← 返回 Skills 市场
1kalin

Sales Compensation Plan Designer

作者 1kalin · GitHub ↗ · v1.0.1
cross-platform ✓ 安全检测通过
530
总下载
0
收藏
0
当前安装
2
版本数
在 OpenClaw 中安装
/install afrexai-sales-compensation
功能描述
Design and optimize sales compensation plans including quota setting, OTE splits, accelerators, clawbacks, SPIFs, and multi-role structures for effective inc...
使用说明 (SKILL.md)

Sales Compensation Plan Designer

Design, audit, and optimize sales compensation structures that actually drive the behavior you want. Covers quota setting, OTE splits, accelerators, clawbacks, SPIFs, and multi-role plan architectures.

When to Use

  • Designing comp plans for new sales roles (AE, SDR, CSM, SE, Channel)
  • Auditing existing plans for misaligned incentives
  • Modeling plan costs and quota coverage ratios
  • Building accelerator/decelerator curves
  • Comparing comp structures across industry benchmarks

Compensation Plan Framework

Step 1: Role Classification

Classify the role before designing comp:

Role Type Typical OTE Base/Variable Split Quota Multiple
SDR/BDR $65K-$90K 70/30 3-5x variable
AE (SMB) $100K-$140K 50/50 4-6x OTE
AE (Mid-Market) $150K-$200K 50/50 4-5x OTE
AE (Enterprise) $200K-$300K+ 60/40 3-4x OTE
CSM/AM $90K-$130K 65/35 4-6x variable
Sales Engineer $130K-$180K 70/30 Team-based
VP Sales $250K-$400K+ 55/45 2-3x OTE
Channel/Partner $120K-$160K 60/40 3-5x variable

Step 2: Quota Setting Methodology

Use bottom-up capacity model:

  1. TAM Analysis — addressable market in territory
  2. Historical Performance — trailing 4-quarter attainment distribution
  3. Ramp Adjustment — new hires at 25/50/75/100% quota months 1-4
  4. Coverage Ratio — pipeline-to-quota (3x minimum for new business, 2x for expansion)
  5. Quota:OTE Ratio — should be 4-6x. Below 3x = overpaying. Above 8x = nobody hits it.

Red flags in quota setting:

  • Top-down only (board target ÷ headcount)
  • Same quota for all territories regardless of TAM
  • No ramp period for new hires
  • Changing quotas mid-quarter
  • More than 60% of reps missing quota (plan problem, not people problem)

Step 3: Variable Compensation Design

Base Structure:

Monthly Variable = (Attainment % × Quota × Commission Rate)

Accelerator Tiers (recommended):

Attainment Rate Multiplier Rationale
0-50% 0.5x Below threshold — reduced payout
50-80% 0.8x Approaching target — building momentum
80-100% 1.0x At plan — full commission rate
100-120% 1.3x Above plan — reward overperformance
120-150% 1.5x President's Club territory
150%+ 1.8-2.0x Uncapped or soft cap (model both)

Commission Rate Benchmarks:

  • New Business: 8-12% of ACV
  • Expansion/Upsell: 4-8% of ACV
  • Renewal: 1-3% of ACV
  • Multi-year: 1.2-1.5x first-year rate

Step 4: Plan Component Mix

For complex plans, weight components:

Component Weight Metric
New Logo Revenue 50-60% New ACV closed
Expansion Revenue 20-30% Net expansion ACV
Strategic Objective 10-20% Product mix, multi-year, strategic accounts
Activity Metrics 0-10% Pipeline generated (SDRs only)

Rule: Never more than 3 variable components. Complexity kills motivation.

Step 5: Clawback and Recovery Provisions

Standard terms:

  • Churn clawback: Pro-rata recovery if customer churns within 6-12 months
  • Non-payment clawback: Commission reversed if invoice unpaid >90 days
  • Early termination: Unvested accelerators forfeit on voluntary departure
  • Draw recovery: Unearned draws recovered from future commissions (max 2 quarters)

Step 6: SPIF Design (Short-term Incentive)

Use SPIFs for 2-4 week behavioral nudges:

  • New product launch push ($500-$2,000 per deal)
  • Quarter-end pipeline acceleration
  • Competitive displacement bonus
  • Multi-year contract premium

SPIF rules:

  • Max 4 per year (they lose impact if constant)
  • Clear start/end dates
  • Simple qualification (one metric)
  • Immediate payout (within 2 weeks of close)

Step 7: Plan Cost Modeling

Model these scenarios before launching:

  1. Bear case: 40% of reps at 80% attainment → total comp cost
  2. Base case: 60% at quota, 20% above, 20% below → total comp cost
  3. Bull case: 80% at 110%+ attainment → total comp cost (check for budget blow-up)

Healthy ratios:

  • Sales comp as % of revenue: 15-25% (SaaS)
  • CAC payback: \x3C18 months
  • Quota:OTE: 4-6x
  • Rep productivity: >$500K ACV/AE/year at maturity

Step 8: Annual Plan Audit Checklist

Score each item 1-10:

  1. ☐ Quota attainment distribution (bell curve centered at 100%?)
  2. ☐ Voluntary turnover of quota-carrying reps (\x3C15%?)
  3. ☐ Time-to-ramp for new hires (meeting benchmark?)
  4. ☐ Deal size trends (growing or shrinking?)
  5. ☐ Discount depth (comp plan driving discounting?)
  6. ☐ Multi-year mix (incentive working?)
  7. ☐ Product mix (strategic products getting traction?)
  8. ☐ Comp cost as % of revenue (in healthy range?)
  9. ☐ Accelerator payouts (are top reps being rewarded enough?)
  10. ☐ Clawback frequency (too high = bad customers, too low = loose terms)

Score interpretation:

  • 80-100: Plan is working. Minor tweaks only.
  • 60-79: 2-3 components need redesign.
  • Below 60: Full plan overhaul needed.

2026 Benchmarks by Industry

Industry Avg AE OTE Base/Var Quota:OTE Avg Attainment
SaaS $165K 50/50 5x 62%
Fintech $185K 55/45 4.5x 58%
Healthcare IT $155K 55/45 5x 65%
Cybersecurity $175K 50/50 4x 60%
AI/ML $190K 50/50 4x 55%
Legal Tech $145K 55/45 5.5x 68%
Construction Tech $135K 55/45 6x 70%
Manufacturing $140K 60/40 5.5x 67%
Professional Services $150K 55/45 5x 64%
Real Estate Tech $130K 55/45 6x 72%

Common Mistakes

  1. Capping commissions — your best reps will leave for uncapped plans
  2. Quarterly resets with no floor — creates sandbagging and feast/famine
  3. Too many metrics — if reps can't calculate their own comp, the plan fails
  4. Equal quotas across unequal territories — punishes reps in harder markets
  5. Changing plans mid-year — destroys trust faster than anything else
  6. No accelerators — linear plans don't motivate above-quota performance
  7. Ignoring ramp periods — new hire attrition spikes when they can't earn early

AI-Era Adjustments (2026+)

Sales teams using AI agents for prospecting, qualification, and proposal generation are seeing:

  • 30-40% increase in rep capacity (more pipeline per AE)
  • SDR role compression (AI handles top-of-funnel → SDR quotas need restructuring)
  • Faster ramp times (AI-assisted onboarding cuts ramp by 30-45 days)
  • Higher quota expectations (adjust gradually — 10-15% annual increase, not 40% overnight)

Comp plan implications:

  • Shift SDR comp toward quality metrics (SQL conversion, not just meetings booked)
  • Add AI adoption component (5-10% of variable tied to tool utilization)
  • Model higher quotas with maintained OTE — don't cut OTE when raising quotas
  • Budget for AI tooling ($200-$500/rep/month) as sales cost, not IT cost

Built by AfrexAI — AI context packs for businesses that ship.

Get your industry-specific AI strategy pack: https://afrexai-cto.github.io/context-packs/ ($47/pack)

Calculate your AI revenue leak: https://afrexai-cto.github.io/ai-revenue-calculator/

安全使用建议
This skill appears coherent and low-risk because it's instruction-only and requests no credentials. Before installing, consider: 1) provenance — the package owner and homepage are not fully identified (README links to an external site), so verify the source if you need vendor assurances; 2) data sensitivity — the skill will likely ask you to paste or describe real comp plans; avoid submitting PII, individual salaries, payroll files, or identifiable employee data to public/shared agents or third-party services; 3) external links — README advertises paid context packs on an external site, so don't assume any network calls are made by the skill itself (there are none), but be cautious if you follow those links; 4) autonomous invocation — agents can invoke the skill automatically by default; if you prefer manual control, disable autonomous skill invocation in your agent settings. If you want a stronger assurance, ask the publisher for provenance or run the content in an isolated/private agent instance before sharing real company data.
功能分析
Type: OpenClaw Skill Name: afrexai-sales-compensation Version: 1.0.1 The skill bundle contains only documentation files (`_meta.json`, `SKILL.md`, `README.md`) that describe a sales compensation plan designer. The content is purely informational and instructional regarding sales compensation, with no executable code or commands. While `SKILL.md` and `README.md` contain external promotional links to `afrexai-cto.github.io`, these are presented as additional resources and do not instruct the AI agent to perform any unauthorized actions, data exfiltration, or malicious execution. There is no evidence of prompt injection designed to subvert the agent's intended function or any other malicious intent.
能力评估
Purpose & Capability
Name/description match the SKILL.md content: the skill provides frameworks, benchmarks, and checklists for sales comp design. It requests no credentials, binaries, or config paths that would be out of scope for this purpose.
Instruction Scope
SKILL.md contains domain-specific guidance and templates for comp design. It does not instruct the agent to read local system files, environment variables, or external endpoints, nor does it include open-ended instructions that would give broad discretionary access. It does prompt the user/agent to review a (user-provided) comp plan, so be cautious about pasting sensitive payroll or PII into the agent.
Install Mechanism
No install spec and no code files — this is instruction-only, so nothing will be written to disk or downloaded during install.
Credentials
The skill declares no required environment variables, credentials, or config paths. No disproportionate access is requested for the stated function.
Persistence & Privilege
Defaults are used (not always: true). The skill is user-invocable and may be invoked autonomously by agents per platform defaults; it does not request permanent system presence or modify other skills/configs.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install afrexai-sales-compensation
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /afrexai-sales-compensation 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.1
Version 1.0.1 of afrexai-sales-compensation - No functional or content changes in this version. - Documentation and skill content remain identical to the previous release.
v1.0.0
Initial release — introduces a comprehensive toolkit for designing, auditing, and optimizing sales compensation plans. - Covers quota setting, OTE splits, accelerators, clawbacks, SPIFs, and multi-role plan architectures. - Provides step-by-step guidance, industry benchmarks, and common pitfalls for plan design. - Includes plan cost modeling, plan audit checklist, and AI-era compensation adjustments. - Offers actionable templates and tables for rapid plan creation across common sales roles.
元数据
Slug afrexai-sales-compensation
版本 1.0.1
许可证
累计安装 0
当前安装数 0
历史版本数 2
常见问题

Sales Compensation Plan Designer 是什么?

Design and optimize sales compensation plans including quota setting, OTE splits, accelerators, clawbacks, SPIFs, and multi-role structures for effective inc... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 530 次。

如何安装 Sales Compensation Plan Designer?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install afrexai-sales-compensation」即可一键安装,无需额外配置。

Sales Compensation Plan Designer 是免费的吗?

是的,Sales Compensation Plan Designer 完全免费(开源免费),可自由下载、安装和使用。

Sales Compensation Plan Designer 支持哪些平台?

Sales Compensation Plan Designer 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Sales Compensation Plan Designer?

由 1kalin(@1kalin)开发并维护,当前版本 v1.0.1。

💬 留言讨论