How to Use Sales Comp as a GTM Lever | Siva Rajamani (Everstage CEO)

Podcasts

Listen on YouTube // Apple // Spotify

Who we sat down with

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.

Episode highlights

0:30 – Siva’s RevOps background at Freshworks

4:00 – Scaling RevOps from 1 to 25

4:50 – Why he left to build Everstage

6:30 – Why incentives drive revenue, not tools

8:00 – 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

Key takeaways

1. Your comp plan is the real instruction manual, not your 1-on-1s.
If reps aren’t doing what you want, don’t question the rep, audit the plan. Sales compensation is the glue between what a company intends and what reps actually do, and people will always follow the path of least resistance the plan creates. If the plan rewards fast closes, you’ll get fast closes, no matter what you say you want.

2. Complexity is the silent killer, and 90% of plans fail the test.
Companies start simple, then patch in one exception after another until the plan has ten parameters and optimizes for nothing. Siva’s gut checks: if explaining the plan takes longer than 60 seconds, it’s broken, and if your comp plan needs an FAQ, it’s not a plan, it’s a tax code.

3. Watch the hidden math, or you’ll punish the behavior you’re trying to reward. A classic trap: a company adds an accelerator for multi-year deals, but the discount reps must give to land those deals outweighs the accelerator. So reps rationally avoid multi-year contracts. The intent shows up in the spreadsheet, not the slide.

4. Optimize for your top reps’ earning potential, it’s better on margins too.
The gap between top and average reps is widening fast, especially as top performers use AI to scale their leverage, and the best ICs are heading toward $1M+ in annual earnings. Counterintuitively, paying big commissions to a few A-players beats hiring a stack of mid-level reps, because you carry far fewer base salaries for the same revenue.

5. Keep it simple and make earnings visible.
Everstage runs its own plan on just three levers (overall quota, a multi-year accelerator, and one-time revenue) and stays inside standard enterprise benchmarks: roughly 50/50 base-to-variable and a 4 to 5 quota-to-OTE ratio. Just as important, reps need to see their potential earnings before they act, the ability to visualize “what do I make if I close this?” is what actually drives behavior.

The GTMnow Podcast – subscribe to support

It would mean the world to us if you subscribe to the show on your platform of choice. This helps support our growth, which in turn helps us continuously bring on bigger guests and deliver the content that you want to hear most.

The GTMnow Podcast shares how the best in tech build, scale and invest.

Visit gtmnow.com for more episodes, The GTMnow Newsletter editions, and other content.

GTMnow is run by GTMfund, an early-stage venture firm made up of 350+ go-to-market executives from the fastest-growing companies.

GTM 194 Episode Transcript

00:00 – 00:08

Siva Rajamani: For complex needs FAQs, then it’s not a plan, it’s a tax code. And the top performing is are going to consistently get closer to $1 million in earnings every single year.

00:08 – 00:14

Sophie Buonassisi: Sales compensation is is not, like you mentioned, a cost center. It’s actually a huge lever of your go to market strategy.

00:14 – 00:31

Siva Rajamani: I think of sales, it’s basically the glue that connects companies intentions to the reps actions. So at the end of the day, if you see the 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 compliance because that’s what the compliance is telling them to do.

00:31 – 00:35

Sophie Buonassisi: Seva Rajamani, co-founder and CEO of Ever Stage.

00:35 – 00:46

Siva Rajamani: They were meant to be the architect, but today they’re really being plumbers. And so the evolution in the next few years is you will start to see revenue operations professionals really become revenue architects for the company.

00:46 – 00:50

Sophie Buonassisi: You recently actually ran a survey of over 400 rev ops professionals.

00:51 – 01:00

Siva Rajamani: Teams that have tried to experiment, but just it’s a bolt on AI ended up being less satisfied with the solution. Then teams that didn’t even experiment with their.

01:00 – 01:21

Sophie Buonassisi: How are you yourself first as an organization leveraging it at every stage?

01:21 – 01:22

Sophie Buonassisi: Welcome to GTM now.

01:22 – 01:23

Siva Rajamani: Excited?

01:23 – 01:25

Sophie Buonassisi: Yeah. Likewise.

01:25 – 01:25

Siva Rajamani: Yeah.

01:25 – 01:46

Sophie Buonassisi: 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.

01:46 – 02:00

Sophie Buonassisi: 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 Fresh Work? Take us back. What were you working on? What did you learn?

02:00 – 02:22

Siva Rajamani: Yeah, I mean, this is pretty nasty because it takes me back. Ten years back when River ops was still something that was becoming popular as a function, right? Like, this 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 Fresh Works leading the revenue operations.

02:22 – 03:02

Siva Rajamani: It was a very fun part of the journey. I mean, Fresh Works was growing, tripling year over year. It was, I think when I joined, it was in the 10 to 100 million error journey. And so there’s lots of learning from me, of course. But obviously, as someone who is managing or setting up the revenue operations function, there’s a lot of aspects that were very interesting because I saw that, you know, we were growing lot from a revenue standpoint, but there’s lots of things that were broken on the revenue process, ten point system standpoint and in general, anything that contributes towards revenue, there was a lot of like broken areas, and it was surprising to

03:02 – 03:22

Siva Rajamani: me that we still were able to, you know, grow at that base. Right. And so that was really my time when, you know, I start to understand it was not just unique to fresh works alone. Right? Like there was a lot of other peers that I was speaking to at that point in time, and everybody was going through a very similar setup of, you know, broken processes and systems.

03:22 – 03:45

Siva Rajamani: And this was also the time ten years back when there was a proliferation of go to market tech, right? So you had a lot of new tech coming in. Processes were broken. And then it all ended up being a mix of a situation where you were trying to solve with systems, but then it just accelerated the broken process further.

03:45 – 04:07

Siva Rajamani: So yeah, Town of learnings at that point in time, I do remember one time, for example, when, there was a, a pricing change and this pricing change was driven by the product management team and the product marketing team, obviously. But as you can imagine, any change in prices have downstream impact on the go to market side impact on, say, for example, the average contract value, right.

04:07 – 04:27

Siva Rajamani: With the higher prices, you presume that your contract values are going to be bigger is also going to be impact on the wind 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 going to have an impact on the sales quarter.

04:28 – 04:56

Siva Rajamani: 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 really informed. And then here we are at revenue operations you know trying to figure out how to set now change things right from codas to, you know, compensation etc. because there’s huge frustration in the sales floor when you had the strange come in without that impacting the other things that you had to change.

04:56 – 05:13

Siva Rajamani: So and as I said, this is not just unique to one company, it was just the common theme. And yeah, I felt like there’s a opportunity to come and fix this and honestly, more like a personal peeve to solve for in some sense.

05:13 – 05:34

Sophie Buonassisi: You felt the the pain firsthand and you started kind of built out that first work, the singular function of robots all the way to a team of about 25. Great. That’s definitely worth mentioning because that takes kind of the the base of it, and then really just simplifies a lot of the systems that are crazy and messy to begin with.

05:34 – 05:57

Siva Rajamani: Absolutely. I think revenue operations was a great, 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, and then there was finally one single function, that came in with a promise of solving for a lot of different things. Of course, we have to talk about whether the promise is being solved.

05:58 – 06:06

Siva Rajamani: But but at least, you know, you finally had some somebody to look at the entire end to end of the revenue process and systems.

06:06 – 06:21

Sophie Buonassisi: Yeah. Okay. So you’re in fresh works and you see this, this problem of one of the fastest growing companies kind of pre-IPO. Why not build a solution in house like you scaled the team from 1 to 25. Why did you decide to actually go and start ever stage?

06:21 – 06:43

Siva Rajamani: Yeah, I think this goes back to, 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 River ops leaders coming in. So the conversation had moved from, what does a leader do to, you know, hey, there’s so many different things broken.

06:44 – 07:12

Siva Rajamani: Where do I go and fix. 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 especially companies that have been growing super fast. So there was a mix of situation 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 head on.

07:12 – 07:35

Siva Rajamani: So I felt like it almost. It’s it was on me to, you know, come in and build things for the community for the better of the community. And I think there were multiple different parts. Right. If you think of wraps as obviously multiple different paths, right? From planning to, you know, tools to, you know, processes to compensation, etc..

07:35 – 08:05

Siva Rajamani: And one of the areas for me was very clear that, you know, while you had to fix all these processes and systems, ultimately revenue is ultimately driven by humans, and you have to solve for the underlying incentives to be able to drive the right behavior and performance. 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 that problem.

08:05 – 08:29

Siva Rajamani: And if you think about sales compensation, it’s that one thing where, you know, it was set up to drive the right kind of behavior and motivation of your teams. But today, if you speak to most people, at most companies, most sales teams, it’s probably the biggest area of friction. So you’ve taken something that was supposed to motivate into a point of frustration.

08:30 – 08:44

Siva Rajamani: And so there was a huge opportunity to first rectify that whole piece, because anything that you do on tools and systems need to still have aligned sales teams to be able to drive the action.

08:44 – 09:05

Sophie Buonassisi: Sales compensation is I mean, one of the things that drives revenue at the core for companies. 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?

09:05 – 09:39

Siva Rajamani: Yeah, I think that’s the biggest piece. A lot of companies don’t think of, at least early on, they think of sales comp as a back office problem where, yeah, it’s really about computing some numbers and making sure you do, you know, payouts effectively. Yeah. But it’s it’s much more than that. Right. Because if you think of sales comp, that’s the reality between what it’s basically the glue that connects companies intentions to the reps actions.

09:39 – 10:04

Siva Rajamani: 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. That’s really what they’re doing, right? And I think so, for example, let’s get into some specifics.

10:04 – 10:30

Siva Rajamani: Right. I’ve had people tell me that the plan is solving for driving more. Longer term or multi-year contracts. Right. So that’s really what they want to incentivize. But then 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.

10:30 – 10:52

Siva Rajamani: So now there is a disconnect between what you’ve put in the plan and what reps are seeing, because reps are at the end of the day. Most humans at the end of the day are solving for the path of least resistance. And so, so you’re trying to see what gets you to the, you know, the path that you want to as fast as you can.

10:53 – 11:24

Siva Rajamani: So, so you have to go and introspect your complex. So that’s really where, you know, things are broken. And to me that’s a piece that some of the smart crows know. But sometimes it’s also a question of understanding the specifics. Right. Like you might have, for example, this multi-year contract as part of your accelerator. But as an example, if, 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.

11:24 – 11:52

Siva Rajamani: That means people are not going to sell multi-year contract because they know even post the accelerator, it’s going to get them lesser commissions. So as specific as this, there’s so many such examples of where companies think that they’ve done the right thing on the plan, but actually it shows up in the action. If you put it the right way, and if given the right exposure to reps on how they make what they make, they you should get the right action.

11:52 – 12:00

Sophie Buonassisi: Do people usually get the right action. Like what are those 1 to 2 mistakes that teams are typically making or zeroes are typically making with their compliance.

12:00 – 12:26

Siva Rajamani: I think the one of the most common themes with compliance is most companies when they start off, start off with a fairly simple plan. But over time you know things happen. Meaning this always exceptions. Like there’s one large deal where something happened and some collections didn’t happen on time and whatever, and you put an additional class on your compliance.

12:26 – 12:52

Siva Rajamani: 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 you really review it, over time you start to get this massive, complex comp plan that has ten different parameters. If a complex has ten different parameters to optimize for, it really means that you are not optimizing for anything, right?

12:52 – 13:15

Siva Rajamani: Like reps are not are not going to be able to, you know, optimize for ten different things. So. Right. I think that’s one of the common themes that I see in especially fast growing large companies, 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.

13:15 – 13:38

Siva Rajamani: So that’s one common theme. There’s of course, the other part, which is you’ve created a plan, but at the end of the day, and actually just to close out on the loop on the complexity, there’s also the situation where I see a lot of companies have FAQs on compliant. Right. So complex needs FAQs then. It’s not a plan.

13:38 – 14:06

Siva Rajamani: It’s a tax code. So so that’s really, you know, clearly clarifying how complex your complaint is. The other part is, if you think of the aspect of the plan itself, there’s obviously things around, you know, what your driving the plan to be, but you also need to give visibility to reps to be able to understand what it means in the reality of the pipeline.

14:06 – 14:29

Siva Rajamani: Right? So for example, 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.

14:29 – 14:48

Siva Rajamani: Today I see this compound that they exist. That’s 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. This a different one where you’re giving your peers with another day. And this at the end of the month conflict between both of these.

14:48 – 15:08

Siva Rajamani: 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 visualize how much they could make for themselves. That will help drive the right behavior and performance for the company.

15:08 – 15:31

Sophie Buonassisi: Those those are really interesting takeaways that I’m sure are not unique to any specific company. Ones it sounds like you see time and time again, 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 competition at LinkedIn for over 5000 reps at LinkedIn.

15:31 – 15:47

Sophie Buonassisi: And he had this really interesting rule of thumb. It was if your sales compensation plan is longer than 60s articulating it, it’s broken. Yep. How often does that occur? Because you have this unique purview across so many different comp plans.

15:47 – 16:12

Siva Rajamani: That’s the situation with 90% of the companies. Wow. Yeah. So, 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 rulebook on your plan. And then over time, these rules start adding up. And before, you know, you’ve just created such a complex plan that nobody even understands, right.

16:13 – 16:28

Siva Rajamani: 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 trap of over complexity of their plans.

16:28 – 16:48

Sophie Buonassisi: 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 is shifting. And a huge thing that we’re seeing from our side is like your sales compensation is 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.

16:48 – 17:14

Sophie Buonassisi: 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, 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.

17:14 – 17:41

Sophie Buonassisi: And I was reading through the data around your 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 rate of about 26% for under tubers. Not surprising that people would be more satisfied when they’re overachieving versus under.

17:41 – 18:00

Sophie Buonassisi: 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.

18:00 – 18:06

Sophie Buonassisi: Like, are you designing it for fairness? Or you’re designing it so that people can make a lot of money? How do you actually approach that?

18:06 – 18:29

Siva Rajamani: Yeah, I think we need to understand what’s happening in the broadest enterprise sales world. Way to think of it. Right. Especially with the with AI, you’re going to have a massive difference between the top performing rep and the rep who’s on your average. Because see, the end of the day, you always have, you know, your best performing reps, you have your middle.

18:29 – 19:09

Siva Rajamani: 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 comfortable using AI to increase their leverage. If you think of sales, and this is probably going a little off topic sales as a function, in order for you to make more money in sales, primarily, you had to move from an icy role into a people management role eventually, right?

19:09 – 19:36

Siva Rajamani: Like became 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, you know, the market today and with the help of AI, I foresee a situation where AI’s can maximize their own potential and the top performing AI’s are going to consistently get closer to $1 million in earnings every single year, right?

19:37 – 20:11

Siva Rajamani: Today, it’s an exception. That’s something that’s going to increasingly become an opportunity for a lot of the top performing AI’s. 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 is translated to how much yearnings 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 in the mid-level would increase.

20:11 – 20:37

Siva Rajamani: And so if you miss out on your top performing age, who have opportunities to make more at different companies, then they’re going to move on and you’re going to miss out, right? So I think that’s the biggest theme that I would say. So, you know, you could solve for, you know, risk prevention or, you know, ensuring that, you know, there’s a really big, large opportunity, you know, what you do.

20:37 – 21:19

Siva Rajamani: How much do you pay and all of that. Or you could solve for, you know, if how many of my A’s can I get them to, you know, today pay over half $1 million in overall earning potential because the length 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 A’s and they end up earning a lot of money and you’ve set up your compliance for it, you’re not hiring other A’s who are essentially contributing or, you know, miss filling the pipe that the top A has not performed for.

21:19 – 21:44

Siva Rajamani: 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 A’s 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 clearly there, and when that’s the case, you still have only one base salary that you’re paying.

21:44 – 22:12

Siva Rajamani: We’re all talking about commissions. Yeah, right. 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. So if you actually do the math, it also ends up being positive in terms of margins by actually optimizing for higher earning potential for your top A’s.

22:12 – 22:13

Siva Rajamani: Got it.

22:13 – 22:35

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

22:35 – 22:53

Siva Rajamani: Absolutely. And to get into some additional specifics there, that also means that, you know, your top A’s are not carrying $1 million quota. They’re probably carrying two, two and a half like higher quotas. And they’re going to be super productive for you. And it’ll it’ll benefit them. It’ll benefit the company.

22:53 – 23:01

Sophie Buonassisi: Should people be giving the top a is different quotas than, let’s say, the mid-range. Mid-range. Yeah.

23:01 – 23:23

Siva Rajamani: It as long as you know you’re correcting for the base salary as well. And you know, obviously the earning potential is also there. Right. Like so a 2 million code I mean we we talked about coda to OT ratio. Yeah. So I think in enterprise software at least you need to try and get to not go beyond like six six is great.

23:23 – 23:27

Siva Rajamani: I mean six six of coda to the on target earnings.

23:27 – 23:29

Sophie Buonassisi: So don’t go about that.

23:29 – 23:29

Siva Rajamani: Sorry.

23:29 – 23:30

Sophie Buonassisi: Don’t go above that.

23:30 – 24:08

Siva Rajamani: Yeah. Don’t go about that. Like 4 to 6 is where most companies are. 4 to 5 is actually what I think today is something that most companies are at. So you could optimize for higher quotas, but beyond that it becomes not very, you know, you’re not setting up the reps for the success. So when I talk about 2 million quotas, you have to ensure that at a 5050 base in variable and add A5X coda to OT ratio, you’re talking about a earning potential of 400,000 for the 2 million, and the base should be at least $200,000.

24:08 – 24:15

Siva Rajamani: So so that’s really how I think about it. So you need to increase the base as well. And then obviously giving them the opportunity to earn their commissions with the higher code.

24:15 – 24:29

Sophie Buonassisi: 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?

24:29 – 24:52

Siva Rajamani: I think in for the sales teams, it’s very clearly established. You know, at a 5050, it, you know, is fairly well structured in enterprise software at least. I mean, you could make some changes. That could be 4555. That’s fine. But you know, anything outside of that is not very competitive in enterprise software. Obviously there’s different industries where it’s different.

24:52 – 25:14

Siva Rajamani: Like for example, if you take commercial real estate, everybody is on 100% commissions. There’s no bass player, right? So there’s industry specific nuances. But 5050 is a good structure for sales teams. Obviously when you think of customer success and BDS you know the ratios vary like VDI teams are more. 7030 customer success, 80, 20 and stuff like that.

25:14 – 25:28

Sophie Buonassisi: And we’re going through all these very specific sales compensation and commission questions, because you have built and scaled and run every stage. Can you give everyone listening a little bit of context to whatever stages?

25:28 – 26:03

Siva Rajamani: So yeah, every stage today is managing about 300 plus enterprise customers on their sales compensation automation and, you know, helping drive the revenue and behaviors of their sales teams. You know, we work across AI, native companies, large public SaaS companies, as well as, you know, manufacturing, financial services, healthcare companies or wide variety of companies that trust us. And we’re growing, to year over year at this point.

26:03 – 26:29

Siva Rajamani: And our aspirations are obviously, 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 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, and that’s really the aspiration web stage as well.

26:29 – 26:43

Siva Rajamani: You know, we want to help revenue teams and revenue operations professionals with a set of, you know, partner tools that could help them drive results for their companies.

26:43 – 26:55

Sophie Buonassisi: Very cool. And are you open to sharing how you’ve structured your sales compensation plans that ever stage kind of percentages or the standard? Do they deviate from the standard and why?

26:56 – 27:25

Siva Rajamani: I think going back to some of the things that I mentioned, I mean, obviously based on learnings and also on context that we have from 300 plus customers, we’ve tried to keep our plans very simple. So our quotas are very clear. Its annual quotas with quarterly, you know, goals that they have to hit this accelerators post 100% and fairly, you know, good accelerators for people who achieve.

27:25 – 27:52

Siva Rajamani: So we want to maximize the earning potential of our apps. And one of the things that we’ve optimized for is the multi-year contracts. Like most companies, we want to have more customers who, you know, sign up with us for a longer period, and that’s good for them and good for us. And so from that context, we incentivize multi-year contracts in a very lucrative way for other apps.

27:52 – 28:05

Siva Rajamani: So they get accelerators on those multi-year contracts. And 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.

28:05 – 28:06

Sophie Buonassisi: So wow.

28:06 – 28:06

Siva Rajamani: That’s great.

28:06 – 28:34

Siva Rajamani: So I think I think the reality of your plans show up in the actions. 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 more complex or if it’s not structured the right way in terms of, for example, the accelerators that you 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?

28:34 – 28:36

Siva Rajamani: Like so.

28:36 – 28:53

Siva Rajamani: 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 multiyear accelerator. Third one is more on the one time revenue.

28:53 – 29:11

Siva Rajamani: This, outside of the recurring dream, there’s also an one time revenue piece that, you know, be in twice to bring in. And just that. Right. Keep it super simple, give a lot of visibility and ultimately help, you know, reps maximize their own potential.

29:11 – 29:44

Sophie Buonassisi: You didn’t know, but I was timing you, and you passed John Lee’s test. Simple. 60s. Okay, I’m kidding, but but it’s true. That is fantastic. Sounds like simplicity has been a huge leader for you, and you’ve referred to sales, composition, 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.

29:44 – 29:51

Sophie Buonassisi: And you’ve referred to this person as the revenue Architect. Tell us a little bit about what that means.

29:51 – 30:37

Siva Rajamani: Yeah, I think so. Going back to ops as the function, there was a promise, right? When the revenue operations for the first time, we said, hey, there’s going to be this strategic thought partner to the chief revenue officer who’s going to come in and help drive the revenue behaviors and performance for the team by ensuring that the Crow has context of all of the different moving pieces of the motion, figuring out, you know, how to create leverage for the Crow and ultimately drive revenue predictability through optimizing each part of the system on the revenue process.

30:37 – 30:58

Siva Rajamani: So that was the promise. But what ended up happening was with revenue operations, almost, it’s like they got consumed by the infrastructure that they were set up to, you know, build. Right, right. So and this was not through their failure. It was it was just through the the gravity of, you know, all of the different things that they had to manage.

30:58 – 31:18

Siva Rajamani: I, 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 further.

31:18 – 31:44

Siva Rajamani: And today you have some of the most smartest revenue operation leaders and professionals doing a lot of tactical work 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 talk about sales reps and the opportunity for great ICS to maximize the earning potential.

31:44 – 32:09

Siva Rajamani: Yeah, I think with AI, there’s an opportunity for web apps professionals to truly deliver to the promise of the function, which is to truly be the strategic thought partner to the Crow to help drive revenue results through optimizations and predictability and creating leverage for crows. And so I think of again, if you think of the rev ops, they were meant to be the architect.

32:09 – 32:33

Siva Rajamani: Yeah. But today they’re really being plumbers right. And so the evolution in the next few years is you will start to see revenue, revenue, operations professionals really become revenue architects for the company. And they’ll increase the importance of that function and the role for the overall company and what results they drive for the company.

32:34 – 32:58

Sophie Buonassisi: You can certainly see that. And actually, number one, kind of look back in sight, the number one insight with hindsight 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.

32:58 – 33:08

Sophie Buonassisi: And you recently actually ran a survey of over 400 rev ops professionals. What were some of the most surprising data points that came out of that for you?

33:08 – 33:50

Siva Rajamani: I think one of the most surprising ones was on, you know, teams that have tried AI with more like a bolt on AI, as we call it, 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 the guy. Right? So, a situation where somebody who’s actually put in something additional work, to try out AI, but not put it put the entire effort in architecting it the right way, just did a bolt on AI and of being less satisfied than actually not doing anything at all.

33:50 – 34:13

Siva Rajamani: So so this has been one of our I mean, biggest surprises, right? Like in terms of how we think about it. And that’s true because if you think about the overall, function and if you think of the AI 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.

34:13 – 34:37

Siva Rajamani: Yeah. With AI today, you know, all of us use AI to 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%.

34:37 – 35:01

Siva Rajamani: The data that’s there is not fully accurate. And then whatever the data is, there also doesn’t there’s no additional context that you’re providing. So if you really were to just bolt on AI to any of your internal systems, CRM is an example. It is going to give you accelerated nonsense, right? Like so basically you’re not going to get you’re not going to get any insights out of it.

35:01 – 35:24

Siva Rajamani: 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 going to get magical insights, and then all you get is, you know, something that seems like inside, but it’s not. And you have to now go clean up the mess. So that’s the situation that we’re seeing with the, you know, revenue operations professional and that.

35:24 – 35:27

Siva Rajamani: So that was a very interesting thing that came out of that survey.

35:27 – 35:34

Sophie Buonassisi: So is the solution then to that, to not leverage both on AI and simply leverage AI, native AI.

35:35 – 35:57

Siva Rajamani: So I think the thing is really is to going back to where the role needs to evolve to, which is the revenue architect role, right? Like you need to set the foundations. Right. And so what that what does that mean. So there’s obviously 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.

35:57 – 36:20

Siva Rajamani: And for that you have to do a bunch of different things. And there’s lots of different ways that you could do that. For example, use unstructured data to drive a lot of the data points that are not filled in in your CRM, for example. There’s obviously you need a structure, the date, time of the, you know, record because things keep evolving.

36:20 – 36:47

Siva Rajamani: If you think of the data that’s there in any of the systems, CRM or its point in time data, it tells you what’s the situation today. It doesn’t tell you what what’s 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 to be able to then, you know, generate insights on top.

36:47 – 37:08

Siva Rajamani: 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 set up before you could put on AI and accelerate insights in the next best actions and everything else that hits the company drive revenue growth.

37:08 – 37:28

Sophie Buonassisi: That completely makes sense. And I mean, you really tackling it from a holistic side. You mentioned at the beginning that you decided to solve this problem for you. Use the word community. And that really is what you’re doing now. You’re actually elevating a role. You’re actually creating the solution. But it’s much more holistic than a tool for for commission.

37:28 – 37:57

Sophie Buonassisi: 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, 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 your your pairing that overall with their careers. How do you kind of, as a founder handling such a kind of precarious and and sensitive topic.

37:57 – 38:18

Sophie Buonassisi: How do you find that you’ve been able to actually 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.

38:18 – 38:41

Siva Rajamani: Absolutely, I think so, which is why I think we don’t take our work for granted. You know, we are investing a lot, you know, because business models are evolving. For example, if you think of new companies, there’s a lot of usage based billing and consumption based pricing. We didn’t talk about pricing, actually. So I think of pricing is a very important complementary aspect to the entire commissions.

38:41 – 39:02

Siva Rajamani: And so all of these are interlinked. You know, pricing is interlinked to coders. And then 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 comp plan calculation. That’s probably the easiest part, right?

39:02 – 39:33

Siva Rajamani: 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 where it’s pricing, territories, quotas, commissions, they’re all rules heavy. But there are also exceptions. Every there’s always exception to every rule. And so you need to understand where and why those exceptions are happening and model it as part of your, you know, a tool that you create.

39:33 – 39:45

Siva Rajamani: Because that’s when you can truly automate this whole process and drive the results that you want, both for, you know, administrators and drive ops and finance, as well as to the ultimate users who are the sales teams.

39:45 – 39:47

Sophie Buonassisi: Can you give us an example of that?

39:47 – 40:13

Siva Rajamani: So for example, you could think of pricing, right? Like so in enterprise software again, you would have seen scenarios where, you know, there’s a seamless price, but there’s a particular prospect who might have gotten a discount at a particular point in time with a V, another prospect, and there could be more context associated with it. Right? This could be a different prospect in a different vertical.

40:13 – 40:34

Siva Rajamani: And potentially their margins may not be as much as the other company in a different industry. There might be a much more fast growing logo. So you want to optimize for getting that logo. There could be a situation where, you know it’s quarter end and so you want to drive, you know, revenue closure. So there’s a lot of different contexts.

40:34 – 41:03

Siva Rajamani: And so there’s exceptions that you’re taking 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 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, because there was one rep who, you know, went on a maternity leave and had worked almost 80% of the deal.

41:03 – 41:24

Siva Rajamani: And you want to make sure you know that person’s in incentivize as well. So what do you do there? Do you now just break the commission’s into half or you do, you know, increase the pie so that, you know, there’s enough motivation for the new rep coming into drive closure. So there’s always exceptions that you create for every rule.

41:24 – 41:42

Siva Rajamani: You could have paid out commissions, but there could be a situation where there’s one particular customer you never ended up collecting. You paid out commissions on bookings. But then there is the collections ratio. Now the collections ratio could be driven by a bad sale collection. History could just be driven by the company, you know, going out of business.

41:42 – 42:06

Siva Rajamani: So what do you do there? Right. There is an exception that you need. So all of these are exceptions that happen. But there’s a pattern that you could disappear out of those. 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.

42:06 – 42:22

Sophie Buonassisi: So 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 ease. Let’s talk about AI. How are you yourself first as an organization leveraging at every stage?

42:22 – 42:48

Siva Rajamani: Yeah, I think obviously like most other enterprise software companies, you are betting big on AI as a transformational change coming into the industry. And personally, for me, you know, the last 18 months have been probably the most busiest, I would say, because, you know, it’s really helped, you know, get me back into the weeds and really help me get super hands on.

42:48 – 43:18

Siva Rajamani: So I’m very thankful for that, for that. And so some of the ways I use AI, for example, is certainly, today, if you think of a stage, my sales teams, my customer success teams have hundreds of calls every week. Previously, it was not practical for me to get insights out of these calls. I mean, you could do at a individual call level, but at scale to look at the same call and decipher different insights.

43:18 – 43:45

Siva Rajamani: That was not possible. And today, with the help of AI and you could really make it happen, right? Like you could understand the same set of calls and see what are the points of objections that we need to better handle from a sales standpoint, what are the what’s the feedback that’s coming in from a product that helps us, you know, get better from a product and roadmap standpoint.

43:46 – 44:24

Siva Rajamani: So the same calls can decipher different insights. You could also start to generate insights at scale. Of course, there’s a little bit of tooling that needs to be done on top to be able to architect it. But you know, you could start to derive insights, for example. And we build we build something in-house for it that helps us, you know, tell us for deals that have a certain kind of buyer at a certain stage in the revenue process, what’s the level of conversion rates and how much of an increase is the conversion rates if that persona were to be there?

44:24 – 44:52

Siva Rajamani: Right. And this is something that you can analyze at scale without bothering your apps to fill it on CRM, to say, hey, yeah, you know, there was this persona that came on board in this particular stage. There’s also something that you could see things that have evolved over time in terms of like what was something that seemed like a base two quarters previous, you know, before, but now has changed.

44:52 – 45:15

Siva Rajamani: Say, for example, there was a particular competitor, you know, what were your win rates that you were looking at, if the competitor was mentioned in your initial calls? These are we later calls. Right click again. All of these things were just very anecdotal information that you could get previously. But today, there’s a little bit of work that you have to do.

45:15 – 45:39

Siva Rajamani: And, you know, that’s something that we’ve built in terms of tooling. But with that tooling you could really go into accurate insights. And so which is why I said you’d have to first build the foundation. Yeah. To be able to get to that insights. But once you build the foundation or you know, there will be certainly providers who you could buy it from, you know, you would be able to generate insights that helps you take next best actions.

45:39 – 46:10

Siva Rajamani: Because at the end of the day, why are we looking at all of these insights? Right. Like all of this is to help be more agile, competitive and ultimately drive the value that we want to drive in the market with our customers. So so it’s been super 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 industry for new product research.

46:10 – 46:27

Siva Rajamani: 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, in that pursuit, you know, there’s a bunch of things that I’ve used for. So at least from a secondary research standpoint.

46:27 – 46:47

Sophie Buonassisi: Very cool. So it sounds like you’re doing a lot of data aggregation, pattern matching, outlier action and next steps to from that. Do you leverage AI much for your personal kind of productivity right now? You know, you are an extremely busy person. You’re leading every stage. The founder and CEO, how are you actually managing your time and leveraging AI?

46:47 – 46:54

Siva Rajamani: I think AI has really made me more, I would say productive, but also more busy sometimes.

46:54 – 46:55

Sophie Buonassisi: Yes.

46:55 – 47:38

Siva Rajamani: Because, the way I think about this is there’s just so many things to learn. And it feels like now, a kid in the candy store kind of situation, there’s just lots of things then. So without you trying to actually be, you know, so involved, you just get consumed with a lot of areas. And so what I’ve tried to now do is ensure, I get my 6 or 7 hours of sleep because being fully active is important for you to leverage AI the most, in my opinion, because this a ton of context switching that you will need to do while you know, working, giving a task to AI and then speaking to your

47:38 – 48:03

Siva Rajamani: team and then coming back to see, you know, what’s done. And you know, there’s there’s always context switching in leadership. But I think with AI it’s just accelerated. Yeah. And so yes, so today I’ve never believed in having like, you know, personal assistant, not in, you know, having like, a chief of staff kind of teams.

48:03 – 48:14

Siva Rajamani: I know there’s a lot of leverage through those teams, but I think with AI, you know, you could really get all of the benefits of those without having, you know, necessarily people in those roles.

48:14 – 48:29

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

48:29 – 48:30

Siva Rajamani: Absolutely.

48:30 – 48:35

Sophie Buonassisi: And you mentioned a couple of times and aspirations for every stage. What’s next for every stage.

48:35 – 49:02

Siva Rajamani: Yeah. So so as I said, I think with commissions, you know, we’ve really been able to, you know, help companies drive the behavior and performance of their sales teams. But there’s few other parts that are connected to commissions, as it told you. So there’s one on the territory and coda and capacity management side. So we launched our product for our, you know, territory and Coda management last year.

49:02 – 49:44

Siva Rajamani: Yeah. So that’s been a very important addition for companies to think of how to manage commissions. It’s not just commissions, 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 cpq configure price in code. So the way I think about this is increasingly going to become a very important part of 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?

49:44 – 49:44

Sophie Buonassisi: Right.

49:44 – 50:05

Siva Rajamani: 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 if commissions where the carrot cpq is kind of the stick in some sense, it ensures you get the right discipline and the right kind of revenue.

50:05 – 50:33

Siva Rajamani: And so both of these are connected, and there’s obviously a lot of opportunity with the, you know, coating. Because today, again, it’s a broken experience for a lot of the sales teams. Sales reps spend inordinate amount of time creating codes. It’s not value for their time, especially for those, you know, top reps. And there’s today a lot of opportunity with AI to accelerate code creation, right.

50:33 – 50:51

Siva Rajamani: So if you think of code creation, there’s a lot of context from call recordings. There’s context obviously from your CRM, emails, etc. you could use a lot of that context to create the code without having to, you know, do anything from their end. Right?

50:51 – 50:52

Sophie Buonassisi: Right.

50:52 – 51:20

Siva Rajamani: And it’s not just that. Now with that, you could also then nudge your, you know, the layer that’s in the middle to say, hey, you know what? Typically for these kind of deals. Some of our, your other peers also tend to add a support package. Do you also want to add that as part of your code, like nudge them to the kind of, you know, revenue structure that you want, right?

51:20 – 51:46

Siva Rajamani: It’s 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 intention of the company and the action that the rep takes are both linked. So that’s the vision. And so we’ve launched Cpq and we have aspirations to go further in to help.

51:46 – 51:50

Siva Rajamani: As I said, revenue operations professionals become truly revenue architects.

51:50 – 52:08

Sophie Buonassisi: 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 cruise. What you’re seeing.

52:08 – 52:33

Siva Rajamani: I think 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 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 class after a proof of concept, then that doesn’t mean that, you know, you pay out commissions 100% on the sign up, right?

52:33 – 53:02

Siva Rajamani: So you want to make sure, 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, you know, the prospect continues to be your customer. 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 something where you also have additional breaks at the end of one year or something of that sort.

53:02 – 53:27

Siva Rajamani: That’s increasingly relevant in consumption based, you know, pricing where, you might have gotten a lower number to get your feet in, but you want to see what happens if the company expands them. You want also, you know, incentivize the rep for the sale. And just see, you know, what actions are taken in the first 12 months.

53:27 – 53:42

Siva Rajamani: 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, you will see the right actions.

53:42 – 53:50

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

53:51 – 54:00

Siva Rajamani: Absolutely. And which is why you have, you know, different structures in different companies. It it has to tie back to the overall goals of the company here.

54:01 – 54:11

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

54:11 – 54:39

Siva Rajamani: I think that’s a great thing. And and that is day to day, you know, things are evolving rapidly. So it’s 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 that you don’t change things drastically when you end the six months, right? Like what? You need some level of stability for people to drive, for you to push this kind of behavior on reps.

54:39 – 55:08

Siva Rajamani: If you keep changing things, people are not going to be sure of what you want them to do and just creates confusion. So you could also achieve agility by still keeping a 12 month comp plan by evolving your coda structures, right? So there’s different ways you could still achieve agility while keeping it well. One plan there could be short term incentives that you could leverage for a particular quarter.

55:08 – 55:34

Siva Rajamani: Additionally. So there’s multiple mechanisms to achieve agility. But again, again flows back to what your goals are. If you think your goals will evolve six months down the line, it might be better for you to structure your plan at this point. Fully, fully knowing well that you know you will change some structures of the plan depending on what the market situation is.

55:34 – 55:35

Siva Rajamani: Six constructed in.

55:35 – 55:47

Sophie Buonassisi: Perfect 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?

55:47 – 56:14

Siva Rajamani: Historically before I was I was an entrepreneur. Before that I was a person. I was a consultant, right. And as a management consultant, I got an opportunity to, you know, work on some deals where there was a, you know, M&A deals and pretty much in every single deal. What I saw was the highest earning person in the company was not the CEO was like a enterprise, a who was, you know, who sold like a really massive deal.

56:14 – 56:24

Siva Rajamani: And, you know, ultimately, you know, was making commissions off that. So I think your best day should probably make more than a CEO. So that’s really what I think.

56:24 – 56:28

Sophie Buonassisi: I love it. Well, it will be very excited by that news.

56:28 – 56:40

Siva Rajamani: They should be. I mean they’ve deserved what you know, how they the reason why they’re making more is because they’ve contributed so much value to the company. And so yeah, I think that should be the case.

56:40 – 56:45

Sophie Buonassisi: Amazing. And if people want to follow along you in every stage is journey. Where can they find you?

56:45 – 57:06

Siva Rajamani: Yeah, I’m pretty active on LinkedIn, so I do share a lot of my thoughts, learnings from, you know, both personal learnings from, you know, things that I’ve learned over the years, but also from, you know, advising a lot of customers today on what are the things that are some of the customers are doing well and things that we could all learn from.

57:06 – 57:12

Siva Rajamani: So LinkedIn is a great place. I’m fairly active and yeah, Twitter is also the other place.

57:12 – 57:18

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

57:18 – 57:20

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

57:20 – 57:22

Sophie Buonassisi: Absolutely.

Sophie Buonassisi

Sophie Buonassisi is the SVP of Marketing at media company GTMnow and its venture firm, GTMfund. She oversees all aspects of media, marketing, and community engagement. Sophie leads the GTMnow editorial team, producing content exploring the behind the scenes on the go-to-market strategies responsible for companies’ growth. GTMnow highlights the strategies, along with the stories from the top 1% of GTM executives, VCs, and founders behind the strategies and companies.