Guy Rubin - 2026 GTM Benchmarks

Speaker A: Foreign.

Speaker B: Welcome to Cloud Radio Made for Full Stack cloud operators. Cloud Radio covers all aspects of the business of software. So I am pleased to have Guy Rubin from Fullcast also was the founder and CEO of ebsta. He is our first three time guest and a lot of our initial connection. Our continued connection has come from their excellent 2026 State of GTM benchmarks that they do in parallel with Pavilion. This year's edition covered over 75 billion in pipeline. Just an impressive number of deals and sellers. They're in using their own platform which is very AI enabled and connected into CRM. So very unique level of insights. Much more granular in terms of funnel adoption metrics and then a lot of these self reported benchmarks might be. We've been covering this report for years. We've also uh, been very impressed with Guy's product line that he leads at full Fullcast called Revenue Insights as a service works with private equity firms. Given my background as an investor as a board member, when Guy first showed me Revenue Insights and the impact it can have, the granularity, the fit for private equity growth, equity portfolio companies, I was blown away and we've hosted them at some of our value creation summits. And so that's a very very long intro for Guy who is here in San Diego to do a deep dive on the report. And uh, GTM in general.

Speaker A: It's great to be here in person. It's the first time we've done this one these sessions in person. So I appreciate you hosting me here today.

Speaker B: Awesome. Well I think the first focus area will be on the GTM report and again 75 billion in pipeline as has been the custom actually the last number of years has been real challenges on the sales efficiency side. Like the headline figure this year was negative 28%. Want to cover a bit of that. Like what drove that negative 28% in sales efficiency kind of more granularly and then some thematic things uh, out of that.

Speaker A: Yeah. So to set the scene, the Data originated from 316 B2B software and service businesses. There's a breakdown in the report as to how big those businesses are and the businesses and the size of companies that they're servicing. But I uh, spent a decade building an engine that was able to connect to multiple data sources around organizations to really truly understand what's driving what their top performers are doing differently to the rest of their sales team. And so this report is really the output of that. It's a kind of culmination of all of those individual businesses. What we call insight reports that roll up into what we call our benchmarks. And so yeah, it seems to have been really well received and some of the data within it to me is really, really shocking to see that even in today's market things are still, there's still such a delta between what our top performers are doing and everybody else in our sales organization.

Speaker B: Yeah, and that's one thing that we've covered from the reports. And since they go back in time that call it three or four years ago, the gap might have been 4x between the top performer and the median one. And then in the most recent times it's gotten into the 10 11x range.

Speaker A: Yeah, we're now over 10x different delta between our top performers and the rest of our sales team. And we know that we need to move away from these kind of hero sellers into a place where our systems are able to bring everybody up. And in the best organizations we are starting to see that delta drop. But there's still this drive for uh, what we used to call growth at all cost has now become this AI brute force engine where people we saw in a single year the number of top of funnel opportunities created increased by 68% in a year. And in those organizations while they were closing more deals, when it came to revenue per seller, we saw the revenue per seller actually drop by 25%. And so that tells us a lot about what we're seeing in the market. And organizations that are going the other way will where they're using AI to introduce rigor and process and consistency, they're moving up market, they're spending much more time and energy on icp, they're qualifying out much quicker. And in those organizations we saw revenue perceptor increase by 61%. So it's not about more doesn't necessarily equal more. And what we need to do is focus on what's going to help us win more and really understand what best practice looks like. Especially in a world where AI can generate infinite number of leads.

Speaker B: Yeah, that's been fascinating to see. And again like an advantage of your coverage is around things like pipeline ICP fit and that even in the prior years people holding onto what we've called like fake deals. And it seems like I guess if you increase volume, you're also increasing the number of fake deals for people to hold on to. Is that how you'd characterize it?

Speaker A: Yeah. But also if our go to market engines are broken to start with, if we don't know how to identify ICP opportunities, if we're not very good at qualifying out, you just end up with more and more volume. And so as you mentioned earlier, so I sold Edster to Forecast last August and Forecast are experts at a number of things and one of them is territory planning. And so I started spending. I'm a data geek so I like to look at the data and I would spend a lot of time looking at how territories are balanced and what the impacts, planning imbalance territories are. And what we see is when they've got too much volume to focus on, they don't go as deep with the customer, they aren't as multi threaded, they're not building strong enough relationships and they're not going deep enough into qualification and discovery and the impact of that is compounding. And so we're spinning wheels. We're spending a lot of time and energy on deals that aren't real or that could be real if we went deep enough, but we just don't have the time because the GTM engine is broken. It's kind of counterintuitive for the sales leaders and the sellers because it's not about focusing on more. But actually when we understand that the deals that are winning for us are the ones that look like X, then what we're able to. You can still use nr, lots of leads as long as the GTM engine behind it isn't broken, as long as it knows how to qualify out the stuff that's never going to close before the sellers get involved. And then when the sellers get involved they're expected to qualify out more. So it was interesting. I would get to spend two or three times a week I sit in front of leadership teams and I deliver them these revenue insights and most of these are P back businesses. And what we see time and again is that let's say you're running seven territories. The territory that qualifies out the most is almost always the territory that generates the most revenue for sale. And that's slightly counterintuitive for the guys on the ground because they don't want to have, you know, they want enough coverage and they want more, particularly in their numbers. But in fact all that happens is if you skip through those early stages without doing the work and having that ruthless approach to qualifying out, you end up with all this pain rate stage where things are delayed and you've brought in solution engineers and finance and legal and actually the deals never close. While if you qualify out three course of your deals before they get into an active process or at the early stages, then the magic starts to happen. They skip through the later stages really quickly and you get almost 100% of the deals go one to close one.

Speaker B: And can you elaborate a little bit more on the territory? I know Fullcast has that capability. And then there were some real insights beyond what you just said in terms of routing towards expertise, skipping round robin, which might just very well be a legacy tool that in 2026 with all of this enablement, full cast style technology, you should just be skipping. So maybe a little bit more on territories.

Speaker A: Yeah, so one of the things we spend a lot of time doing is analyzing which deals are certain sellers very good at selling to. And so in the old world, people would break down territories by geographies. And it's very rare that a particular seller is good at selling because somebody happens to be in San Diego. Right. The chances are they're really good at selling to a particular vertical or a particular size of business. And so it's amazing how many businesses are still running round robbit on their lead distribution. So first of all, the businesses that do well are uh, allowing AI to do some of the qualifying out early stage. And then they are getting a lot more granular in how they're routing the right leads to the sellers that have the best chance of closing those types of deals. And again, the good news is the data already exists. It's already within your organization. We just need to unlock it and we can go back through the historical data and understand which sellers are good at selling to which particular emotions. And you now can break territories up in all sorts of interesting way. And it has a big impact on outcomes. On the downside, if your territory isn't balanced and more often than not it's not under resource, you've got too many deals for each territory. We saw win rates drop by 57% so we want to get a lot more grandeur at that kind of thing. And the final thing I'd say is that in the same way we're still seeing people distributing their leads on a round rocket basis when it comes to forecasting, spending a lot of time, they're still forecasting based on stage. Right. And there's wildly different outcomes based on which Personas you're engaging with, uh, how well we've qualified the customer, do we really understand the critical event? Where are we at with budgets? How many days are we spending in stage? And these things have wildly different impacts on outcomes. And so if you're still forecasting based on stage, you're never going to get to an accurate number. But the good news is all of these other data points with AI now with, we can plug into data from sources like mailboxes and calendars and call recording transcripts and CRM and we can look at what good looks like and get very granular about right. When a deal looks like X, then the chance of it closing is Y and you can roll that up into a forecast that means, you know, by week two or week four of a quarter you're at 95 plus percent accuracy of what number you're going to hit at the end of the quarter.

Speaker B: I want to call something out there because like when you think of like all of these things you're covering and able to see, like, just for, for folks who might not be familiar with EBSTA now Fullcast, like mechanically, technically, how you, what do you do you plug into the CRM, the call recordings? I just want to call that out so people can understand kind of.

Speaker A: Yeah. I mean, so when we started we were just a software company like everybody else and we spent, we spent three years building an engine that could make it very easy to connect to things like all these different data sources around business and make sense of the data. Uh, so trolling through all the historical mail traffic, not just of the sellers, but of the solution engineers, the finance department, the customer success teams, we were able to codify what a relationship looked like and score every relationship out of 100. And on average we're finding 62% of companies active relationships with customers and prospects never make it to the CRM. So if you're trying to do reporting without access to this data source, it's a real challenge. So we built this engine that was very, was with an hour's work you could connect everything up to the platform and it would deliver our software. What we've done more recently is develop this, what we call revenue insights as a service, which is a static report we deliver back to the leadership team every quarter, but it still benefits from the engine that we built for the software. So it still only takes an hour to connect to our platform and we deliver this kind of picture based audit. It's 50 pages long, very easy to digest, one takeaway per picture. But what it does is as an independent, I get to sit with the leadership teams of these businesses and show them how they're pacing and what they should prioritize to drive growth. And what's amazing is when you turn these things into pictures and when the data that underpins it is beyond reproach because it's come from source, you're able to give Everyone confidence that this stuff makes sense and all of a sudden everyone starts to align. And the impact on revenue per seller, uh, and sales efficiency within a couple of quarters is dramatic. And a lot of that's why we've seen E houses like HG Capital sign up for global arrangements. Now for us to deliver these reports independently of the software, just the reports across the portfolio of companies. Then you can imagine for the leadership team at hg, they can walk into every pool code and they get a consistent view of what's actually going on and go to market and what do we need to prioritize to drive things forward. So yeah, it seems to have been really well received. And yeah, it turns out that engine that we spent all those years building, we found another reason, another way to repurpose it.

Speaker B: Yeah, it's fascinating. And like my perspective on, uh, it when you first showed it to me. And then some learnings we have here from cloud ratings where we really do use data at scale. It's mind blowing once you see the difference between kind of like the old human way, like our equivalence of channel checks versus scale data. Right. And I've always thought about that from the sales side, the human equivalent of pipeline reviews or so many of these things that inherently you only have so much time. There's only so many call recordings you can listen to. There's only so much time in the sales review meetings. And that, uh, fundamentally you just cannot compete. Right. With scaled data.

Speaker A: Yeah. And the rev ops teams know a lot of the insights that we deliver in these reports kind of intrinsically, but their ability to prove the point in simple, easy to understand graphics that the leadership team can digest and then align to is a real challenge. And so that combination of the simple to read outputs, the speed in which we can just connect everything up within an hour. And that kind of independent auditor, uh, kind of coming in once a quarter and going, right, guys, this is what I'm seeing. And, and ultimately we're not trend agents. Right. We can recommend people that we know or people's internal rev ops teams can actually on this stuff, but we almost don't have a dog in the fight. Right. We're just there to deliver the audit and it lands really well and suddenly aligns the teams in a way we've never seen people do before. Awesome.

Speaker B: And I know one of the insights in the report I found interesting is you kind of have to, at a certain point start looking at what doesn't work. And you've long covered performance by channel relative to the average and you know, BDR source pipeline was at 0.2x, right? So like 80% worse than average. And when I see that, and I also look at like the emails I get in my own inbox that are like AI or outbound and you just are like, you know, this can't be a good use of time, whether it's a human or an AI to generate this. And then when you see that effectiveness. And so like are we entering in an age where like BDR SDR work is just not advisable?

Speaker A: So it's really interesting. I spent a long time looking at attribution and there are certain things that always seem to scale really well. So partnership communities, partnerships are becoming more and more self efficient. So the dollars per day that they generate from the leads coming from those seems to be getting better. Okay, so people are leaning into recommendations from their community, from their partnership, promotion from existing customers. So if you're not already asking your customers for introductions, you absolutely should do. Those leads will give you a much better and a faster close at a higher win rate. But on the other side of the scale, the kind of generic events when you're handing out pamphlets and leaflets, the conversion rates on those deals, they're really low and it's very expensive. And the same with the BDRs that are responsible just for booking meetings. The biggest concern there isn't necessarily the fact that the win rates are so low or it's an inefficient motion. The concern is the volume they're generating and that volume is going into the pipe for these sellers to try and close and it's just polluting the sales cycle. And when you've got single digit win rates on the deals that are coming from those sources, it's a massive distraction. And the volume that they're generating is causing real pain. Now what we've seen as I start delivering these reports back to kind of mid market software and service businesses, what's been really interesting is what they've tried to do about it. So rather than just getting rid of the BDR team, what's been interesting is one of the channels that's actually getting more efficient is the AE outbound. Okay, so self sourcing their own opportunities because they know that deals that look like X are the customers that they can really help. And so we've seen a move to bring the BDRs into almost a pod with the AES and change their incentive structure so they're focused much more on outcomes rather than just booking meetings. And when we see that Happen, that the AES are able to actually work closer with the BDRs and much more focus on help manager educators to what that looks like. And again, rather than focusing the VDRs on volume, we're focusing them on quality. And that introduces rigor and process that works. And so not everybody's just getting rid of their BDR team. Some of them are finding really creative ways of incentivizing them on the right outcomes and aligning them to the AES that understand what grid looks like. And all of a, um, sudden the efficiency starts to rise again from those resources.

Speaker B: And then maybe a hard question when so many of these reports, not just yours, always show know, channel productivity, like the, the power of channel, the, the relative sales efficiency, is it scalable? Like is. Are you naturally at a ceiling though? Like can you grow that? I just look at that and I, I keep wondering, well, why aren't people doing even more channel? And maybe there's some reason that I'm missing from afar.

Speaker A: The, the challenge with channel is it's a flywheel. It takes a lot of energy to get that flywheel moving to starwind. I remember when we started, it took us 18 months to get our first deal through channel. Now we get a third round deal through them. Right. But you have to stick with it. And um, part of that is about maybe changing the commercial models around it, um, because you have to align to what the channel are looking for. And it's not easy because all you're there is, I just want to sell more of my product. Well, that may be true, but your channel's not interested in your thing. Right? What they're interested in doing is helping them do their thing. And so sometimes you need to evolve and improve the channel around this. And again, uh, ultimately we're a software company, but we've been able to use this revenue insights approach through Channel to build out a relationship with all of these individual companies and deliver value before. So kind of giving before we get. Sometimes it's very difficult to do the thinking and it really needs strategic heads on it. This isn't a junior role, especially if you're turning a zero into a one and you're just trying to create that channel in the first place. But the other thing I'd say is that there is. While marketing events like having your boot and hanging out swag, it doesn't really seem to. Again, the efficiency of those are very low. On the other extreme, creating spaces where you get to spend time with your target audience, perhaps with your prospects, your partners and your customers. In the room and you almost kind of get the opportunity just to keep quiet and watch the magic happen in those environments. It's amazing what happens. And again, the conversion rates are incredibly high. When they've had an opportunity to have a dinner or a breakfast or a roundtable discussion with people that are having the same challenges as them and they solve those problems with your thing, but you're not the one selling it. There's definitely a role there. But isn't it funny how in an AI world we're back to basics? It still turns out that relationships drive revenue. And it looks like we've still got to do the core things that we always needed to do. And if anything, the AI is there to help us do more of that. So taking away all the admin that really we shouldn't be focused on anyway.

Speaker B: Fascinating. And then another like long running theme of these reports that's always been shocking and even a lot of CMOs reach out to me once this was covered was how little of the pipeline is true ICP. I know in prior years it was about 15%. This year in the report there's some good coverage. Around 75% plus is like effectively very, very, very inefficient from an ICP perspective. So do you want to elaborate a little bit more on those findings, your learnings there?

Speaker A: Again, it comes down to this AI approach to generating infinite leads. So first of all we found that we also did, as part of the report, we surveyed 250 CROs. And what was really interesting is looking at the two thirds of CROs have got very little confidence in their ICP definition. And ICP should be a living, breathing document. Right? It's something that we can learn from every day. And what's really interesting is all sorts of things can influence icp. It's not just what industry they're in or the size of the business, what's going on their board, have they just got uh, a new C suite? Have they got activist investors at the board? Are they about to sell the company? Have they just done a raise? All of these things can influence whether a business falls into or out of icp, depending on what you're doing. And so the more signals we can get as to what took place in the past will help us to define and evolve what ICP looks like. And it's such a powerful tool if you can get it right. Again, the challenge is that, uh, we're spending so much time on all this volume, that kind of growth or cost model that we saw in the past. Has become this AI kind of brute force model. And it doesn't serve us, but it feels good because we're getting lots of leads in. So yeah, spending time and energy on ICP definition is really powerful. But you're absolutely right when we see, and one of the interesting things we do is we look at purely from a quantity perspective. So we're not interviewing people and asking how they feel. We're just looking at, okay, when we sell to a company that's B2B versus B2C, what's our efficiency number? What's the dollars per day we generate from those deals? Or when we sell to a small business rather than a larger one, or if our customers are selling to enterprise versus SMB, what impact does that have? Or what industry is giving us the most efficient outcomes. And when we do that work, what's interesting is go back through the pipeline on the first day of each quarter and see what proportion of the pipeline, uh, matched for a very high icp. And we see time and again that if it's sitting at about a third, you're in good shape. Right? And as soon as it drops below that, we see ACV drop, we see time to close increase and we see when rates go down. And so, but it's hidden in the data. So again, it's another example of when you bring all this information together, something becomes really clear and easy to understand and then it's obvious what we need to do next.

Speaker B: That's fascinating. And like M for me, my call out there is, you know, because you wonder, well, these people are not like idiots, right? These are sophisticated companies. But if you use like a very classic ICP right around revenue of the target employee count, that probably explains how this happens, right? Definitionally, a lot of this pipeline does fit that employee count or that revenue count. But then when you get into the, the more dynamic and nuanced definitions around changes in C suite changes at the board level, right. That starts to explain how you can create a much more efficient targeted approach. So it was a big learning for me.

Speaker A: Yeah, there's so many signals that can help us understand why we win. And uh, we need to learn every time. And it's incredible to see though. And again, once you start, it's like turning a television from black and white to color. Once you've got visibility of this stuff, suddenly, uh, it becomes a superpower. And we can have really good conversations with the sellers about why these types of businesses were never going to generate, we're never even going to sell them, or if we do sell to them, they're not going to expand the way we want them to. So again, our most expensive resources are our sellers, and we need to get them focused on the things that are most important. AI is a great tool to help enable them to spend more time on the customer, with the customer, but that's the lens we should be looking through. If we introduce this thing, is it going to increase the number of hours my sellers spend in front of customers, or is it going to reduce the amount of time because they're busy behind a keyboard pushing up? And as leaders, it's our job to give them that roadmap, to give them that playbook. And I think we failed as leaders for most of our sellers because we've given that, we've kind of assumed that sales is this kind of black art that, well, we can't quantify and, you know, we just need to lead them to it. When that's not the case, we need to take a lot more control. We need to help our sellers to be more productive and to achieve their outcomes by being a lot more prescriptive about what they should be doing and where they're spending their time. And when we see them do that, when we give them the data to explain that something the sellers wanted too, because ultimately they just want to earn more money. And when you show them, look, if you work with me on this, we can increase your revenue per seller, uh, by 2.3x. In any other industry or any other department. You show them a 3% increase of productivity, they'll bite your hand off. In sales, we're talking about hundreds of percent of productivity. And, um, we still have to convince them. So we found this kind of simple approach, turning into pictures and making sure that the data that underpins it is beyond reproach, Suddenly everyone's on board because ultimately they can see a route now to earning more money.

Speaker B: And we will include some of these revenue insights as a service examples because they are powerful. You can see why leadership, uh, at the AE level is very credible. It's very digestible, but it's also thorough. These are thorough reports. You can see why the private equity folks like them.

Speaker A: Absolutely. Yeah.

Speaker B: So we will include that. We'll include the report, which very much speaks for itself. Like we've been elaborating a lot on. And are there any other takeaways you want to communicate to the audience beyond my kind of pedantic questions?

Speaker A: There's so much in there. Welcome the feedback. And if anyone wants to have a chat about the data that's my thing. Um, what else can I say? We've seen a big positive impact on Ramp, where businesses are using AI to take away the admin burden and the research for their customers. So we're seeing new sellers coming in, are able to actually learn on the job rather than away from the role because the AI is doing some of the heavy lifting. So using AI enablement and RAMP has been a real win. So that's something I'd encourage people to look at in more detail. And we talked about territories. Get those balanced, those territories balanced. And you don't need to stick it to kind of geographies anymore. We can really get Grinder about making sure the right sellers are accessing the right opportunities. So, yeah, there's a lot of takeaways in the report and I welcome people's feedback on it. And we'll include the link maybe in the.

Speaker B: Oh, for sure. We always get the links. We'll have this on, um, the newsletter. And look, there's, uh, a reason we first connected. I've always been blown away by these reports. I've also. It's been good to get to know Guy, his business, his team really like the revenue insights as a service. I've just been a fan since he, he demoed to me last year. It's been interesting to watch it grow too. Uh, I know at the time you were working with HG and I keep hearing about like the other investment firms you're working with. So it's been, uh, exciting to root from the sidelines.

Speaker A: I appreciate that. Uh, yeah, it's been great. And what's been amazing is working with these PE houses to actually evolve this solution in a way that's going to make it easy for their port codes. And as I say, the fact it only takes an hour to connect everything up and the output is. So it's getting more and more powerful every quarter now. And I really enjoy the opportunity to spend time with these leadership teams and really help them understand what they need. The tool tweaks that can be made that can have a big impact. And what I'd say, the final thing I'd say is that the numbers that led to this compounding negative effect on sales efficiency. So we saw sales efficiency drop by 20% last year, and a lot of that was down to this kind of high volume of inappropriate leads coming through. But all of the things that led to the compounding negative effect, it doesn't take much before the compounding positive effects start to happen as well. Where we start to see a small Increase in acv, a small reduction in time to close, a small increase in win rates and all of a sudden they start to compound and you can start to see big impact, um, on revenue for seller, uh, and sales efficiency quarter after quarter after quarter. So yeah, don't lose hope. This stuff is great when you get it right and you're not that far off and you've already got access to all the data, we just need to bring it into the right place.

Speaker B: Yeah. That's again the scale data and then the fact that all of it exists. Right. You can connect to your CRM, you can connect your call recordings, uh, apparently in an hour and it's there. This isn't some heroic effort, it's repeatable as well. Right. You can get revops to go study something around ICP, but very often in the real world that's a one off report that you might regenerate 18 months from now. Right. Have burned a lot of spreadsheet time, a lot of human capital on here. You can do it scalably, repeatably.

Speaker A: Yeah. And look, the core recordings and the CRM people have got access to already. We see people playing around the core on these things. That's great. The piece of the puzzle that we fixed that's very difficult to just automate is the connections from our server. Uh, turning the traffic that we've got going through our organization into a people graph of all the relationships and who's been engaging with who during each stage of the sales cycle helps us understand how important different Personas are to the chances of winning and the chances of retaining and expanding accounts as well. So the reports that we do for our customers do just as much on the, on the right hand side of the bow tower as they do on the left. And again, it's amazing to see that when you maintain engagement with the C suite from 2/4 prior to the renewal, the win rates or the chances of opening up cross sell, upsell opportunity with a 45% win rate are uh, seven times higher. But if you don't maintain engagement with the C suite, your chances churn are four times higher. So there's all of the data's in the systems, we just need to unlock it and then you can see it in a way that's easy to digest.

Speaker B: Beautiful. Look as always, I can't believe this is our third cast. We'll probably be doing these for years at a time and look forward to sharing all this with everyone. And again, thank you guy, and thank you for making it to San Diego for this.

Speaker A: I'm um, great. Did it in person. And we need to make sure we do it every year.

Speaker B: Yeah, we're. We're a good location for host, so any future guests you know, please come to San Diego. So thank you, everyone, and appreciate you listening.

Speaker A: Thanks, everyone.