multiAI Summary Pending
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.
3,556 stars
byopenclaw
Installation
Claude Code / Cursor / Codex
$curl -o ~/.claude/skills/afrexai-sales-compensation/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/1kalin/afrexai-sales-compensation/SKILL.md"
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/afrexai-sales-compensation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Sales Compensation Plan Designer Compares
| Feature / Agent | Sales Compensation Plan Designer | Standard Approach |
|---|---|---|
| Platform Support | multi | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Which AI agents support this skill?
This skill is compatible with multi.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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: <18 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 (<15%?) 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](https://afrexai-cto.github.io/context-packs/) — 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/**