Overview
- Skill Key
- 1kalin/afrexai-sales-compensation
- Author
- 1kalin
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/1kalin/afrexai-sales-compensation
- Latest Commit SHA
- 8305564665f1799778a4cff15139241f878ab56f
Sales Compensation Plan Designer
Stars
0
Installs
0
Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 Afrexai Sales Compensation 技能。 若已安装,则直接安装 Afrexai Sales Compensation 技能。
# 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 Ra...
# Sales Compensation Plan Designer Design, audit, and optimize sales comp plans that drive the right behavior. Covers AE, SDR, CSM, SE, Channel, and VP-level plan architectures with 2026 benchmarks. ## What's Inside - **Role-specific OTE and split benchmarks** across 10 industries - **Quota setting methodology** — bottom-up capacity model, not top-down guesswork - **Accelerator/decelerator curve templates** with rate multipliers - **Plan cost modeling** — bear/base/bull scenarios before you launch - **10-point annual audit checklist** with scoring interpretation - **SPIF design framework** for short-term behavioral nudges - **Clawback provisions** — standard terms that protect without alienating - **AI-era adjustments** — how AI agents change SDR comp, ramp times, and quotas ## Who It's For - Revenue leaders designing or overhauling comp plans - Sales ops teams modeling plan costs and coverage ratios - Founders setting up their first sales comp structure - CFOs auditing sales efficiency and CAC payback ## Quick Start Tell your agent: *"Review our current sales comp plan using the sales compensation skill"* Or: *"Design a comp plan for a mid-market AE role with $180K OTE"* ## 2026 Industry Benchmarks Included SaaS, Fintech, Healthcare IT, Cybersecurity, AI/ML, Legal Tech, Construction Tech, Manufacturing, Professional Services, Real Estate Tech. --- **Get your full industry AI strategy pack →** [afrexai-cto.github.io/context-packs](https://afrexai-cto.github.io/context-packs/) ($47/pack) **Calculate your AI revenue leak →** [afrexai-cto.github.io/ai-revenue-calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) **Configure your AI agent workforce →** [afrexai-cto.github.io/agent-setup](https://afrexai-cto.github.io/agent-setup/) Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) 🖤💛
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