How Solutions Teams Structure Compensation (Q4’25)
We analyzed how 200+ companies structure pay, incentives, and targets for Solutions teams—then compared them to AEs. Here are the headline takeaways; the full interactive cuts are available to those who contributed to the data set..
Our Findings
Pay mix skews more base-heavy than AEs. Median Presales pay mix [75:25] vs. AE [60:40]; Implementation [80:20].
Incentives aren’t only about bookings. [X%] of Presales include activation/“go-live” in the plan; [Y%] of Implementation tie pay to on-time go-live or utilization.
Mechanics are present but restrained. [Z%] report accelerators; median top multiple [1.4×] at [120%] attainment. [W%] use thresholds, typically [70%].
Team/pod targets are common. [Q%] share part of variable with AE/CSM in a pod model; median team weight [20%].
Different from AEs by design. [R%] say their mechanics (accelerators/thresholds/SPIFs) differ from AE plans, primarily to reward enablement and activation, not just bookings.
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Why this matters
Solutions pay has been a black box, and the move toward activation- and usage-based revenue makes traditional AE-style plans a poor fit. This dataset spotlights how leaders are balancing:
Enablement vs. revenue: more credit for activation and successful go-lives.
Individual vs. team outcomes: the rise of pod-shared targets with AEs/CSMs.
Simplicity vs. fairness: lighter accelerators and clearer thresholds to avoid “accidental sales comp.”
What's Inside the Analysis?
Solutions pay has been a black box, and the move toward activation- and usage-based revenue makes traditional AE-style plans a poor fit. This dataset spotlights how leaders are balancing:
Enablement vs. revenue: more credit for activation and successful go-lives.
Individual vs. team outcomes: the rise of pod-shared targets with AEs/CSMs.
Simplicity vs. fairness: lighter accelerators and clearer thresholds to avoid “accidental sales comp.”
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Why is this Only Open To Those Who Contributed?
This is not marketing copy.
Where the goal is surface-level insights to push for marketing.
As a community, we're trying to most effectively solve the data problem in our space. So we're taking a different approach.
We're trying to build the largest and most useful data set so its actually useful for teams.
We believe the best way of doing that is FOMO. If you haven't contributed to this one and are being blocked access, then next time you'll definitely contribute.
And that is a net positive for Solutioners as a whole. We will continue to unapolagetically focus on what's best for our goal at Cofom - elevating Solutions and open-sourcing what actually works.