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

He's seen 300+ sales comp plans and 90% make the same mistake.

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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


View the Full Transcript


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.


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