying consumption. We introduced this chart in our investor letter last week and had a lot of questions about it, and it really is so important to our business. We'll take a few minutes to first explain what it is and then talk about some of the dynamics in there. What CRR for us is, it is the daily run rate of the company. Literally every customer that's on a consumption buying program, and which is the vast majority of our business, we look at how much data times the price of the data, usually $0.25. Then we look at how many provision users times their contracted rate of provision users per month. We annualize it. We do add the legacy business in at their run rate, and we get basically a daily consumption run rate. We look at that every day, some of us more than once a day. That really tells us how we're doing. When I talk about, you know, us really dreaming or this getting ingrained, this is now ingrained into the way we run the company, looking at consumption and consumption run rate. This is what really governs a lot of our behavior and helps our thinking. What this chart is, this is the 30-day or the monthly average of the 30 or 31 days in the month. That's what this represents. You can see a nice steady increase. There's only one dip in this chart, and it shows up in January. Now, I want to explain what happened. We talked about this as a seasonal dip around the holidays. In fact, December was where we saw that seasonal dip occur. The first half of December was quite good. The second half of December, starting mid-month and then continuing, especially during the holiday week, we saw a drop in consumption. I look back over the last 12 months, the only month of all those 12 months where you could say the back half of the month was worse than the first half was December. Every other month, the back half's been better. It's been a pretty consistent pattern other than December. We talked about that softness coming out into the new year and then, say, but what about January? Looks like it was a down month. Well, actually, when you look at January 1st to January 31st, consumption rose, just not as much as we had expected. In a consumption model, the beginning period is always critical, right? If you're looking at a year, it's how you do in the first quarter. If you're looking at a quarter, it's how do you do in the first month. If you look at a month, it's how you do in the first week. January, things rose, just not as much as we had expected. February, similarly. February 1 to February 28, consumption rose, just not as much as we had expected. The recovery coming out of the seasonal lull wasn't as fast as expected. We looked into that, and we mentioned this on the call last week. What was driving that? One of the big factors driving that was customers who were running hot. We define running hot as about 130% or more of your contract. You're loving the product. You're consuming a lot of it. You know, we look at those great customers, right? They had slowed their growth, and in some cases had reduced their consumption in Q4, in the January-February timeframe. That was a drag on our overall growth. You look at why would this happen? How would this happen? We went back. This didn't happen in our 3Q. This behavior didn't happen in October, November with the customers that were running hot or up for renewal in December. It just happened in this cohort. You know, what's going on? Well, remember, 100% of consumption means that right about nine months you've consumed your full commitment. At that point, oh, you're over budget, right? What happens in January? Everyone is focused on budgets. Everyone, you know, as everyone's planning and, oh my gosh, you're a little bit over. They just established a straight line, by the end of the year, we're going to be broke. You know, all this panic around budgets and real high intense focus on budgets in that January sort of timeframe. At the same time, you have these customers who are loving the product, getting a ton of value, but they're saying, "Oh my gosh, I'm squeezing the budget." What do they do? They do some house They do their spring cleaning. They say, "All right. Look, let's look at, you know, those people moved out of the department. We don't have to provision them." They clean up their users, and they, you know, I think it's healthy, but their consumption, the growth slows, and as I said, in some cases decline. We got through that, and then you can see in March things pick up again. March, April, things get back to, you know, what we'd expect as normal. You know, this has been a learning process. It's something we learned about, things we have to do as we go forward and things we can do to prevent that as we go forward. First of all, we, you know, we've seen the whole year now a much better sense for how to plan for this and how to manage it. These customers that are running hot, you know, we've got to make sure they're understanding the value, make sure they understand where they are in advance of getting to that critical point, and then also make sure they're on the right contract. You know, early renewal. Let's get them an appropriate contract that is appropriately sized for them, so they don't have a budget owner come and say, "Hold on. You got to do something." We just have to work with them more proactively and get them onto the right vehicle in advance. By doing that, we feel like we'll be able to get a much better control as we go forward. This slide is something we've never published before. It's interesting. This is called improve retention. We call this internally churn, and we didn't put churn as a headline on the slide because so many people have so many different views of churn. I'll just give you what our definition is in this slide. This is the percentage of dollars on a dollar basis, the percentage of customers who were up for renewal in a quarter, who basically left the franchise, who said, "I'm not paying New Relic any more money right now." You can see, you know, if you go to PayGo, for instance, you're not included in this slide because what we see is PayGo customers a lot of times end up consuming more than they were on their old model. This is just the people who've left. As long as they stay with us, we have a chance to grow them. This is the number ones who left. As you can see, seven quarters ago, that was the quarter we introduced the new model. Since then, we have had seen a great progression, and for the last year, we've seen four quarters of steadily improving performance. When we look out, we think there's room to even perform and improve even more. We're at the stage now where customers are familiar with the model. They have history to look back on. It's no longer. You know, the first conversation is, "Oh my gosh, what are you doing to me? Why are you changing the model? My pricing." The next question is, "Well, how much am I going to use?" Now they have comfort with the model. They're embracing the platform, they're embracing the pricing, and they have history to go back on to say, "Okay." Here's what I'm doing in the past. This is what I'm doing in the future. Here are the tools I can take out. Here's what other budget I can get. Here's what I could commit to. It's also their own decision. Our reps are no longer compensated by promoting as high a number as possible. Sure, it's in their, you know, secondary incentive to do that, but it's no longer that kind of antagonistic relationship. The customers are doing that. We're at a stage now where customers are getting more and more comfortable with the model, more and more comfortable with growth. You know, anecdotally, what we're seeing, and we're trying to do some more digging into these numbers, but the longer folks, we only got 18 months, really, of history, but the folks that are on the model for a longer period of time, those growth and behavior characteristics seem to be the best of any cohort. It just, you know, there's a familiarity to it that really helps. We think we can improve here as we continue to improve here as well. Net revenue retention is the consumption equivalent a lot of times what people think about a subscription metric, about people going up and down like this. This is a better. It's a 12-month look as to what our customers are doing. You can see it's a trailing metric and generally follows revenue. The thing I wanna point out here, though, is that the under 25K segment is actually better than our average, which may strike you as odd. Struck me as odd, certainly. When you think about the under 25K segment, these are transient customers that come in and out, they bounce, they come. They're super price sensitive. You know, that's the stereotype of that customer base. You know, what I think is going on is under 25K customers for us, these are not small companies, but they're small installations. They're small implementations of our product. In many cases, they're new. They don't have the legacy baggage of thinking of New Relic as an APM company worth this amount of money. They come in, they get the platform, right? They don't sign up for APM. Maybe they think they're coming for APM, but they get the platform from the get-go. You see those growth characteristics of these companies. Even if they migrate it over, maybe they used to have two hosts or something, and they migrate over. It's a fresh look. They're on this better model. They start to grow, and you see these great growth characteristics. Now, these small implementations generally lead the big ones, right? In all sorts of ways, in what technology they adopt, all sorts of things. What, you know, I'm optimistic is that these type of characteristics we're seeing from these companies that don't come in with the baggage about what New Relic used to be, that these type of characteristics are gonna grow up with the customer base, and we're gonna see these type of characteristics in our larger customers as well as, you know, as we get beyond the history. You know, it's a really interesting performance. I do see that, you know, I think that that'll be great when we do get more and more customers beyond the "Okay, this is what New Relic is. No, this is my old model for New Relic." All right, turning to bottom line. Over the last two years, we've had a lot going on. I mentioned all those changes, and it has impacted our bottom line. You can see the graph here. You know, two things in particular I would call out. One is our cost of goods. Our gross margin has declined over the last couple of years, and that's been driven by a number of things. I'll talk about that in just a minute. Our sales and marketing spends, we talked about on a call. We are amortizing sales and commission costs that are from our old model. They're non-cash costs. It's an accounting change that drove it. Last year, it was $34 million. If you reduce that loss by $34 million, we actually improved a little bit in the bottom line. This current year, fiscal 2023, it's $23 million. If you look at our guide for the year, you subtract that out, we're roughly getting to, you know, apples-to-apples basis, getting to break even for the year. Let's talk about COGS. After four quarters in the 60s%, pleased that we got to 71% in Q4, and we've guided to mid-70s% exiting fiscal 2023. About a third of that, we said, is coming from data center migration, where we will be completely out of our data centers by the end of the year. We've been working on this for the last couple of years. Around the world, we're moving to the cloud, and we've had this double bubble cost. These are costs that are gonna be, you know, gradually filtering out over the course of this year. By the end of the year, they will be completely gone. Then the other two-thirds of this are coming from optimizations. What we focused on over the last couple of years is the transformation and the transition to the new model, to the platform, getting all this data, scaling, making sure our customers have outstanding performance. We haven't yet gone through and optimized for operations in the cloud. Now, these are things that we're starting to work on. You see, we made some progress last quarter. These are projects that we have planned. In many cases, they're staffed. In many cases, they're underway. These are things that we've identified. They're gonna be able to help us improve this gross margin to the mid-70s% by the end of the year. On the sales and marketing line. A couple years ago, we recognized our sales and marketing costs were very high. We've talked about that. You know, when you take out those commission costs I mentioned and you look, our sales and marketing spend hasn't changed that much over the last couple years. In fact, last year, it was basically flat year-over-year, and yet we were able to re-accelerate our top line. We were able to get customer growth again, and we were able to do that, keeping these commissions flat. Keeping sales and marketing expenses flat. In fact, over the last two years, we've been able to grow revenue significantly, and we've dropped 10 points as sales and marketing as a percentage of revenue. We've made progress. We have plans to continue to drive efficiency here, and a lot of the work Manav talked about drives that. We think there's more room here, and we're gonna keep working on it. Now, when you put this together, you think of the cost improvements we have. We're getting out of the data center, the sales and marketing improvements we've had. It positions us for a fiscal 2024. We're not giving guidance there, but you can see where the trend lines are very favorable into starting to get into, you know, into much better position from a bottom-line standpoint in fiscal 2024. With that, I'd like to bring up Bill to go through the last couple conclusions and then we'll get to the name. Thanks, Mark. We wanted to close with sort of one, one, five. Not sure what happened to the numbering there. Five reasons that we love this business and are committed to it so passionately. First, we have the luxury of working in a very healthy category where it's large, it's under-penetrated, it's growing fast. Second, we believe we have a really unique and differentiated position, hard-fought and established over the last two years, especially with our hyperscale data platform and this all-in-one observability experience. Third, the business model transition we did to consumption really is customer-centric, and we believe overdue. If you think about this category and the major players in it, and the history of customer complaints around exorbitant bills and out-of-control budgets, we believe consumption model's a fair exchange of value and an inevitability, not only for this category, but for enterprise software. We wanna be pioneers, and we believe it's a long-term structural advantage. It's not easy to do, as we've proven, to do the shift from subscription to consumption. We're largely through it, and it's gonna be a strength for us going forward. Fourth, we have made the really important supporting move with the consumption business to shift our go-to-market strategy to focus on customer success, to, you know, support that consumption growth versus driving commitments, the traditional enterprise selling motion around subscriptions. That as well is a reason that consumption companies have the growth characteristics they do because when you focus on the customer and you're more obsessed about their success than your own, it's you know putting the horse before the cart. It's helping you know rise all boats, the customer success as well as the company's. We're really excited to have done that. We made the bold move in FY 2022 at the beginning of last year to shift commissions 100% towards consumption to make sure that our reps' incentives are aligned with our customers, and that's paying off for us. You saw that churn chart that Mark showed earlier, FY 2021 churn very high. I think one of the major drivers around that reduced churn and consistent improvement over the last four quarters is that shift around alignment of incentives. Fifth, as Mark just described, between the amortized commission expense, the exiting of our data centers, and operating improvements in public cloud, we believe we have a clear path to non-GAAP profitability with continued margin improvement once these double bubbles essentially are taken off. Five great reasons that we're excited to be in this business, and I hope that you see those opportunities as well. With that, I think we're moving to Q&A. Team, why don't you come up? Well, maybe we should sit down there. The camera. Yeah. Sure. Try this one. Can we turn it, please? Can we turn the projector off, so we're not blind by the light? Now it's on. Oh, wow. Lots of hands. Who's moderating? Kristy. Peter's doing it. Peter. Yeah, I'll go ahead and do it. Let's go start. Just state your name for the folks dialing in. Hi. Good evening. Keith Bachman from BMO Capital Markets. Thanks very much for doing this. Particularly enjoyed the customer segment. Wanted to start with you. You identified the vulnerability suite today at the keynote. If you could just start, what do you think differentiates that? You know, Datadog and Dynatrace have been out talking about similar. Yeah. Characteristic. What distinguishes New Relic in this regard? I had a follow-up question. Great question. Before I answer it, since you mentioned the customers and some of them are still back here. Who's paying who here? I mean, isn't that amazing? Every time I have these customer conversations, I feel like I should be paying them because their story, they tell our story so much better than we do sometimes. Thank you all back in the room because we didn't pay them. They really speak passionately about the value. We paid them in all the value we created for them. Maybe there's that. I love the customer stories, and you saw them in the keynote as well, some great customers. It's the best part of the job. Speaking about security and the differentiation there. You know, I mentioned in the keynote a lot of people have been asking, customers have been asking, investors have been asking, "When are you going to do security? All the competitors are doing security." We have, you know, wanted to do it, but we wanted to do it when the time was right. We needed to get through the business model transition. We needed to get the platform model in place. We wanted to do it not chasing their coattails, but doing it in our way. Our way, as maybe you saw in the keynote, is data-centric and as a platform. Competitors, both the competitors you mentioned, actually are implementing their own security product, instrumentation capabilities. We have that ability, too. Our agents collect information. Like, if you remember the demo he showed at the very end, that library explorer, where you could look up one library and see everywhere in your system, all the versions of it that were potentially at risk. We collect that telemetry already on behalf of our customers, and now we're exposing it as a security feature. We're going a step beyond that because we're doing what our competitors aren't, which is partnering with the security ecosystem to, just like we do on observability and DevOps, to bring all that telemetry into our platform, to correlate it, to prioritize it, and then help customers work across the silos. Because it's the exact same problem as observability. You have infrastructure teams with infrastructure security threats. You have application teams with application security threats. Those teams today, again, different vendors, different silos. You know, we're taking that data-centric approach to bring all of those vulnerabilities in, helping correlate them, helping prioritize them, supplementing them with our own telemetry, and then presenting it up to customers in a more, we think, coherent way of attacking security. That's our approach. Really excited to get into that market. If I can. Oh. If I can quickly just add, too. One of the things that's exciting about this approach is one of our first customers is ourselves. Jointly on the implementation team, on the development team with our product teams is our CISO, Esteban Gutierrez. Then one of the breakouts here today is being led jointly by Kymberlee Price, who runs product security for us. Of course, we'll be partnering with our customers through the preview period to continue to refine it. I'm glad you brought that up because, you know, security is not a new problem, and it's a complex problem. Nearly every IT team already has security solutions that they have implemented for different parts of their tech stack and different parts of their software component. Enterprise IT teams, enterprise software teams don't want one more tool to add on to it, right? Because that silo makes it harder to see what's really going on and separate signal from noise, right? What we are doing different than our competitors is that no one vendor can solve the security problem. It is going to be a multi-vendor approach. We're bringing, like Bill was saying, aggregating and unifying those signals across, and taking a customer-centric approach here and a partner-centric approach here. That's what's different. The adoption is going to be, you know, it's a different path. I'll ask my second question and just pass the mic, because I wanted to just ask about pricing for a second. You have a per user and a consumption-based components. The broader question is, do you feel like you have a stable pricing framework right now in terms of dynamics between those two? Secondly, do you think you have an elastic demand curve? You're raising prices by, call it $0.20-$0.30. You may not want to say this in front of your customers, but do you feel like you have something like Atlassian where you might have a runway depending on how the mix shakes out or whatnot, where you could see increasing prices over time that could benefit for all the development and things along those? Just wanted to hear more broadly about pricing. Thanks very much. Yeah. When we first entered the platform consumption model, we had no data. I mean, no one's done user data pricing before. No one's done consumption in this category before. We built a hypothesis around the following. First, we believe data is not just important but absolutely required in order to create insights that then users can action. The prior pricing models were really data-centric, you know. Different metrics, we charge by the gigabyte today, but hosts is effectively a data model, database pricing model. The prices were so high, even from New Relic, that it limited customers' ability to even capture the data because they had to sample, you know, decide where they were going to deploy those agents in the first place. We wanted to lower the price of data as low as we could to encourage sending more data, therefore giving us ability to generate more insights, therefore delivering the value and the bulk of the cost of the platform through the user price meter, where there's that obvious alignment in terms of customer value. The engineers getting value, of course, that's where they're also willing to pay. That was our hypothesis. That's what we entered into. We based the data price element on our costs. One of the differences with this business than lots of traditional, you think about Salesforce and CRM as an example. The data set with CRM is much different than the data set with observability. That data set's a relatively small relational data set that doesn't change a lot. Observability has a streaming data set with large data volumes and lots of data processing involved. There's inherent cost to it that has to be contained somewhere. We had a data element where we had to capture the cost and pass that along to customers. That effectively, we estimate to be about one third of the total contract for most customers on average. There's customers who have lots more data and fewer users, and some who have lots less data and lots more users, but that's on average. The rest of the cost we would capture in terms of user price. We did pricing studies, including elasticity studies on that, you know, with third parties to assess what we could charge for and what the elasticity would be. We went into market. What we've seen is a few dynamics play out. One is the low data price is definitely attractive to customers. It's increasing. That's I think what's driving the 50% year-over-year growth. I shared even in today's keynote, some of the price comparisons with competitors were significantly lower per incremental host or gigabyte. We've also seen user growth, which we knew would be lagging because, again, we're creating the data gravity well, bringing the data in, we're creating insights. But to get to user growth, we need to ensure that customers understand the platform and can start to benefit from it. If they're not using it, then they're not willing to pay for it. The second element around user growth that's a little bit more difficult than data growth is it's easy to manage. Administrators, who are often the buyers, can easily say this, you know, "Joe has access and Mary does not." "I don't care, Mary, if you think you need it, we don't have budget. We're not gonna provision you until next month or next quarter." With data growth, it's a little bit more ephemeral because engineers are instrumenting systems, and there's not a buyer admin persona usually in between. If there is, it's kind of after the fact. It puts more friction on the user growth, less on the data growth. That's caused both of those elements have caused us to trend more towards 40/60, per our last report. We believe that the price raise from $0.25- $0.30, which we're putting into effect June 1, is necessary, and customers so far in all the conversations we have seem to understand it because we've added a ton of value on the data platform side. We have not increased prices for two years, and our costs, just as you know, doing business and processing all of that data, are going up. Again, it's a cost plus model. We're passing that along to customers, but it's still a great savings. The new SKU, the Data Plus SKU that's at $0.50, that's also driven by increased cost. If you look at the features that we're bundling there, like increased retention, well, increased retention comes with an increased cost for us, so we have to capture that somewhere. You look at increased query capacity, well, that comes in the form of increased compute for us, so we have to pass along the cost there. Yes, it's a higher priced SKU, but it's also a higher value SKU, and we believe beneficial to customers and some will be willing to pay for it. Yeah, we believe that, you know, the value is there, and we'll see about the adoption. We'll also see how it affects ingest rates. I'm optimistic that customers will continue to ingest in increases they have, but, you know, you don't know until we do it. I might add one data point that you shared earlier today, which is that the marginal cost of adding instrumentation on a host with New Relic with the $0.30 New price is $4 a host. The same thing with our chief competitor is $15-$25 a host. Even with the increased $0.25-$0. 30 price, our customers are getting great economics as they expand their footprint. All right. Thanks, Rishi Jaluria, RBC. Really appreciate all the detail, and thank you so much for doing this. Nice to be able to do this in person again. I just wanted to get a little bit more color on the churn rates you were talking about with that 23% churn number in F2Q 2021, if I'm not mistaken. I guess to clarify, that doesn't include downgrades. That's just full unplugging the platform. Correct. Maybe you can help us understand, you know, what happened there, right? Did they move to competitors? Did any of them come back to the New Relic platform? You know, maybe help us understand why was the impact so outside from doing this model transition, given your competitors aren't on a full consumption platform the way you are. A lot of them do have consumption elements, you know, even if it's just on a module by module basis. Some more color there would be helpful. I have a quick follow-up. If you saw that outsized quarter Q2, Q1 was 13%, so more than twice what it is today. I think our didn't show prior to that year, but I think our churn, and correct me if I'm wrong, I think it was still fairly high even the year before, too high for several years. Bill, just to clarify just with that number as well, that was the quarter we introduced the key change. We introduced the free tier. Customers, anyone paying less than $8,000 or something, it was kind of crazy if they didn't go to free. It's a relatively small cohort, our September cohort, so that's with dollars. You know, that's a pretty frightening number, right? You see that 23%. Just to put some sense to it, that was one of the reasons it spiked up. As Bill said, it was elevated prior to that as well. Multiple reasons driving that. You know, first I'd say product competitiveness. I think we started to struggle with that probably FY 2019, and 2020 was elevating the churn number. I think, you know, when we introduced the new platform pricing model in FY 2021, there's also, you know, lack of experience and lack of ability for our go-to-market team to communicate that when it was brand new. I don't think we did it very well, frankly. The leaders in the go-to-market organization at the time are no longer with us. There is a certain mindset. I love the language analogy that Mark used, you know. There's a certain mindset associated with enterprise selling and subscription. The leaders at the time in the company and many of the sellers had that mindset and tried to understand the new language, but were not effective at speaking it. Oftentimes it came across as tone deaf to customers, unfortunately. I heard a number of customers who were pretty unhappy with how we communicated those pricing changes. Fortunately, we learned from that. We got better over time, and new leadership came in that really embraced this, consumption model and helped, starting in FY 2022, and you see immediately the improvements on that and consistent improvement over the years. I think also I mentioned the conditions change from rewarding on commitments versus consumption also has helped with the churn. It's multiple factors there. Oh, the product definitely is much stronger than it's been for several years, and that obviously helps customer churn as well. All right, great. Just a quick follow-up. I mean, you had a, you know, what looked like a relatively lower or worse than expected January and February on a CRR basis. By the way, we'd all love if you start disclosing that as a metric quarterly. As we just think about, you mentioned that was a result of customers running hot and, you know, kind of doing some spring cleaning. Mark, you used the language that you used. What are you doing to prevent that from happening again? Is it a matter of just better leveraging these inside salespeople to get contracts, you know, more in line with what reality is gonna be? What can you do to prevent that sort of situation from happening again? Yeah. Thanks. A couple really obvious things in retrospect that we're now doing consistently is we've had the usage information in the product experience. Budget holders often aren't in the product experience. They're not engineers. They're not seeing that information enough. We've been relying on the AE to communicate that. We wanna deliver that information front and center to budget holders, admins upfront, so they're educated, so that they know the consumption rate and whether it's exceeding, you know, the commitment rate and have a chance to plan and prepare for that. No one likes to be surprised with, you know, surprise bills. The second thing is, again, these are our most successful customers. These are customers who are consuming 130%+ of their commitment. What we need to do is help them understand the value of that consumption and also capture the budget around that additional value of the consumption that they're making. You know, again, because our heroes are in the accounts that hold the budgets. They have constituencies, they have stakeholders they have to manage, whether it's the finance or procurement or their executive team. We wanna work with them earlier in the cycle if we need to pull forward renewals with that value plan to say, "Hey, look, you've expanded, you've added these additional projects. Let's capture the budget associated with those so you're not having to go justify a 30%, 50%, 75% overage when it comes up to the new fiscal year boundary." Early renewal is another key part of driving that. You can't ever overstate how hard it is to go through that renewal conversation. It's almost like the last massive subscription model, even though it is moving on to consumption. It's a ton of toil. Our account teams were spending a lot of their conversation time and a lot of their key in-person time doing that, as opposed to saying, "Hey, what do you need? How can we add more value?" Frankly, finding those budgets and aligning our solutions against those budgets, which they're doing now, and they're doing well in advance. Whether it's early renewals or whether it's just earlier in the life of that contract, they're able to spend their time doing that. A question in the back here. Yeah. If you can see me? There we go. Eric Heath with KeyBank. Again, great event. Appreciate you doing this. Bill, I guess just for you. I mean, we talked about the market growth rate kind of being 25%, and you're trying to get there, and the product's come a long way. Mark had comments about kind of the disruption we had with moving to the consumption model. It's been a headwind to kind of getting back to that growth rate. I guess in your view, what's the trigger? What's the tipping point that gets us that we should be looking out for that kind of gets you to that market growth rate? I don't think there's a trigger point. I actually would say I disagree with the consumption business model being a headwind. I think it's actually corrected some of the challenges that we had in the prior business. If you look at the re-acceleration of year-over-year revenue growth rates actually started as soon as we shifted to being all in on consumption and migrating the business. So we're on the right track. All the secondary metrics show the progression. Revenue's always the lagging indicator. It's always the last thing to fall in line, and no doubt we have room to go there. It's about building the machine. You know, the machine, the business machine spans as I love Manav's presentation because it talks about, you know, the full cycle of getting customers engaged and then expanding. A part of that machine is missing as well, not only the go-to-market, but the G&A functions in terms of contracting and capturing that revenue efficiently. You know, we're building that machine, and there's no shortcuts to getting that to be hyper-efficient. It gets better and better with every turn. You know, some of our competitors have enjoyed being in a business for three, four, five years consistent without having to do the transition we've done. Their efficiency level, the operational efficiency of that machine is just higher than us. That's what we're working on. There's unfortunately no shortcuts. We just wanna see every quarter continue to best the quarter before it. Hi, Gabriel Roade with Canaccord Genuity. I'm trying to have a better understanding of the motivation behind the bundling of Data Plus. If you guys are seeing more adoption of new products from customers and the increase in like the products that they use, and also you're trying to improve the margins and you have a higher cost behind it, why bundle together all these products on a lower discounted price in a way? Yeah, good question. The first reason is just simplicity. Selling those add-ons is complex. It takes time again. You know, when we see patterns of interest and adoption, we wanna just make that as simple for customers to transact as possible. Second, you know, we're still keeping that cost plus model intact, adding that additional value but at a higher price point that we think captures that value, and then that also obviously leads to increased revenue for us. We think the value exchange is fair, but we have to capture that cost and it comes along with the value we're delivering. Yeah, over here. Hi, Yun Kim from Loop Capital Markets. The number one question that I get from investors after this past three quarters or so of you guys is that, you know, how should we expect seasonality next year given that, you know, obviously we saw the Q2 upside and, you know, many thought that maybe the pricing model saw an inflection point. We saw Q3 where, you know, the strong renewals quarter kind of masked the upside that we kind of saw in Q2. We saw, you know, what happened in Q4. You know, given how things played out last year and the lessons learned, should we expect, you know, similar seasonality, maybe not as profound this year? Or should we see more smoother seasonality this year versus last year? Yeah. Just curious on your thoughts. The first thing I'd say is make sure you're looking at the CRR versus the quarterly revenue growth when you're thinking about seasonality, because some of the ways we recognized revenue fluctuations in the, you know, in our model impacted that. The CRR is a better predictor of, you know, a better view of the historical growth and seasonal impacts. There are obviously mitigations in place based on what we learned last year, like the early renewals, like the value realization, like, you know, putting the consumption information front and center in the budget holder's eyes that we think will mitigate some of those seasonal variations that we saw. There's nothing that's gonna change the fact that there's Black Fridays and Cyber Mondays and this huge run-up to the holiday season that drives growth. There's a lull when everyone takes off seemingly on vacation and stops usually doing a lot of business at least online. That seasonal variation is likely to persist, but some of the knock-on effects and some of the seasonal variation, the contract cycles, we think we can mitigate. Thanks. Since Manav is here, you know, I'll ask him a go-to-market question. New Relic had a little bit of a different model than the other vendors out there, not just within the observability space, but just in software where you guys tried to introduce the free model and then, you know, have the user use that. In terms of getting or targeting certain more strategic customers, to Actually, try to use that free tier initially. Is there certain go-to-markets that you're using, certain marketing that, you know, that you either are going after to specifically target the strategic customers in the first place? Then, do you identify those customers and try to nurture them, you know, while they're in the free stage? Just if you can just talk about the whole process around that would be helpful. Thank you. Yeah, yeah, absolutely. I think there's a few things to mention here. First, you talked about the free tier. You know, most software companies out there, including all of our competitors, follow a trial model, where they start a ticking timer on their customers, saying, "You've got 14 days to use it or get out." Right? That model maybe makes sense for them, but it's not a customer-friendly model. Engineers don't like that pressure. They want to use the product when they wanna use it, how they wanna use it, and pay for it when it makes sense for them. We did that, perpetual free tier model, to solve for that. The added benefit from that is now we have a much longer tail of customers converting. One of the reasons you see an acceleration in the number of paid customers is we now have free tier customers from several months ago. Because they didn't have a ticking time bomb, they were taking their own time to see where New Relic made sense in the environment, they are now converting to paid. As time goes on, the free tier compounds the potential market of conversions over time, and we continue to get gains from that. That's one really important metric that most people don't understand is free tier versus trial model. That's why some of the best cloud companies have a free tier model, not a trial model. To your second question about strategic customers, large customers. You know, the way engineering tools work for most companies is that it starts with an engineer, it starts with an engineering team who wants to solve a problem. It could be like, Mark, you were talking about this in the NRR chart, right? The free tier is not small companies. The paid customer is not small companies. They are the first projects for companies small and large. Our free tier gives that engineer, that engineering team, a frictionless, efficient way of adopting New Relic in their environment and seeing if it makes sense and then growing from there. Now, obviously, our inside sales function that we added this year is becoming very good at identifying, you know, a person from a larger company, from a smaller company, which is why the deal size differences I mentioned to you, dynamics are playing out. They come in and help out sooner than later or especially answer questions that larger companies have before they become a paid customer. We're super excited about the approach we're taking here with the free tier and then also identifying more strategic customers. Sanjit Singh with Morgan Stanley. Thank you so much for the content, Bill. It's been super insightful and a lovely keynote as well, though. I had two questions. First, on the customer cohorts that were reducing their consumption towards the end of the contract cycle, one of the points of feedback that I'm hearing is, does this sort of raise any concerns about the mission criticality of the service? Like, are these supposed to be production systems? How, in fact, do you reduce consumption, you know, that quickly, on a dime? I guess the question is, how is that lower consumption manifested? Was that through the user side or was that through the data side? 'Cause I imagine the implications would be different, depending on how the customer went about it. Yeah. For the last question, we did the analysis ourselves, and it was almost 50/50, users and data. Yeah, some customers, more users, some of them more data. Across those that reduced, which again was isolated to the very hot cohort, the other cohorts were still, you know, growing, it was about 50/50. In terms of the mission criticality, I would, you know, let me use a different analogy, which is we've committed to be all in on public cloud. We're exiting our data centers in FY 2023. Our public cloud providers are mission-critical for us. Our business does not run without them. Our margins are not where they should be. We've told you we have to increase our margins to get back to the mid-70s in FY 2023, and we wanna get back to the high 70s, low 80s in FY 2024. The fact that we need to go drive efficiency there, despite it being mission-critical, is similar to the effect with customers and observability. They need to be efficient in how they use consumption-based observability. There's all kinds of ways to do that on the edges when there's budget pressure. For example, you know, cases where that might be true, Mark mentioned one of them. Maybe they provisioned users who've left the company, and they didn't deprovision the account. It's an obvious situation, happens all the time, especially in the age of the Great Resignation. They come up for renewal this quarter, they got three months, they're overconsuming. Oh, have we cleaned up all the accounts? Nope. Easy to deprovision, save money. Another one on the data side would be, hey, we ramped up a bunch of instrumentation on a project as it was being built and scaling and getting up to, you know, scale, and now it's kind of at a steady state. It's not being developed or enhanced significantly. It's kind of just running, maybe we can dial down the instrumentation and put that data, you know, next quarter on a new project where it's needed. So they can do things like that, which is totally fair. It's, like, the right thing to do from a customer perspective. Obviously, impacts our revenues in the short term. My second question to actually dovetail from your comments is the pricing matrix between users and data. Maybe one way to look at it, and correct me if I'm wrong, and certainly push back if I'm off here, but one potential implication of those higher prices on data is that maybe the initiatives on the user side is taking longer to bear fruit. As I sort of extend this out and think about the user dimension of your pricing strategy, it's always gonna be a point of friction, right? You're sort of asking customers to sort of, in some sense, ration users. I know there's limitations, there's guardrails on how often customers can toggle their users with the contract. Usage as a pricing dimension to maximize long-term growth, is that something that you think you would have to revisit over time, or do you think it's gonna be a foundational element of the monetization strategy? Believe it or not, we've debated that internally ad nauseam, because it is hard. It's also, again, we believe aligns with our strategy of aligning with customer value. The onus is on us to make that mission statement that I talked about true, which is every engineer, every day, at every stage of lifecycle. As long as that's not true, then customers are fair to ask, "Do I need to provision this user?" You know, "Am I getting value? Are they getting value, and I'm willing to pay?" That's why we continue to focus on that. From a product perspective, trying to make the product more useful across the software lifecycle, trying to make it more of a proactive practice versus just reactive, where you use it when you're on call, otherwise you don't touch it. Because that is where the value is, and that's what would help customers say, "Oh," like several of them so eloquently did today. If it's a 10% in productivity improvement, you're paying them $200,000, while you're actually saving money by giving them a full suite of New Relic. The other thing I would add is, uncertain, whatever you price on is gonna be the friction point, right? We came from a world where you were priced on what you monitored, 5% or a couple of years ago, was that 5% of applications were monitored. That's not because customers didn't care about the other 95%. They couldn't afford it, or they chose. They said it's an option. It's a nice to have on that other 95%. From a customer standpoint, as a customer, which would I rather decide on? What I'm getting visibility into? That's a really hard decision, and every time I roll something out, I struggle with it, right? Versus a metric that is more predictable around provisioning people. Yeah. It is more customer-friendly. I mean, the other thing that you made a mention from the keynote this morning from Bill's section is, with our pricing model, customers pay for users once across all platform capabilities. With our competitors, they don't call it that, but they bundle the price of a user in their, in their pricing model. Customers are waking up to it, right? They see it, and this model is more customer-friendly and creates more value. Question over there. Guys, let's Q&A now. What? Let's get one more, please. All right. Between us and the cocktail. Okay. No alcohol and then have cocktails served. As long as there are questions. One question. As you go to the second chapter of growth, you've migrated a lot of customers. Now, the idea is drive more usage. It seems, this may be oversimplifying, but it seems there's kind of two different growth approaches. There's the shift left with bringing durability into pre-production, where there's more of a greenfield opportunity, or there's this, let's address this swivel chair issue. You've got too many tools, and let's consolidate and unplug some of your legacy tools in the production environment. What if you look at those two different growth vectors, what's the easier path? What's the low-hanging fruit? For go-to-market, it's the swivel chair. Yep. For product, it's the shift left. That's right. You know, the good thing is, like, R&D is a long-leading investment. Product team is building out that capability set now, but it does take time to mature and find the right product-market fit. That's what then sets up chapter three, obviously, as well. But it's not like we do one or the other. We're doing both. They just kind of overlap and have different cycle times. Make sense? You're clear. You're welcome. Hey, thank you. Thanks. All right, guys. Cocktail hour. All right. Thanks all.