He's Seen 300+ Sales Comp Plans. 90% Make the Same Mistake | Siva Rajamani (Everstage CEO)

Most sales comp plans are quietly broken, and the people running them have no idea. Siva Rajamani, CEO of Everstage, has visibility into 300+ enterprise comp plans, and he says 90% of companies make the same mistakes. In this episode he breaks down what's going wrong, how to spot it, and what a comp plan that actually drives revenue looks like.

Siva explains why sales compensation is not a back office cost center but the single biggest lever in your go-to-market strategy. It's the glue between what a company intends and what reps actually do. If your reps aren't doing what you want, the answer isn't in a 1-on-1. It's in your comp plan.

We get into the over-complication trap, the hidden math that makes reps refuse your best deals, the base-to-variable ratios that actually work, why your top reps should out-earn almost everyone, and how AI is about to blow open the gap between your best and average sellers.

Chapters:
00:00 Intro
00:30 Siva's RevOps background at Freshworks
04:00 Scaling RevOps from 1 to 25
04:50 Why he left to build Everstage
06:30 Why incentives drive revenue, not tools
08:00 Comp as the glue between intent and action
10:30 The 1 to 2 mistakes almost every team makes
12:00 "If your comp plan needs FAQs, it's a tax code"
14:00 The 60-second test for a broken plan
15:30 Designing comp to retain top talent
16:50 How AI widens the gap between top and average reps
18:00 The $1M sales rep is coming
19:30 Why optimizing for top earners is better on margins
21:30 Quota to OTE ratios that actually work
23:00 Base vs variable: the 50/50 rule and exceptions
24:00 What Everstage does and who it serves
25:30 How Everstage structures its own comp plan
28:00 The rise of the revenue architect
48:00 CPQ and connecting margin to commissions
50:30 When should reps earn commission in the deal cycle
52:30 Six month vs twelve month comp cycles
54:30 The most a sales rep has ever made
55:20 Where to find Siva

Connect with Siva Rajamani: 
Co-founder, CEO of Everstage
Twitter/X: https://x.com/siva_rajamani
LinkedIn: https://www.linkedin.com/in/sivasrajamani/

Host: Sophie Buonassisi, SVP at GTMnow
Follow Sophie: https://x.com/sophiebuona
LinkedIn: https://www.linkedin.com/in/sophiebuonassisi/

ABOUT GTMnow

GTMnow is the media arm of GTMfund, sharing the strategies, tactics, and stories from the operators and investors building the next generation of go-to-market.

Visit us on: https://gtmnow.com
Follow us on LinkedIn: https://www.linkedin.com/company/gtmnow
Follow us on X (Twitter): https://x.com/GTMnow_
Follow us on YouTube: https://www.youtube.com/@GTM_now
Follow us on TikTok: https://www.tiktok.com/@gtmnow_
Follow us on Instagram: https://www.instagram.com/gtmnow_/

Subscribe for more conversations with the operators and founders behind today's best go-to-market teams.

The GTMnow Podcast
The GTMnow Podcast is a weekly podcast featuring interviews with the top 1% GTM executives, VCs, and founders. Conversations reveal the unshared details behind how they have grown companies, and the go-to-market strategies responsible for shaping that growth.

Visit gtmnow.com for more episodes and other interesting content. 

Transcript

SPEAKER_02 0:00

If a company needs FAQs, then it's not a plan, it's a practical. And the top performing means are going to consistently get closer to a million dollars in learnings every single year.

SPEAKER_00 0:08

Sales compensation is not, like you mentioned, a clock center, it's actually a huge lever of your go-to market strategy.

SPEAKER_02 0:14

You think of sales compensation? It's basically the view that connects the company's intentions to the rep secrets. So at the end of the day, if you see reps not doing the things that you want them to do, then it's not going and checking with the rep, it's really going and checking your comp plan because that's what the comp plan is telling them to do.

SPEAKER_00 0:31

Deva Rajamani, co-founder and CEO of Everstate.

SPEAKER_02 0:35

The RevOps, they were meant to be the architect, but today they're really being plumbers. And so the evolution in the next two years is you will start to see revenue and operational professionals really become revenue architects for the company.

SPEAKER_00 0:46

You recently actually ran a survey of over 400 RevOps professionals.

SPEAKER_02 0:51

Teams that have tried to experiment but just bolt on AI ended up being less satisfied with the solution than teams that didn't even experiment with it.

SPEAKER_00 1:00

How are you yourself first in an organization leveraging it on everything? Ziva, welcome to GTM now.

SPEAKER_02 1:23

Excited.

SPEAKER_00 1:23

Yeah, likewise. Likewise, likewise. And there's nobody better to dive into this topic than yourself. We're going to jump into the meaty topic of sales compensation. And I am so excited. This is one of the most frequent topics that comes up both across the GTM fund portfolio and across the community of GTM leaders, LPs. So very excited that pattern holds for the greater ecosystem. Your background is actually quite an interesting node and insightful journey around sales compensation. So why don't we start there with your time at Freshwork? Take us back. What were you working on? What did you learn?

SPEAKER_02 2:00

Yeah, I mean, this uh, you know, is uh pretty nausea because it takes me back 10 years back when um RevOps was still something that was uh uh becoming popular as a function, right? Like this uh was the time in 2015, 2016 when revenue operations became more common in most functions. And so that was the time when I was at FreshWorks leading the revenue operations. Uh it was a very uh fun part of the journey. Uh RevOps, I mean FreshWorks was growing, uh tripling year over year. It was, I think when I joined, it was in the 10 to 100 million ARR journey. And so there's lots of learning for me, of course. But obviously, as uh someone who was managing or setting up the revenue operations function, there's a lot of aspects that were uh very interesting because I saw that you know we were growing a lot uh from a revenue standpoint, but there's lots of things that were broken on the revenue process standpoint, uh system standpoint. And in general, uh anything that contributes towards revenue, there was a lot of like uh broken areas. And it was surprising to me that we still were able to grow at that pace. Uh right. And uh so that was uh really my time when uh you know I started to understand it was not just unique to Freshworks alone, right? Like uh there was a lot of other uh peers that I was speaking to at that point in time, and everybody was going through a very similar setup of um you know broken processes and systems. And this was also the time 10 years back when there was a proliferation of go-to-market tech, uh, right. So um you had a lot of new tech coming in, processes were broken, and then it all ended up being uh a mix of a situation where you were trying to solve with systems, but then it just accelerated the broken process further. Um so yeah, a ton of learnings at that point in time. I do remember one time, for example, when um there was uh a pricing change. Uh, and this pricing change was driven by the product management team and the product marketing team, obviously. Um, but as you can imagine, any change in prices have downstream impact on the go-to-market side. Uh impact on, say, for example, the average contract value, right? With higher prices, you presume that your contract values are going to be bigger. There's also gonna be an impact on the um win rates or the conversion rates from pipeline to closure, presuming that you might have to, you know, lose out some deals where you know people are not prepared to pay that price. But all of this also meant that it's gonna have an impact on the sales quota, right? And but there was a pricing change that was determined by the product and product marketing teams, and the go-to-market teams were uh really informed. Uh, and then here you we are at revenue operations uh you know trying to figure out how to set now change things, like from quotas to um you know compensation, etc. Because there was huge frustration on the sales uh floor um when you had this change come in without that impacting the other things that you had to change. So uh, and as I said, this is not just unique to one company, it was just the common theme. And uh yeah, I felt like there's an opportunity to come and fix this. Uh and honestly, more like a personal beeve to solve for uh in some sense.

SPEAKER_00 5:13

Yeah, you felt the the pain firsthand. And you started as kind of built out at FreshWorks the singular function of RobOps all the way to a team of about 25.

SPEAKER_01 5:23

Right.

SPEAKER_00 5:24

It's definitely worth mentioning because that takes kind of the the base of it and then really just uh simplifies a lot of the systems that are crazy and messy to begin with.

SPEAKER_02 5:34

Absolutely. I think uh revenue operations was a great um you know function to come into play because if you think about again the history, before that there were sales operations, there was marketing operations, uh and then there was finally one single uh function um that came in with the promise of solving for a lot of different things. Of course, we have to talk about whether the promise has been solved. Uh but at least, you know, you finally had some somebody to look at the entire end-to-end of the revenue processes and systems.

SPEAKER_00 6:06

Yeah. Okay, so you're in Freshworks and you see this problem at one of the fastest growing companies kind of pre-IPO. Why not build a solution in-house? Like you've scaled the team from one to 25. Why did you decide to actually go and start ever stage?

SPEAKER_02 6:21

Yeah, I think this goes back to um, you know, what I was talking about in terms of my conversations with other peers, right? It was not a unique problem that only one company was facing. It was the common theme across the board. There were new RevOps leaders coming in. So uh the conversation had moved from what does a RevOps leader do to, you know, hey, there's so many different things broken. Where do I go and fix? Uh, right. And there's again, as I said, proliferation of tools, but the tools were the vendors in the market weren't really solving for uh, especially companies that were growing super fast. So there was a mix of uh situations where things were broken across the board, and then the there was an opportunity where today the vendors in the market weren't actually addressing the problem uh head on. So I felt like it almost uh it's it was on me to you know come in and build things uh for the community, uh for the better of the community. Uh and I think there were multiple different parts, right? If you think of RevOps, there's obviously multiple different paths, right? From planning to you know tools to uh you know processes to compensation, etc. And uh one of the areas for me was very clear that um, you know, while you had to fix all these processes and systems, ultimately revenue is ultimately driven by humans, and you had to solve for the underlying incentives um to be able to drive the right behavior and performance. Uh if you don't impact the human motivation, any processes that you set up, any tools that you set up will still not solve for uh that problem. And if you think about sales compensation, it's that one thing where uh you know it was set up to drive the right kind of behavior and motivation of your teams. Uh but today, if you speak to most people at most companies, most sales teams, uh uh it's probably the biggest area of friction. So you've taken something that was supposed to motivate into a point of frustration. And uh so there was a huge opportunity to first rectify that whole piece. Because anything that you do on tools and systems, needed to still have aligned sales teams to be able to drive the action.

SPEAKER_00 8:44

Sales compensation is I mean, one of the things that drives revenue at the core for companies. It's it's a huge force and motivator behind behavior and sales and revenue and ultimately growth. What happens when these parts of it are not actually firing together? What happens if we get it wrong?

SPEAKER_02 9:05

Yeah, I think um that's the biggest piece uh a lot of companies um don't think of uh, at least uh early on. Uh they think of sales comp as a back office problem where uh yeah, it's really about computing some numbers and you know making sure you do uh you know payouts effectively. Yeah. But it it's it's much more than that, right? Like because if you think of Salescom, that's the reality between what it's basically the glue that connects companies' intentions to the reps' actions. Um so at the end of the day, if you see uh reps not doing the things that you want them to do, then it's not uh going and checking with the rep, it's really going and checking your comp plan because that's what the comp plan is telling them to do. That's really what they're doing, right? Um and I think so, for example, let's get into some specifics, right? Um I've had uh people tell me that their plan is uh solving for driving more uh longer-term or multi-year contracts, uh, right? So that's really what they want to incentivize. But then um I look at what the teams are doing, and the teams ultimately are exhibiting a scenario of you know, trying to obviously push the deals that will close as quickly as possible. So now there is a disconnect between what you put in the plan and what reps are seeing, because reps are at the end of the day, um most humans at the end of the day, are solving for the path of uh least resistance. And so um, so you're trying to see what gets you to the you know to the path that you want to as fast as you can. So um so you have to go and introspect your compliance. So that's really where you know things are broken. And to me, that's a piece that uh some of the smart CROs know, but um sometimes it's also a question of uh understanding the specifics, right? Like you might have, for example, this multi-year contract as part of your accelerator. But as an example, if um the discounts that you have to give in order to get that multi-year deal is more than the accelerator that you give for the multi-year contract, that means people are not going to sell multi-year contracts because they know even post-tacelerator, it's gonna give them lesser commissions. So, as specific as this, there's so many such examples um of where companies uh think that they've done the right thing on the plan, but actually uh it shows up in the action. Uh if you put it the right way and have given the right exposure to reps on how they make what they make, they you should get the right action.

SPEAKER_00 11:52

Do people usually get the right action? Like what are those one-to-two mistakes that TEES are typically making or CROs are typically making with their comp plans?

SPEAKER_02 12:00

I think the one of the most common themes with Complan is uh most companies, when they start off, start off with a fairly simple plan. But over time, uh, you know, things happen, meaning there's always exceptions. Um, like there's one large deal where something happened and some collections didn't happen uh on time and whatever. And you put an additional class on your comp plan. And over time, every quarter, there's additional classes that keep getting added. Then you try to get creative, you add new components of the plan. And before uh you really review it, over time you start to get this massive complex comp plan that has 10 different parameters. If a comp plan has 10 different parameters to optimize for, it really means that you are not optimizing for anything, right? Like reps are not are not gonna be able to optimize for 10 different things. So I think that's one of the common themes uh that uh I see in especially fast-growing large companies uh where they have overcomplicated the comp plan to an extent where now it's not really helping drive the behavior that you want the teams to exhibit. Um so that's one common theme. There's of course um the other part, which is you've created a plan, but at the end of the day, um and actually just to close out on the loop on the you know complexity, there's also the situation where I see a lot of companies have FAQs on comp plan, right? If a comp line needs FAQs, then it's not a plan, it's a tax code. So so that's really uh you know clearly clarifying how complex your comp plan is. The other part is um if you think of the um aspect of the plan itself, there's obviously things around um you know what you're uh driving the plan to be, but you also need to give visibility to reps uh to be able to understand uh what it means in the reality of the pipeline, right? So, for example, um just being able to help reps understand, hey, what if I were to close this deal? How much could I make? What if I do 10% lesser discount? What if I push this to a multi-year contract? So if you're able to help them see all of these, visualize all of these, even before they take the action, that's what's going to drive them to the action. Today I see this compound that exists. Reps obviously do math, but you may not be sure that it's always the right math. And then at the end of the day, there's some you know spreadsheet where they're doing the math. There's a different one where you're you know giving your payouts at the end of the day, and there's at the end of the month conflict uh between both of these. And so if there's not enough clarity before a rep takes action, they're not going to take that action. So I think the aspect is also to drive enough visibility and enable the reps to uh visualize how much they could make for themselves. That will help drive the right behavior and performance for the company.

SPEAKER_00 15:07

Hmm. Those those are really interesting takeaways, and I'm sure are not unique to any specific company ones. It sounds like you see time and time again. Yeah. And I want to go deeper on both. So let's start with the first point, actually. You talked about overcomplicating comp plans. And I listened to you speak with John Lee. John Lee runs sales compensation at LinkedIn for over 5,000 reps at LinkedIn. And he had this really interesting rule of thumb. It was if your sales compensation plan is longer than 60 seconds, articulating it, it's broken. Yep. How often does that occur? Because you have this unique purview across so many different comp plans.

SPEAKER_02 15:47

That's the situation with 90% of the companies. Wow. Yeah. So um, and as I said, it's not intentional. Companies start off simple. It's just that over time you're solving for that one exception that becomes the rule book on your plan. And then over time these rules start adding up. And before you know, you've just created created such a complex plan that nobody even understands, uh, right? Yeah. Um, and these are not like really large companies that I'm talking about, like enterprises off the scale of LinkedIn. I'm talking about even fast-growing, much smaller companies getting into the this trap of overcomplexity of their plans.

SPEAKER_00 16:28

That makes sense. That absolutely makes sense. And those are oftentimes the use cases people need it more. They're going through hypergrowth. A lot of shifting, and a huge thing that we're seeing from our side is like your sales compensation is not like you mentioned, a cost center. It's actually a huge lever of your go-to-market strategy because it incentivizes your growth, the actions people take towards your growth. So a very, very important one to get right, but it's also extremely hard to get right. So I want to say iterate on well as opposed to get right. Um, at least in the near term, people are starting to get it right. The second part that you mentioned was around how people want to be incentivized to have a positive financial outcome from sales. And I was reading through the data around your state of sales compensation report that recently came out. And there was this really interesting data point. It was around how about 59% of people who are overachievers are satisfied in their role compared to people being satisfied at a rate of about 26% for underachievers. Not surprising that people will be more satisfied when they're overachieving versus underachieving, but that's a huge, huge gap. And churn is a massive problem at companies. So for companies that want to ensure that they're designing comp plans to retain talent and retain the best talent and make them satisfied by helping them make a lot of money. How do you think about designing it? Because it feels like there might be two different ways. Like, are you designing it for fairness? Are you designing it so that people can make a lot of money? How do you actually approach that?

SPEAKER_02 18:06

Yeah, I think we need to understand what's happening in the broadest enterprise sales world, uh the way to think of it, right? Um, especially with the uh with AI, you're gonna have a massive difference between the top performing rep and the rep who's on your average. Because see, at the end of the day, you always have, you know, your best performing reps, you have your middle, and then obviously you have some performers who may not be the right fit for you at that company at that point in time. Now, the gap between that top performer and the middle is going to expand further and further because the top performing reps are going to be much more uh comfortable using AI to increase their leverage. If you think of uh sales, and this is probably going a little off-topic, sales as a function, um in order for you to make more money in sales, primarily you had to move from an IC role into a people management role eventually, right? Like become a sales manager and then you know, a director, VP and whatever, right? That was your path towards maximizing your earning potential. But with the evolution of um, you know, the market today and with the help of AI, I foresee a situation where AEs can maximize their earning potential. Uh, and the top performing AEs are gonna consistently get closer to a million dollar in earnings every single year, right? Today it's an exception. That's something that's going to increasingly become an opportunity for a lot of the top performing AEs. So, and why is that? Because they're going to create so much value for companies, and essentially you want to make sure, therefore, that value uh is translated to how much earnings that the sales reps make. So, in my opinion, companies need to optimize for the earning potential of their sales teams, especially the top performing ones, because as I said, the gap between the top performing ones and the mid-level would increase. And so if you miss out on your top performing A's who have opportunities to make more uh at different companies, then they're gonna move on and you're gonna miss out, right? So I think that's the biggest theme that I would say. So uh, you know, you could solve for um, you know, risk prevention or uh, you know, ensuring that, you know, if there's a really big, large opportunity, you know, what do you do, how much do you pay, and all of that. Or you could solve for, you know, if how many of my AEs can I get them to, you know, today pay over half a million dollars in uh overall earning potential. Because at the end of the day, it's it makes fiscal sense. If you think of, if you actually do the math, what happens is if you continue to have those top-performing AEs and they end up earning a lot of money and you've set up your comp plan for it, you're not uh hiring other AEs uh who are essentially contributing um or you know, misfilling the pike that the top AE has not performed for. So what I mean by that is you don't have as many A's that are needed if you have a lot of top AEs uh who can maximize their earning potential, and thereby they're contributing to the company, right? I'm presuming that the link between revenue contributed to actual earning potential is you know clearly there. And when that's the case, um, you still have only one base salary that you're paying. We're all talking about commissions, yeah. Right. Um, but if you have a ton of mid level folks who aren't contributing as much, so you could have saved, you think that you could have saved on commissions, but you know what, you're paying much more on base salary. Uh so if you actually do the math. It also ends up being positive in terms of uh margins by actually uh optimizing for higher earning potential for your top AEs.

SPEAKER_00 22:12

Got it. So for anyone thinking about how do I design this, it sounds like optimize for highest earning potential. That will create, inevitably, especially with AI's utilization, this delta between your top performers and kind of your lowest performers. And then you continuously iterate by kind of um shifting your team composition to be like higher and higher and higher leverage out of that. Okay.

SPEAKER_02 22:35

Absolutely. And to get into some additional specifics there, that also means that you know your top AEs are not carrying a million dollar quota. They're probably carrying two, two and a half, like higher quotas, and they're gonna be super productive for you and it'll it'll benefit them, it'll benefit the company.

SPEAKER_00 22:53

Should people be giving the top AEs different quotas than let's say the mid-range AE? Yeah, individualizing it?

SPEAKER_02 23:02

As long as, you know, uh you're correcting for the base salary as well. Uh and you know, uh obviously the earning potential is also there, right? Like so a two million quota AE. I mean, we've we talk about quota to OTE ratio. Yeah. Um, so I think in enterprise software at least, you need to try and get to not go beyond like six. Uh six is great. I mean, six X of quota to the on-target earnings. Um so don't go above that. Sorry?

SPEAKER_00 23:29

Don't go above that.

SPEAKER_02 23:30

Yeah, don't go above that, right? Like the four to six is where most companies are. Four to five is actually what I think uh today uh is something that most companies are at. Um so you could optimize for higher quotas, but beyond that, it becomes not very um, you know, you're not setting up the reps for the success. Um so when I talk about two million quotas, you have to ensure that at a 50-50 base in variable uh and at a 5x quota to OT ratio, you're talking about an earning potential of 400,000 for the 2 million. And the base should be at least $200,000. Uh so that's really how I think about it. So you need to increase the base as well. And then obviously give them the opportunity to earn their commissions with the higher quota.

SPEAKER_00 24:15

Got it. And this is a super loaded question, but it's one that broadly comes up in different shapes and forms all the time. And it's how should people think about the ratio between your base and your actual commission for a sales comp plan?

SPEAKER_02 24:29

I think uh in for the sales teams, it's very clearly established. Uh, you know, at a 50-50, it you know, it's fairly well structured uh in enterprise software at least. I mean, you could make some changes, it could be 45, 55, that's fine. But you know, anything outside of that uh is not very competitive uh in enterprise software. Obviously, there's different industries where it's different. Like, for example, if you take commercial real estate, everybody is on 100% commissions. There's no base pay. Yeah. Right? Like so there's industry-specific nuances. Uh, but 50-50 is a good structure for sales teams. Obviously, when you think of customer success and BDRs, you know, the ratios vary. Like BDR teams are more with 70-30, customer success, 80-20 and stuff like that.

SPEAKER_01 25:13

Mm-hmm.

SPEAKER_00 25:14

And we're going through all these very specific sales compensation and commission questions because you have built and scaled and run Everstage. Can you give everyone listening a little bit of context to what Everstage is?

SPEAKER_02 25:28

So, yeah, uh Everstage today um is managing about 300 plus enterprise customers uh on their sales compensation, uh automation, and you know, helping drive the revenue and behaviors of their sales teams. Um, you know, we work across AI native companies, large public SaaS companies, uh, as well as manufacturing, financial services, healthcare companies. So a wide variety of companies that uh trust us and we're growing uh 2x year over year at this point. And um our aspirations are obviously um, you know, my background, as I said, was from revenue operations. So, you know, I see sales composition as the first lever that every company needs to solve for uh to ensure that you're able to get the right revenue results. But that's not the only thing. There's a few other areas that you need to solve for. Um, and that's really the aspiration of web stage as well. You know, we want to help uh revenue teams and revenue operations uh uh professionals with uh a set of um you know partner tools that could help them uh drive results for their companies.

SPEAKER_00 26:43

Very cool. And are you open to sharing how you've structured your sales compensation plans at ever stage kind of percentages? Are they standard? Do they deviate from the standard and why?

SPEAKER_02 26:56

I think um going back to uh some of the things that I mentioned, I mean, obviously based on learnings and also on context that we have from 300 plus customers, uh, we've tried to keep our plans very simple. Um so our quotas are very clear. It's annual quotas with you know quarterly, you know, goals that they have to hit. There's accelerators post 100% uh uh and fairly uh you know good accelerators uh for people who overachieve. So we want to maximize the earning potential of our apps. And uh one of the things that we've optimized for is uh the multi-year contracts. Uh, like most companies, we want to have more uh customers who um you know sign up with us for a longer period. Um, and that's good for them and good for us. And so um from that context, we incentivize multi-year contracts uh uh in a very lucrative way for our apps. Um so they get accelerators on our multi-year contracts. Um and uh so today most of our customers, and that shows up in the action, right? Like more than 85% of our customers are on multi-year contracts with us. Um Wow, that's great. So I think I think the reality of your plans show up in the actions. Uh so it's the best way to check if things are working the way it was intended to. And if not, then you need to go either one check your plan and see, you know, if it's either become overcomplex or if it's not structured the right way in terms of, for example, the accelerators that I mentioned, or if they if the reps don't have the right level of visibility on what the plans are, and actually helping them visualize how they make more money for themselves, right? Like uh so if you have those two, you should be able to see those in the actions of the reps. So, what we've done really is you know, try to keep the plan super simple. We just have three levers, as I said, one is on the overall coda, second is like a multi-year accelerator, third one is more on the one-time revenue. This uh outside of the recurring, I mean, there's also a one-time revenue piece that you know we in seven device uh reps to bring in. Um and just that, right? Keep it super simple, give a lot of visibility, and ultimately help uh, you know, reps maximize their own potential.

SPEAKER_00 29:11

You didn't know, but I was timing you and you passed John Lee's test. Simple 60 seconds. Oh, it's okay. I'm kidding. Um, but but it's true. That is fantastic. Sounds like simplicity has been a huge lever for you. And you've referred to sales compensation and commission specifically as a lever many times now throughout this conversation. So if sales compensation is a lever, then the person that is actually like pulling that lever, the one executing it after designing it and the one understanding the behavioral impact of that, they become pretty valuable. And you've referred to this person as the revenue architect. Tell us a little bit about what that means.

SPEAKER_02 29:51

Yeah, I think so. Um there was a promise, right? With the revenue operations, for the first time, uh, we said, hey, there's going to be this strategic thought partner to the chief revenue officer who's gonna come in and help uh drive the revenue behaviors uh and performance for the team by uh ensuring that the CRO has context of all of the different moving pieces of the revenue motion, figuring out um, you know, how to create leverage for the CRO and ultimately drive revenue predictability through optimizing each part of the system on the revenue process. So that was the promise. But what ended up happening was uh with revenue operations, almost it's like they got consumed by the infrastructure that they were set up to you know build. Right. So, and this was not through their failure, it was it was just through the gravity of you know all of the different things that they had to manage. I uh I jokingly say that at revenue operations, you never get into the limelight and things are going well. But when something breaks, you're already in the spotlight and you know you're the one you know trying to fix it. So all of those firefights ended up becoming a common theme week over week. The proliferation of tools have just complicated it further. And today you have some of the most smartest uh revenue operation leaders and professionals doing a lot of tactical work uh and not solving for the intention of why the function was set up. Right. I think now we are in a very interesting phase where for the first time, again, just like how we talked about sales reps and the opportunity for great ICs to maximize the earning potential. Yeah. I think with AI, there's an opportunity for RevOps professionals to truly uh deliver to the promise of the function, which is to truly be the strategic thought partner to the CRO to help drive revenue results through optimizations and predictability and creating leverage for CROs. And so I think of again, if you think of the RevOps, they were meant to be the architect. Yeah. Uh, but today they're really being plumbers. Uh, right. And so the evolution in the next few years is you will start to see revenue, uh, revenue revenue operations professionals really become revenue architects for the company. And that'll increase the uh importance of that function and the role uh for the overall company and what results that they drive for the company.

SPEAKER_01 32:32

Mm-hmm.

SPEAKER_00 32:33

I can certainly see that in actually the number one kind of look back insight. The number one insight with hindsight's perspective and benefit that people share of what they did right, or they either did not do right and wish they did, was actually higher foreign scale revenue operations earlier because it should serve that role and hopefully can serve that role. And you recently actually ran a survey of over 400 RevOps professionals. What were some of the most surprising data points that came out of that for you?

SPEAKER_02 33:08

I think um one of the most surprising ones was um on uh, you know, teams that have uh tried AI with more like a bolt-on AI, as we call it. Uh something where they've tried to experiment, but just it's a bolt-on AI ended up being less satisfied with the solution than teams that didn't even experiment with AI. Right. So um a situation where somebody who's actually put in something, uh additional work, uh, to try out AI, but not put it, put the entire effort in architecting it the right way, uh, just did a bolt-on AI, end up being less satisfied than actually not doing anything at all. So so this has been um one of our, I mean, biggest surprises, uh, right, like in terms of how I think about it. And that's true because if you think about the overall um function, and if you think of the AI um as a bolt-on, what's really happening is you have things that you say, for example, you want to get insights out of your CRM data. Yeah. With AI today, uh, you know, you all of us use AI to uh do you know research on the market and you know understand what's happening, etc. But then you go and try and bolt on on your CRM, you're not able to get the right level of insights simply because the the overall data is not there. It's not filled to 100%. The data that's there is not fully accurate. And then whatever data that's there also doesn't, there's no additional context that uh you're providing. So if you really were to just bolt-on AI to any of your internal systems, CRM is an example, it's just going to give you uh accelerated nonsense, right? Like so basically uh you're not gonna get you're not gonna get any insights out of it. Yeah. And that's really what's happening where you know, without this, you would have done this on spreadsheets. Now with bolt-on AI, you're thinking that you're gonna get magical insights, and then all you get is, you know, uh something that seems like insight, but it's not. And you have to now go clean up the mess. So that's the situation that we're seeing with uh uh you know revenue operations professional. And that's so that was a very interesting thing that came out of the survey.

SPEAKER_00 35:27

So is the solution then to that to not leverage Bolton AI and simply leverage AI native AI?

SPEAKER_02 35:35

So I think the thing is really is to going back to where where the role needs to evolve to, which is the revenue architect role, right? Like you need to set the foundations right. Um and so what that what does that mean? So there's obviously um, you know, there's your system of record that's not fully clean. So you need to first set the system of record in place. Uh and for that, you have to do a bunch of different things. Uh and there's lots of different ways that you could do that. For example, uh use unstructured data to drive a lot of the data points that are not filled in in your CRM, for example. Uh there's obviously you need to structure the date uh time of the record because things keep evolving. If you think of the data that's there in any of the systems, whether it's CRM or ERP, it's point-in-time data. It tells you what's the situation today. It doesn't tell you what was the situation one month back. You need that context to be able to derive insights. And so, as I said, it goes back to creating first the foundation uh to be able to then um, you know, generate insights on top. And which is why we think of revenue operations evolving into more a revenue architect role to set the foundation in place, think through all of the different things that needs to be uh set up before you could uh put on AI uh and accelerate insights and the next best actions and everything else that helps the company drive revenue growth.

SPEAKER_00 37:07

Mm-hmm. That that completely makes sense. And I mean, you're really tackling it from a holistic side. You mentioned at the beginning that you decided to solve this problem for you were use the word community. And that really is what you're doing now. You're actually elevating a role, you're actually creating a solution, but it's much more holistic than a tool for commission. It's like truly a transformation, it sounds like of the org design and role. And you're also dealing with one of the most, I mean, most emotional topics for people, which is their finances a lot of the time. Designing plans for people's individual finances and livelihood. And then you're you're pairing that overall with their careers. How do you, kind of as a founder, handling such a kind of precarious and sensitive topic, like how do you find that you've been able to actually um lead in that space? Because a lot of other leaders feel like there's, you know, sensitive topics that are related to what they're building. And you're almost at this interesting intersection where you're dealing with psychology and finances and like very, very sensitive topics for people.

SPEAKER_02 38:18

Absolutely. I think um, so which is why I think uh we don't take our work for granted. You know, we are investing a lot, uh, you know, because business models are evolving. For example, if you think of new companies, uh, there's a lot of usage-based billing and consumption-based pricing. Um, we didn't talk about pricing actually. So I think of pricing as a very important uh complementary aspect to the entire commissions. And so all of these are interlinked. Yeah. You know, pricing is interlinked to quotas, and then uh quotas are interlinked to territories. Territories also determine how you think about commission plans. So all of these are very interlinked, and you'd have to ensure that you cover all of these different topics. It's not just, you know, a calm plan calculation. That's probably the easiest part, right? The math is the easiest part. If you think of every company, the reason why things break is all of these different parts that I talked about, whether it's pricing, territories, quotas, commissions, they're all rules heavy, but they're also exceptions heavy. There's always an exception to every rule. And so you need to understand where and why those exceptions are happening and model it as part of your uh, you know, uh tool that you create. Because that's when you can truly automate this whole process and drive the results that you want, uh, both for uh you know administrators and web ops and finance as well as to the ultimate users who are uh the sales teams.

SPEAKER_00 39:45

Can you give us an example for?

SPEAKER_02 39:47

So, for example, um you could think of pricing, right? Like so uh in enterprise software, again, you would have uh seen uh scenarios where you know there's the same list price, but there's a particular prospect who might have gotten a discount at a particular point in time vis-a-vis another prospect. And there be there could be more context associated with it, right? This could be a different prospect in a different vertical, um, and uh potentially their margins may not be as much as the other company in a different uh industry. There might be a much more fast-growing logo, so you want to optimize for getting that logo. Uh, there could be a situation where um, you know, it's quarter end, and so you want to drive, you know, revenue closure. So there's a lot of different contexts. And so there's exceptions that you're taking uh for the same list price, on, but it's not because it's of one reason. There's multiple different reasons why those exceptions could happen. This could be the same thing with uh commissions as well. You could take a particular deal, but that one particular deal, a large deal, could have been worked by two different reps, uh, because there was one rep who you know uh went on a maternity leave and had worked almost 80% of the deal, and you want to make sure you know that person's incentivized as well. Uh so what do you do there? Do you now just break the commissions into half, or you do uh um, you know, increase the pie so that you know there's enough uh motivation for the new rep coming into drive closure? So there's always exceptions that you create uh for every rule. Um you could have paid out commissions, but there could be a situation where this one particular customer you never ended up collecting. You paid out commissions on bookings, but then um there is the collections issue. Now the collections issue could be driven by a bag sale, collection issue could just be driven by the company, you know, going out of business. So what do you do there, right? There's an exception that you need to take. So all of these are exceptions that happen, but there's a pattern that you could decipher out of those uh and then that's the piece that tools need to really understand because with automation, it's easy to automate rules. It's super hard to automate exceptions. When you're able to automate exceptions, you really become a partner of choice.

SPEAKER_00 42:06

Siva, you mentioned that there's going to be a larger delta between your top performers, those leveraging AI, and more of your middle-of-the-pack AEs. Let's talk about AI. How are you yourself first as an organization leveraging it at every stage?

SPEAKER_02 42:22

Yeah, I think uh obviously, uh like most other uh enterprise software companies, we are betting big on AI as a transformational change coming into the industry. Uh and personally, for me, uh, you know, the last 18 months have been probably the most busiest, I would say. Because uh, you know, it's AI has really helped, you know, uh get me back into the weeds and really helped me get super hands-on. So I'm really thankful for that, for that. Um, and so some of the ways I use AI, for example, is um, certainly um today, if you think of Everstage, my sales teams, my customer success teams have hundreds of calls every week. I previously it was not practical for me to get insights out of these calls. I mean, you could do at uh individual call level, but at scale, to look at the same call and decipher different insights, that was not possible. Um, and today, with the help of AI and you could really make it happen, right? Like you could uh understand the same set of calls and see what are the points of objections that we need to better handle uh from a sales uh standpoint. What are the what's the feedback that's coming in from a product that helps us, you know, uh get better from a product and uh roadmap standpoint? Uh so the same calls can decipher different insights. You could also start to generate uh insights at scale. Of course, there's a little bit of tooling that needs to be done on top uh to be able to architect it, but uh you know. You could start to derive insights, for example, uh, and we build we've built something in-house for it. Um, that helps us uh, you know, tell us for deals that have a certain kind of buyer uh at a certain stage in the revenue process, what's the uh level of conversion rates and how much of an increase is the conversion rates if that persona was were to be there, right? And this is something that you can analyze at scale without bothering your apps to fill it on CRM uh to say, hey, yeah, you know, there was this persona that came on board in this uh particular stage. There's also something that you could see uh things that have evolved over time in terms of uh like what was something that seemed like a base two quarters previous uh you know before, but now has changed. Uh say, for example, um there was a particular competitor. Uh, you know, what were your win rates that you were looking at if the competitor was mentioned in your initial calls vis-a-vis later calls. Uh, right. Like again, all of these things were just very anecdotal information that you could get previously. But today, um, there's a little bit of work that you have to do, and you know, that's something that we've built in terms of uh tooling. But with that tooling, you could really go into accurate insights. Uh, and so which is why I said you'd have to first build the foundation to be able to uh get to that insights. But you know, once you build the foundation, um, or you know, there will be certainly providers who you could buy it from, you know, you'd be able to generate insights that helps you take next best actions. Because at the end of the day, why are we looking at all of these insights, right? Like all of this is uh to help be more agile, competitive, and ultimately drive the value that we want to drive in the market uh with our customers. So it's been super um helpful that way. Obviously, I use it for some of the other more common use cases as well, which is like market research, understanding what's happening in a certain segment, in a certain uh industry for new product research. You know, we as I said, you know, our aspirations is to build a suite of products that helps the revenue operations truly become revenue architects. And so um in that pursuit, you know, there's a bunch of things that uh abused AI for. So at least from a secondary research standpoint.

SPEAKER_00 46:27

Very cool. So it sounds like you're doing a lot of data aggregation, pattern matching, outlier action, um, next steps too from that. Do you leverage AI match for your personal kind of productivity right now? You know, you are an extremely busy person. You're leaving every stage, you're the founder and CEO. How are you actually managing your time and leveraging AI?

SPEAKER_02 46:47

I think AI has really made me more um uh, I would say, uh productive, but also more busy uh in some things. Yes. Because um the way I think about this is there's just um so many things to learn. And it feels like now uh uh uh kid in the candy store uh kind of situation, there's just lots of things and so without you trying to actually be uh you know so involved, you just get consumed with a lot of uh areas. And so what I've tried to now do is ensure um uh I get my six, seven hours of sleep. Because being uh fully active is important for you to leverage AI the most, in my opinion. Um, because there's a ton of context switching that you'll need to do while you know working, giving a task to AI and then speaking to your team and then coming back to see you know what's done. And you know, uh there's a there's always context switching in leadership, but uh I think with AI it's just accelerated. Yeah. And uh so yes, uh, so today I've never believed in uh having like uh you know personal assistant, uh, not in um you know having like a chief of staff kind of uh teams. I know there's a lot of leverage uh through those teams, but I think with AI now, you could really get all of the benefits of those without having um, you know, uh necessarily people in those roles.

SPEAKER_00 48:14

For sure. For sure. And I will say I I've built a chief of staff uh leveraging AI and it's certainly helpful, but it's definitely not the exact same yet. Uh yet. Hopefully we'll get there. But it's it's taken off like a massive part of that role. Absolutely.

SPEAKER_02 48:29

Absolutely. Yeah.

SPEAKER_00 48:30

And you've mentioned a couple of times some aspirations for Everstage. What's next for Everstage?

SPEAKER_02 48:35

Yeah. So uh so as I said, I think uh with commissions, um, you know, we've really been able to uh, you know, uh help companies drive the uh behavior and performance of their sales teams. Um but there's a few other parts that are connected to commissions, as I told you. So there's one on the territory and coda and capacity management side. So we launched our product for uh you know territory and coda management last year. Yeah. Uh so that's been a very uh important addition for companies to think of how uh to manage commissions. It's not just commissions, it's typically coda and territories that you also need to manage in order to manage commissions effectively. So that's something that we launched. Earlier this year, we launched uh CPQ, configure price and code. Um, so the way I think about this is increasingly going to become a very important part of uh how you need to manage commissions because what ends up happening is today, if you think of most commission plans, they solve for driving revenue from a quantity standpoint, right? Right. Most plans don't solve for the margins, the quality side of things, right? Like not every dollar is the same. Yeah. So you want to get the right kind of dollars. And so I think of uh if commissions wear the carrot, CPQ is kind of the stick uh in some sense, it ensures you get the right discipline and the right kind of revenue. And so both of these are connected. Um, and there's obviously a lot of opportunity with uh you know quoting because today, again, it's a broken experience for uh a lot of the sales teams. Sales reps spend an inordinate amount of time creating quotes, it's not value uh for their time, uh especially for those uh you know top reps. And there's today a lot of opportunity with AI to accelerate code creation, right? So if you think of code creation, um, there's a lot of context from call recordings, there's uh context obviously from your CRM, emails, etc. You could use a lot of that context to um create the code without the reps having to, you know, do anything from their end, right?

SPEAKER_01 50:51

Right.

SPEAKER_02 50:52

And it's not just that. Now, with that, you could also then nudge your um you know, uh the layer that's in the middle to say, hey, you know what? Uh typically for uh these um kind of deals, some of our your other peers also tend to add a support package. You also want to add that as part of your code, like nudge them to the kind of uh you know, uh revenue structure that you want to get to. Yeah. And let them also then look at their commissions and visualize how much of that will help impact what their commission payouts would be. So, with that, you're ensuring that the uh intention of the company and the action that the rep takes are both linked. So that's the vision. Uh and uh so we've launched CPQ and we have aspirations to go further in to help, as you said, revenue operations professionals become truly revenue architects.

SPEAKER_00 51:50

At what point in the revenue journey should people be earning commission on? Because oftentimes to date, it's been on the sale. Now what we're seeing is a lot of people are now incentivized to hit that one-year mark or other kind of renewal marks and their commission is actually shifting further down the funnel. Curious what you're seeing.

SPEAKER_02 52:08

I think um it still needs to be. I mean, if not 100%, most of it needs to be at the time of booking, because that's when, because that's the most important time frame uh where, you know, a prospect is truly becoming a customer. But again, that's provided they are committing to be a customer. For example, if there's an opt-out to us after a proof of concept, then that doesn't mean that you know you pay out commissions 100% uh on the signup, uh, right. So you want to make sure uh, you know, they continue to serve US customers. Because at the end of the day, today all of the commission plans are structured towards at least a 12-month period where uh, you know, the prospect continues to be your customer. Uh, and if that's not the case, again, if the revenue process that you have doesn't structure for it, then you'd have to modify your commission plan accordingly and position it as uh something where you also have additional breaks at the end of one year or something of that sort. That's increasingly relevant in consumption-based um you know, pricing, where um you might have gotten a lower number to get uh your uh feed in. Um but you want to uh see what happens if the company expands, then you want to also incentivize the rep for the sale. Um, and just see you know what actions are taken in the first 12 months. So so that's the only thing that I'd say. But again, as you see, all of it flows from what your the company's intentions are, the revenue intentions are. As long as you can match it exactly to the comp plan, uh you'll see the right actions.

SPEAKER_00 53:42

So it sounds like your overall motion in addition to the outcomes under that are going to greatly dictate your actual commission structure.

SPEAKER_02 53:51

Absolutely. And which is why you have you know different structures in different companies. Um it it has to tie back to the overall goals of the company. Yeah.

SPEAKER_00 54:00

GitHub has this really interesting structure where they actually count their salespeople on a six-month cycle. Have you seen that in other companies? And what do you think of that six-month versus 12-month mark?

SPEAKER_02 54:11

I think that's a great thing. And uh at the end of the day, today, uh, you know, things are evolving rapidly. So it's um, you know, it's good to, you know, be agile. I think the only thing that I'd say is a word of caution is um that you don't change things drastically uh when you end the six months, right? Like what you need some level of um stability for people to uh drive uh for you to push a certain kind of behavior on reps. If you keep changing things, people are uh not going to be sure of what you want them to do, uh, and just creates confusion. Um, so you could also achieve agility by still keeping a 12-month comp plan by evolving your coda structures. Uh right. So there's different ways you could still achieve agility while keeping a 12-month plan. Uh there could be short-term incentives that you could uh leverage for a particular quarter additionally. Um, so there's multiple mechanisms to achieve agility. Uh, but again, again, it flows back to what your goals are. Um, if you think your goals will evolve six months down the line, it might be better for you to structure uh your plan at this point, fully welling, fully knowing well that uh you know you will change some structures of the plan depending on what the market situation is six months down the line.

SPEAKER_00 55:36

Perfect. Um and last rapid fire question that that we may potentially stitch in is what is the most that you've seen a sales rep make in a year?

SPEAKER_02 55:47

Historically, before I was uh I was an entrepreneur, before that I was a RevOps person, I was a consultant. Uh right. And as a management consultant, I got an opportunity to um you know work on some deals where there was uh you know MA deals. And pretty much in every single deal, what I saw was um the highest earning person in the company was not the CEO, was like an enterprise AE who's uh you know who sold like a really massive deal and um you know ultimately you know was making commissions off that. So I think your best AE should probably make more than a CEO. So that's really what I think.

SPEAKER_00 56:24

I love it. Well, AEs will be very excited by that news.

SPEAKER_02 56:28

Uh they should be. I mean, they've deserved what uh you know how they the reason why they're making more is because they've contributed so much value to the company. Um and so yeah, I think that should be the case.

SPEAKER_00 56:40

Amazing. And if people want to follow along you in Everstage's journey, where can they find you?

SPEAKER_02 56:45

Yeah, I'm pretty active on LinkedIn. Uh so I do uh share a lot of uh my thoughts, learnings from uh, you know, both personal learnings from you know things that I've uh learned over the years, but also from uh, you know, uh advising a lot of customers today on what are the things that uh are uh some of the customers are doing well and things that we could all learn from. So LinkedIn's a great place. I'm fairly active. Uh and uh yeah, Twitter is also the other place.

SPEAKER_00 57:12

Amazing. Those will be in the show notes. Siva, thank you so much. This has been an extremely insightful conversation.

SPEAKER_02 57:18

Thank you so much for having me. I really enjoyed it. Thank you.

SPEAKER_00 57:21

Absolutely.