m3ter Revenue, Valuation & Funding (2024)

[00:00] Guys, Grip sold his last company to AWS and through that process that I've got a great idea which he launched in 2020. It's called meter, and it helps companies that are generally doing more than $50,000,000 of revenue, more accurately capture and and bill based off usage. You've got to capture the product usage data and bill against it resulting in billions of API calls per year. In some cases today meter is working with between call it ten [00:22] and one hundred customers. They've got 56 on the team with quote a majority being engineers and quote plenty of runway as Griff and his team looks to invest in the long term. Hey, folks. If we haven't met yet, my name is Nathan Latka. I launched and sold my first software company back in 2015 and went on to write a book about it, which you guys made a Wall Street Journal bestseller purchasing over 30 copies. Thank you [00:45] so much for that. After the book, I launched this show and one went on to create founderpath.com. I raised a large fund to do non dilutive deals with b to b software founders. So far, we've invested in over 400 software founders totaling a $150,000,000. Here in 2024, we're doing three to four new deals per week. So if you're looking for capital and don't wanna give up equity, go sign up at founderpath.com for free to get your [01:13] offer. Alright. Let's jump into the interview. Hey, folks. My guest today is Griff Perry. His him and his cofounder, John Griffin, started Meter after building and selling a back end as a service company for video games to AWS. The experience brought the challenges and opportunities of using usage based pricing into sharp focus, inspiring them to found Meter, an intelligent metering and pricing engine for SaaS companies. Griff, you ready to take us to the top? [01:38] >> Yes, absolutely. Where would you like me to start? [01:41] Well, it's great to have you. I will say there's a lot of people that think the future of SaaS is actually going to be pure usage based pricing. We saw Chargeify try and pivot into this. It didn't really work that well. They sold us as optics. We see sort of paddle and some others in The UK trying to capture this. Now Stripe is a big player. How do you fit into this ecosystem? [02:04] >> Taking two things you said in turn. I definitely don't think it's the case that everything is going to be usage based and everything is going to be sort of an extreme variation of usage based. But what creates the tailwind for our business is that there's been a rapid adoption of usage based pricing strategies often used in conjunction with more traditional subscription pricing. So it was probably a minority concern as recently ago as three or four years. [02:33] >> But now, like the majority of B2B software companies are using some kind of usage based pricing. Spectrum. So, know, you've got the AWSs and the Snowflakes in this world doing, you know, pretty pure usage based, but you've got a whole bunch of other players who are basically doing subscription 2.0. So it looks like a subscription, but it's got usage based elements. [02:55] >> It could be an allowance that you've got to track where you pay overages if you exceed that allowance, that kind of thing. [03:05] >> And moving to your second point, the reason that something like Meter exists is that the existing stack doesn't anticipate the usage based pricing components. And so what they don't do is rate product usage. When I say rate product usage, mean apply pricing to usage. So you've got to capture the product usage and then you've got to apply pricing to it to work out how much you would pay. And that's what Meta does. So Meta comes along [03:33] >> and we automate that bill calculation. And so for the most part, we integrate with those other logos that you're talking about, because we're doing the thing that they haven't anticipated. And for the most part, our customers are already committed to tooling in their quote to cash stack and we absolutely don't want them to rip it out. We just want it to work the way it needs to. Now they're using these slightly different pricing approaches and effectively [03:59] >> will help them modernize their quote to cash stack. [04:03] So I guess when I hear you say that in order for meter to work or for anyone to do metered pricing, they first have to capture the product usage data and then sort of bill against it. Those are two. I mean, Pendo only does product usage and they're a multibillion dollar company. There's others that only do the billing and they're multibillion dollar companies. You have to do both of them to sort of make this work. Give [04:22] me an example of a customer using you today and a version of sort of usage based or product tracking that they would do in their specific business that then they bill against. [04:35] >> SIFT is a good example. So if you know SIFT, they used to be called SIFT Sciences, they're a great business and they're doing fraud detection for online retail effectively. And the core metric [04:50] >> that they charge against is based around APIs. So they have naturally usage based pricing, but they have big customers and their big customers want quite a high degree of predictability. So a lot of their deals involve sort of minimum commitments, which includes certain allowances and sort of discounted rates above those allowances, that kind of thing. So that's a typical pattern that we would cater for. And need, a meter as a business, we need to integrate with [05:25] >> whatever their source of truth for product usage data is. And if it exists already, we'll take from there. If it doesn't, then nature itself can act as that source of truth. And we also need to integrate with their source of truth for account data and for pricing data. So again, we integrate wherever that currently sits. And what we're doing is pulling the product usage, the pricing and the account data together and processing it. And what you're [05:50] >> spitting out is bill amounts. And then we deliver those wherever they're needed across the stack. So they're needed once a month for billing, but they're also needed at any given moment so that customer success staff or sales staff know how much customers are using. The product team might want to build dashboards so that the end customer can see how much they're using and how it converts to spend at any given moment. The FP and A team [06:13] >> might want to export it to the BI stack so that they can analyze the business effectively. So that's the key thing. It's not just for billing, it's actually to power a whole bunch of functions all around the business. [06:24] That makes a lot of sense. So I guess today and we'll go back to your founding story here in a second. I just want the snap and shot today first and then we'll go get the story. But today, how many companies like SIF Science actively use meter to do their usage based billing? [06:39] >> Forgive me, we don't disclose those numbers, but we're a solid series of A business. We've got great customers like Sift or Onfido or Clickhouse who love our product has a transformative impact, and they're happy to tell their friends about it. [06:59] Can you give a I understand you have to say slightly vague, but can you put us at least in the right sort of world? Are we talking like five enterprise customers or like 5,000,000 low ARPU, high volume customers? [07:08] >> So, okay, so that provides, okay, for context, our focus is definitely on scale up and above. So what we're looking for is, or our customers are looking for is solutions to quite a high degree of complexity. So our customers are typically of the size of those examples I gave, SIFFs and the Alphidos of the What [07:27] metric was that you haven't attached a number to them? Is it number of employees? Is it revenue they're doing? Is it number of customers they're managing? Like what's the numerical value of the customer you're targeting? [07:35] >> So I would use the simplistically, I would say revenue. So it's $50,000,000 ARR and above. [07:41] Okay, got it. [07:42] >> What better way to think about it is it's really about maturity. So a company in their early stages only has a few customers and they maybe only have one product and they might only operate in one geo, but when they get more complicated, they have lots of customers and multiple products and operate multiple geos. And they will probably have an enterprise sales team that has quite a high appetite to do custom pricing deals to win and [08:08] >> retain key accounts. It's when customers get to that point that whatever solution that they had in place before to do what Meta does becomes overwhelmed. You know, they would have had a manual based spreadsheet system, or they would have built something themselves. And it's when they get overwhelmed that we come in. So we are at that, you know, our typical customer is $50,000,000 hour and above. And the stage of our businesses that we had tens of [08:35] >> customers like that and growing fast. [08:38] Thanks for that range. It puts us in at least in the right ballpark. So fair to say you guys serve between 10 and a 100 customers and you're focused on ones that are doing ideally north of 50,000,000 of revenue because it requires more complexity. [08:49] >> Absolutely. Very well put. [08:51] Let's go back to the backstory here. You were CEO of GameSparks. Did you guys build your own custom billing engine for, like, know, credit to get virtual swords in the games? I mean, how did you experience this problem directly yourself? [09:02] >> We actually gave people the ability to do that. So what Gamesfox was, I mean, I would call it cloud infrastructure, but given where you've come at this from, think about it as a back end of the box. So video games were changing quite rapidly. So previously, except for, you know, some relative niches, most games were something that you could put on a shiny disc or it's digital equivalent and sell. And that was it. Like, you know, [09:29] >> somebody, people kept score by the number of units they sold. And then video games went through a transition where typically video games would have a whole bunch of online features and they would be living products. And the way people kept score changed from the number of units you sold to the number of active players that you have. And there was a lot of, a lot of this was the growth of mobile as a platform. Anyway, so [09:54] >> there was a big appetite coming from the video games industry to build back end platforms so they could do things like leaderboards or achievement systems. And typically, video games companies didn't have those skills in house because it was new. And so that's what Gamesbox was. It was a highly flexible, highly configurable backend as a service. [10:13] You bootstrapped that and just sold it to AWS? [10:17] >> Yes, we did. So our background is, we had a background in an adjacent sector, so we did a lot of work in online TV and a lot of the intellectual capital that you developed there about how the technologies work was actually applicable to video games. I mean, if I did it all over again, wouldn't have built a service for an industry that I didn't know intimately myself. And hopefully we're avoiding that problem with Meta, but we [10:47] >> made it work and I really enjoyed it. And I love the video games industry. Yeah, it was a success. [10:54] That's great. Well, Griff, we've about four minutes left. I got a lot more we're gonna try and learn from you. Talk to me about other people's pricing. What about your own pricing? So you guys charge quote based off of platform based on the number of measurements you send and the number of API calls you make subject to minimum commitments and allowances for storage and data egress. So that might say like you can do a million API [11:11] calls per year for $10 and if you go above that it's X. [11:16] >> We're very like, you know, our customers is that we have to be usage based. I mean, we kind of have to eat our own dog food. And for that's what our customers want. But because we try, we sell into those more mature businesses, they want predictability, like I mentioned before. So our deals typically are underneath the hood, they're usage based. But the way they work is that our customers make a minimum commitment to us. And that [11:45] >> involves generous allowances of those usage vectors. And if they exceed them, they pay overages. But so [11:55] >> it's quasi fixed recurring, but with a usage based core. And you see that a lot. [12:00] I'm not a tech guy, so I don't know, you know, how many API calls a $50,000,000 AR company would be doing, but give me, teach us a little bit here. Would that be like a million API calls per year or a 100 or? [12:11] >> Oh, it's so variable. It just depends. And, you know, and it's, [12:19] >> there's a lot of, it can be the amount of usage data that they're ingesting. So it can be very high volume and high velocity. What the other way, you've to would be a high [12:30] API number? A million a year, 10,000,000 a year, a 100,000,000 a year? Oh, no, billions a year. Billions, billions of you have customers that are doing a billions of API calls through you per year. [12:40] >> But there's different vectors. So it's not just the amount that you're ingesting in. It's also the, how frequently you're calculating the bill. Because if you calculate the bill just once a month for billing purposes, you won't do many bill calculations, but if you calculate them every fifteen minutes so that there's an up to date how your bill is tracking available Just on a [13:02] to be real, I'm trying to get a sense of scale here. Do have customers that are doing billions of API calls per year on the platform. [13:08] >> Yeah. [13:09] Wow, that's incredible. I mean, that's incredible because of doing real time price, Every single usage thing, every single second, thing things go up or down. [13:17] >> But I I don't see that as a big number because of our Gamesbox experience. So, you know, we we would [13:22] doesn't have your experience. That's why I'm trying [13:23] >> to give you numbers to you. That also I'll use Gamesbox as an example. So we were doing about 40,000,000,000 API calls a month. And, you know, we were probably, you know, we were smaller and earlier stage than our ideal customer. So it just depends. I mean, if you're doing things in cloud infrastructure, they can be very high volumes. Different verticals, they can be [13:48] So lower what's the minimum you require? Like if someone's doing only a thousand API calls per month, they're not a good fit for you. What is sort the minimum that you would require someone to get value from your platform? Is that, you know, 50,000,000 API calls per month? You just said GameSpot or at that 40,000,000 per month is too small. [14:03] >> It's not, but I wouldn't say that the, I wouldn't think that way because [14:11] >> it's dependent, they could be trying to cope with a high degree of price complexity that might not have a huge amount to do with the volume of usage ingest. So, you know, it might be whatever, like a 10,000,000, a 100,000,000, it doesn't matter. But what the reason that they might be having real headaches is they've got a lot of customers and they've got a lot of skews and they've got a lot of complex bundling and they [14:33] >> need to do a lot of complex billing logic and they want to change prices. They want to do a lot of custom pricing. The sales team want to do a lot of custom pricing. So that's what creates a complexity for that business. Is that there's lots of vector, we like complexity. That's what we serve. [14:49] I'm trying to quantify. So you mentioned earlier, you have a minimum number of API costs per year that you require folks to get. Is that like a million API costs per year or 10,000,000 or a 100,000,000 or a billion? [14:59] >> I didn't say that because we don't, but [15:03] You don't charge me just, sorry, just back at minute eight fifty seven, we transcript real time. You said, quote, you have a minimum number of credits that they've had a purchase and then they go up or down from that. [15:15] >> So they would pay us a minimum amount, which would give them an allowance of x, but we don't require that they use a certain minimum level of that allowance. They can use money if they like. [15:28] Refunded if they don't use the full amount in the year? [15:31] >> No, because what we're delivering them what we're is a really sophisticated piece of kit that they would otherwise have to build themselves. And so that's why it is usage based because the better way to think about it is you pay, we wouldn't position it like this, but think about it as a platform fee. You're paying a platform fee, but then you can flex how much you pay above it depending on how heavily you're hammering that platform [15:59] >> or how much you're using it. [16:01] Mhmm. That makes good sense. As we wrap up here, you launched the biz did you launch this right after the sale of AWS or when did you launch the company? [16:09] >> We worked for three years at AWS. They have all the problems that we solve for just like GameSpark several problems we solve for. And then we we left AWS in 2020. It's been going for about three, three and a bit years. [16:22] Okay. So launched LaunchMeter in 2020. And you guys, I believe, have raised how much total have you guys raised? [16:29] >> 31,500,000 from external sources. [16:32] Okay, and you bootstrapped GameSpark so you know the difference between doing each, right? Why did you make the decision that meter was the thing you had to go raise a bunch of EC for? [16:44] >> Partly because we just wanted to do something different and sort of follow a different path for interest's sake, but also, I mean, we're building critical infrastructure for significant companies and that requires quite a lot in comparison, a lot of capital. So you know, minimum MVP to do this kind of stuff, which you know touches dollars, know, drives billing, is quite high. So it seemed like the natural path for us, but it was also, you know, the [17:15] >> novelty value, it was fun to do something different. [17:19] I mean, but this is very, this is very dilutive though, right? I mean, series A you're selling 10 to 15%, the average series A, you know, seed you're selling 15 to 20% even. So you guys are now diluted down to whatever you're diluted down to, right? So, but you've made the idea, you've decided that you needed and it was worth that dilution to go build something big. [17:36] >> That's the game. I mean, you're trying to build something very big and then the dilution still makes sense. So yeah. [17:44] Talking about the team really quick, how many are full time and how many are engineers? Again, backing up your statement that this requires a lot of engineering. [17:52] >> We're between fifty and sixty at the moment [17:57] >> and the engine so we're still mostly engineers. The reason I'm slightly pausing is some of our engineers are actually focused on implementation because these are quite big transformations that our customers are going through and we provide a lot of value by helping them through it. But yeah, we're a company maturity engineer company. [18:18] So, okay, so if I say how many engineers on the team you would you'd say 50? [18:25] >> I don't have the number on the tip of my tongue, but it's the majority of the of the company is engineering. That's what we do. [18:38] Okay. I mean, the reason I ask is you can't just have a great product if if no one knows about it, no one's gonna buy it. Right? So you're saying there's no sales team, there's no AEs, no SDRs, no [18:47] >> No. No. We I mean, yes. We we have go to market capability for sure. But [18:58] >> with the nature of our company is that you have to be quite heavy in terms of your product because you're building a lot of it. [19:04] Oh, I understand that. I'm gonna Quantify it, That would make sense if you said, hey, we have 40 engineers and 10 sales reps, right, or go to market folks. But when you say majority engineers, don't I just don't know what you mean by that. [19:14] >> More than [19:15] 25 engineers would be the technical definition, I guess. [19:18] >> I'm dissembling because I don't know the exact number. [19:20] That's okay. That's okay. That's okay. Who's doing are you coding or are you doing selling in terms of how you and John split roles? [19:29] >> John is doing everything. John is the CRO, so he manages the go to market teams, which includes the pre sales engineers. [19:43] >> The way we work together is that I'm a strategist and a company builder. So I'm I'm about creating the infrastructure of the company. And he's focused on code [19:55] on the founding team then? [19:57] >> Pardon me? [19:58] There is no one that writes code on the founding team. You you nor John write code. [20:02] >> So if the founding team is John and me, that's correct. Although John is a data scientist. But [20:11] >> this is a founding group that came from our previous company involving strong engineering that came with us through GameSpark and AWS. [20:19] Oh, so you have other founders? [20:21] >> Well, it depends exactly. Consider them to be part of the founding theme. I don't know exactly what language you want to use. But yes, so you're a You tight [20:34] guys put out when you raise capital and it says founders, Griffin, Perry, John Griffin. I'm just using publicly traded sources. [20:41] >> Okay, to answer your question, there are two founders, both called Griffin. Neither of us code or you wouldn't want us to be, but we built a team of people we'd worked closely with in the past and very high quality engineering was involved from inception with the company. [21:04] That makes sense. I guess as we wrap up and you think about your pricing model over time, if someone's like, let's say I want to sign up right now to Meter and I'm more than 50,000,000 of AR, I'm going to pay for I'm going to make this up 100,000,000 API calls per year. Are you saying, okay, Nathan, the platform fee is a $100 and then it's a point o o 1¢ per API call or, like, how [21:24] would that be structured? [21:26] >> Again, forgive me if I don't disclose that because that's sort of commercially sensitive information. But, you know, we again, to give you a sort of some direction, like we have quite, we have a sales led motion. And that means that we need to earn a significant amount from our customers for the unit economics of our business to work and they do. So yes, the amounts of customers pay us are reasonably high. And that is nicely consistent [21:54] >> with the amount of value we deliver to them because it's transformative for them. [21:59] How do we end with a macroeconomic with 56 full time employees and assuming that you follow the average of the average revenue per employee per for a VC backed company be about $110,000 that we could back into maybe a revenue guess of about $6,000,000 with what you've raised $35,000,000, assuming that was raised at a multiple in the 2020s or 2021, right? It's fair to say maybe you raised at north of 100,000,000 valuations today. Things have really [22:24] compressed. How do you make sure that you take whatever revenue you're at today and you grow into evaluation that can support the last you raised out without getting options underwater? [22:35] >> So I'm not going to comment on valuations or revenue, but I can say that we've got, we've been very fortunate and that we've got a lot of runway and that provides us with a lot of flexibility. [22:50] >> I mean, in terms of the potentially dilutive impact, I still think that we were incredibly fortunate to found the company when we did, because those favorable fundraising conditions allowed us to raise a lot of funding and that was needed because we were building critical infrastructure, like I said. And now I'm focused on the long term. Like we were trying to build a really big company. I don't worry too much that the conditions have changed. It's just [23:16] >> is what it is. And you just continue to make progress. So let's see what the market conditions are like, if and when we raise again. And they'll be different from they are today and certainly different from last year. [23:29] Okay, so just to be clear, you're not feeling any sense or need to manage around a valuation issue where you raised at a 40x multiple two years ago or a year ago when you raised your series A versus sort of where the market's trading at today, you don't feel that's not you don't feel that pressure at all? [23:47] >> I can imagine scenarios where it's easier, and I can imagine scenarios where it's more difficult, but I'm not leaving losing sleep over it. Like, what I'm focusing on is building the business effectively. [24:01] >> I wanna build a great business. [24:04] In 2024, where are you to to your point on a lot of runway, which is great. Where are you spending? I mean, as a capital allocator, as the founder, you do a lot of this. Where are you investing capital this year to try and create something better long [24:15] >> term? So, I mean, like our focus generally is that we're in that tinkering phase. What I [24:25] Tinkering mean by that is phase, you've raised $35,000,000 like you have to have real revenue. You're not in a tinkering phase. [24:32] >> Well, it depends what you see yourself as tinkering. Like, what we're doing, you're building a machine. Like, you build a product. Now you need to build the company. You need to be able to scale it effectively. So when I mean tinkering, it's like, how do we grow faster? How do we improve our unit economics? How do we improve all our metrics? It's that tinkering. It's like, you know, we're at a stage where really [24:54] >> you want to be a business architect and a technician. You're sort of fiddling with all the knobs to make the machine run smoothly. [25:05] >> Sorry, I forgot your question. Move just from my mic. [25:07] We're out of time. So we'll wrap up with the famous facts. These are rapid fire one word answers. Number one, is there a CEO you're following or studying? [25:14] >> No. [25:15] Number two, is there a book that's really had an impact on you? [25:19] >> Many, but I'll call out one, Escaping the Build Trap by Melissa Perry. [25:25] Escaping the Build Trap. Great. Number three, is there a favorite tool that you use to build meter? [25:30] >> I feel like I have to say AWS. [25:33] Fair, fair, fair. And number four, how many hours sleep do you eat every night? [25:39] >> Seven to eight, more than Pretty I used [25:41] good. And with situation, married single kiddos? [25:45] >> I'm married with three children, the oldest of which turned 18 yesterday. [25:48] Great, you're a busy guy then, four startups. How old are you as we wrap up here, Chris? [25:53] >> How old am I? Yep. 51. [25:57] 51 years young. Last question, something you wish you knew back when you were 20? [26:02] >> Well, I mean, feels quite close to home given my oldest became an adult yesterday. I would say go easy on yourself. Like, if you don't know what you wanted to do or who you want to be at 20, that's completely normal. Just take your time. [26:17] >> So that's the good news. The bad news is if you wanna achieve stuff, grit and resilience matters an awful lot. Unfortunately, you have to accept that. [26:25] Guys, Grip sold his last company to AWS, and through that process said, I've got a great idea, which he launched in 2020. It's called METER, and it helps companies that are generally doing more than $50,000,000 of revenue more accurately capture and bill based off usage. You've got to capture the product usage data and bill against it resulting in billions of API calls per year. In some cases. Today, Meter is working with between, call it, ten and [26:48] one hundred customers. They have about 56 on the team with, quote, a majority being engineers and, quote, plenty of runway as Griff and his team looks to invest in the long term. Griff, thanks for taking us to the top. [26:59] >> My pleasure. Lovely to meet you.