--- name: sales-operations description: Expert sales operations covering CRM management, sales analytics, territory planning, compensation design, and process optimization. version: 1.0.0 author: Claude Skills category: sales-success tags: [sales-ops, crm, analytics, territory, compensation] --- # Sales Operations Expert-level sales operations for revenue optimization. ## Core Competencies - CRM administration - Sales analytics - Territory planning - Quota setting - Compensation design - Process optimization - Forecasting - Sales enablement ## Sales Analytics ### Key Metrics Dashboard ``` ┌─────────────────────────────────────────────────────────────┐ │ Sales Performance - [Period] │ ├─────────────────────────────────────────────────────────────┤ │ Revenue Pipeline Win Rate Cycle Time │ │ $2.4M $8.2M 28% 45 days │ │ vs Quota: 102% Coverage: 3.4x vs LQ: +3% vs LQ: -5d │ ├─────────────────────────────────────────────────────────────┤ │ PIPELINE BY STAGE │ │ Prospect: $1.2M (15%) ████ │ │ Discovery: $2.1M (26%) ███████ │ │ Demo: $2.8M (34%) █████████ │ │ Proposal: $1.5M (18%) █████ │ │ Negotiation: $0.6M (7%) ██ │ ├─────────────────────────────────────────────────────────────┤ │ REP PERFORMANCE │ │ Rep A: $520K (115%) Rep B: $480K (107%) Rep C: $420K (93%)│ └─────────────────────────────────────────────────────────────┘ ``` ### Sales Metrics Framework **Activity Metrics:** | Metric | Formula | Target | |--------|---------|--------| | Calls/Day | Total calls / Days | 50+ | | Meetings/Week | Total meetings / Weeks | 15+ | | Proposals/Month | Total proposals / Months | 8+ | **Pipeline Metrics:** | Metric | Formula | Target | |--------|---------|--------| | Pipeline Coverage | Pipeline / Quota | 3x+ | | Pipeline Velocity | Won Deals / Avg Cycle Time | - | | Stage Conversion | Stage N+1 / Stage N | Varies | **Outcome Metrics:** | Metric | Formula | Target | |--------|---------|--------| | Win Rate | Won / (Won + Lost) | 25%+ | | Average Deal Size | Revenue / Deals | $[X] | | Sales Cycle | Avg days to close | <60 | | Quota Attainment | Actual / Quota | 100%+ | ## Territory Planning ### Territory Design Principles **Balance:** - Similar opportunity potential - Comparable workload - Fair distribution **Coverage:** - Geographic proximity - Industry alignment - Account relationships **Growth:** - Room for expansion - Career progression - Market potential ### Territory Model ```markdown # Territory Plan: [Region/Segment] ## Overview - Total accounts: [Number] - Total ARR potential: $[Amount] - Rep count: [Number] ## Territory Assignment ### Territory 1: [Name] - Rep: [Name] - Accounts: [Number] - ARR Potential: $[Amount] - Named accounts: [List] - Geographic coverage: [Area] ### Territory 2: [Name] ... ## Metrics by Territory | Territory | Accounts | Potential | Quota | Coverage | |-----------|----------|-----------|-------|----------| | [T1] | X | $Y | $Z | W% | ## Rules of Engagement - Account ownership: [Rules] - Lead routing: [Rules] - Splits: [Rules] ``` ### Account Scoring ```python def score_account(account): """ Score accounts for territory assignment and prioritization """ score = 0 # Company size (0-30 points) if account['employees'] > 5000: score += 30 elif account['employees'] > 1000: score += 20 elif account['employees'] > 200: score += 10 # Industry fit (0-25 points) if account['industry'] in ['Technology', 'Finance']: score += 25 elif account['industry'] in ['Healthcare', 'Manufacturing']: score += 15 # Engagement (0-25 points) if account['website_visits'] > 10: score += 15 if account['content_downloads'] > 0: score += 10 # Intent signals (0-20 points) if account['intent_score'] > 80: score += 20 elif account['intent_score'] > 50: score += 10 return score ``` ## Quota Setting ### Quota Methodology **Top-Down:** ``` Company Revenue Target: $50M ├── Growth Rate: 30% ├── Team Capacity: 20 reps ├── Average Quota: $2.5M └── Adjustments: ±20% based on territory ``` **Bottom-Up:** ``` Account Potential Analysis: ├── Existing accounts: $30M ├── Pipeline value: $15M ├── New logo potential: $10M ├── Total: $55M └── Risk adjustment: -10% Final: $49.5M ``` ### Quota Allocation | Rep | Territory Potential | Historical | Ramp | Final Quota | |-----|---------------------|------------|------|-------------| | Rep A | $3M | 110% | Full | $2.7M | | Rep B | $2.8M | 95% | Full | $2.4M | | Rep C | $2.5M | N/A | 50% | $1.2M | ## Compensation Design ### Compensation Structure ``` TOTAL ON-TARGET EARNINGS (OTE) ├── Base Salary: 50-60% └── Variable: 40-50% ├── Commission: 80% │ ├── New Business: 60% │ └── Expansion: 40% └── Bonus: 20% ├── Quarterly accelerators └── SPIFs COMMISSION RATE ├── 0-50% quota: 0.5x rate ├── 50-100% quota: 1x rate ├── 100-150% quota: 1.5x rate └── 150%+ quota: 2x rate ``` ### Comp Plan Template ```markdown # Sales Compensation Plan: [Role] ## Plan Overview - Role: [Role Name] - OTE: $[Amount] - Base/Variable Split: [X/Y]% - Pay Period: [Frequency] ## Commission Structure ### New Business - Rate: [X]% of ACV - Accelerators: - 100-120%: 1.2x multiplier - 120%+: 1.5x multiplier ### Renewal/Expansion - Rate: [Y]% of ACV - Expansion: Same as new business - Renewal: Reduced rate ## Quota - Annual: $[Amount] - Quarterly: $[Amount] - Ramped: [If applicable] ## Payment Terms - Commission paid: [Timing] - Clawback period: [Duration] - Draw: [If applicable] ## Special Incentives - [SPIF 1]: [Details] - [SPIF 2]: [Details] ``` ## Forecasting ### Forecast Categories | Category | Definition | Weighting | |----------|------------|-----------| | Closed | Signed contract | 100% | | Commit | Verbal commit, high confidence | 90% | | Best Case | Strong opportunity, likely to close | 50% | | Pipeline | Active opportunity | 20% | | Upside | Early stage | 5% | ### Forecast Report ``` ┌─────────────────────────────────────────────────────────────┐ │ Q4 Forecast - Week 8 │ ├─────────────────────────────────────────────────────────────┤ │ Quota: $10M │ │ │ │ Category Deals Amount Weighted │ │ Closed 12 $2.4M $2.4M │ │ Commit 8 $1.8M $1.6M │ │ Best Case 15 $3.2M $1.6M │ │ Pipeline 22 $4.5M $0.9M │ │ ───────────────────────────────────────────── │ │ Weighted Total $11.9M $6.5M │ ├─────────────────────────────────────────────────────────────┤ │ Forecast: $4.0M (Closed + Commit) │ │ Upside: $5.6M (with Best Case) │ │ Gap to Quota: $6.0M │ │ Required Win Rate on Pipeline: 35% │ └─────────────────────────────────────────────────────────────┘ ``` ## Process Optimization ### Sales Process Audit ``` STAGE ANALYSIS ├── Average time in stage ├── Conversion rate ├── Drop-off reasons └── Bottleneck identification ACTIVITY ANALYSIS ├── Activities per stage ├── Activity to outcome ratio ├── Time allocation └── Best rep practices TOOL UTILIZATION ├── CRM adoption ├── Feature usage ├── Data quality └── Automation opportunities ``` ### CRM Hygiene **Data Quality Checks:** - [ ] Required fields populated - [ ] Stage dates updated - [ ] Close dates realistic - [ ] Deal amounts accurate - [ ] Contact roles assigned - [ ] Next steps documented ## Reference Materials - `references/analytics.md` - Sales analytics guide - `references/territory.md` - Territory planning - `references/compensation.md` - Comp design principles - `references/forecasting.md` - Forecasting methodology ## Scripts ```bash # Pipeline analyzer python scripts/pipeline_analyzer.py --data opportunities.csv # Territory optimizer python scripts/territory_optimizer.py --accounts accounts.csv --reps 10 # Quota calculator python scripts/quota_calculator.py --target 50000000 --reps team.csv # Forecast reporter python scripts/forecast_report.py --quarter Q4 --output report.html ```