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sales-operations

sales-operations

github.com/dengineproblemMarketing & growth91 installs
Repository

About sales-operations

A sales operations skill covering sales process design, CRM administration, forecasting, pipeline and performance analytics, deal desk operations, and territory planning. It is intended for teams structuring and reviewing sales operations, with YAML examples for processes and metrics.

Key features

  1. 01Sales stage and process design
  2. 02CRM data model administration
  3. 03Forecast categories and criteria
  4. 04Pipeline and performance metrics
  5. 05Deal approval and territory models

Use cases

  1. 01Defining sales stages and ownership
  2. 02Structuring CRM lead fields
  3. 03Reviewing pipeline and forecast accuracy
  4. 04Setting deal approvals and territory models

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/dengineproblem/agents-monorepo --skill sales-operations

After installing, type/sales-operationsin Claude Code to confirm it loaded.

Details

From the project README

Sales Operations Expert

Operational excellence in sales process design, systems administration, and analytics.

Sales Process Design

sales_stages:
  stage_0_prospecting:
    name: "Prospecting"
    owner: "SDR"
    probability: "0%"
    activities:
      - "Account research"
      - "Contact identification"
      - "Initial outreach"
    exit_criteria:
      - "Meeting scheduled"
      - "Interest confirmed"
    required_fields:
      - "Lead source"
      - "ICP score"

  stage_1_discovery:
    name: "Discovery"
    owner: "AE"
    probability: "10%"
    activities:
      - "Discovery call"
      - "Needs assessment"
      - "Stakeholder mapping"
    exit_criteria:
      - "Pain identified and quantified"
      - "Budget range confirmed"
      - "Timeline established"
      - "Key stakeholders identified"
    required_fields:
      - "Primary contact"
      - "Problem statement"
      - "Budget range"
      - "Expected close date"

  stage_2_qualification:
    name: "Qualification"
    owner: "AE"
    probability: "25%"
    activities:
      - "MEDDIC completion"
      - "Technical fit assessment"
      - "Champion development"
    exit_criteria:
      - "MEDDIC 80% complete"
      - "Technical requirements documented"
      - "Champion identified"
      - "Competition mapped"
    required_fields:
      - "Decision criteria"
      - "Decision process"
      - "Competitors"
      - "Champion name"

  stage_3_demo:
    name: "Demo/Evaluation"
    owner: "AE + SE"
    probability: "50%"
    activities:
      - "Product demonstration"
      - "Technical deep dive"
      - "POC/trial if needed"
    exit_criteria:
      - "Demo completed successfully"
      - "Technical approval received"
      - "Positive feedback documented"
    required_fields:
      - "Demo date"
      - "Attendees"
      - "Technical requirements"
      - "POC scope (if applicable)"

  stage_4_proposal:
    name: "Proposal"
    owner: "AE"
    probability: "75%"
    activities:
      - "Proposal creation"
      - "Pricing presentation"
      - "Contract review"
    exit_criteria:
      - "Proposal delivered"
      - "Pricing discussed"
      - "No major objections"
    required_fields:
      - "Proposal sent date"
      - "Proposed amount"
      - "Contract terms"
      - "Discount (if any)"

  stage_5_negotiation:
    name: "Negotiation"
    owner: "AE"
    probability: "90%"
    activities:
      - "Term negotiation"
      - "Legal review"
      - "Final approvals"
    exit_criteria:
      - "Terms agreed"
      - "Legal approved"
      - "Signature pending"
    required_fields:
      - "Final contract"
      - "Expected signature date"
      - "Approvers"

  stage_6_closed_won:
    name: "Closed Won"
    probability: "100%"
    required_fields:
      - "Signed contract"
      - "Start date"
      - "Implementation owner"

CRM Management

crm_administration:
  data_model:
    objects:
      lead:
        purpose: "Pre-qualified prospects"
        key_fields:
          - "Name, Company, Email"
          - "Lead source"
          - "Lead score"
          - "Status"
        lifecycle: "Create → Qualify → Convert to Contact/Opp"

      contact:
        purpose: "Individual people"
        key_fields:
          - "Name, Title, Email"
          - "Account relationship"
          - "Role in deals"
        relationships: "Account, Opportunities"

      account:
        purpose: "Companies"
        key_fields:
          - "Name, Industry, Size"
          - "ICP score"
          - "Owner"
          - "Tier"
        relationships: "Contacts, Opportunities"

      opportunity:
        purpose: "Potential deals"
        key_fields:
          - "Name, Amount, Stage"
          - "Close date"
          - "Probability"
          - "Owner"
        relationships: "Account, Contacts, Products"

  data_hygiene:
    rules:
      duplicate_prevention:
        - "Email uniqueness on Contacts"
        - "Domain matching for Accounts"
        - "Automated merge suggestions"

      required_fields:
        - "Enforce by stage"
        - "Validation rules"
        - "Picklist standardization"

      data_quality:
        - "Weekly duplicate reports"
        - "Monthly enrichment updates"
        - "Quarterly data audits"

  automation_rules:
    lead_routing:
      criteria:
        - "Territory (geography)"
        - "Company size"
        - "Lead score"
        - "Round robin for overflow"
      sla: "5 minutes to assignment"

    opportunity_creation:
      trigger: "Lead converted"
      actions:
        - "Create opportunity"
        - "Copy MEDDIC fields"
        - "Assign to AE"
        - "Create tasks"

    stage_progression:
      validation:
        - "Required fields complete"
        - "Exit criteria met"
        - "Manager approval (if needed)"

Forecasting

forecast_methodology:
  categories:
    commit:
      definition: "Will close this period"
      confidence: ">90%"
      criteria:
        - "Verbal yes"
        - "Contract in legal"
        - "No blockers"
      weighting: "100%"

    best_case:
      definition: "Could close with effort"
      confidence: "60-90%"
      criteria:
        - "Proposal accepted"
        - "Negotiating terms"
        - "Timeline aligned"
      weighting: "70%"

    pipeline:
      definition: "May close this period"
      confidence: "30-60%"
      criteria:
        - "Active evaluation"
        - "Budget confirmed"
        - "Possible timeline"
      weighting: "40%"

    upside:
      definition: "Low probability this period"
      confidence: "<30%"
      criteria:
        - "Early stage"
        - "Timeline uncertain"
        - "Budget not confirmed"
      weighting: "10%"

  forecast_calculation:
    weighted: |
      Forecast =
        (Commit × 100%) +
        (Best Case × 70%) +
        (Pipeline × 40%) +
        (Upside × 10%)

    coverage: |
      Coverage Ratio = Total Pipeline / Quota
      Target: 3-4x coverage

  forecast_cadence:
    weekly:
      - "Rep submits forecast (Monday)"
      - "Manager review (Tuesday)"
      - "Leadership call (Wednesday)"
      - "Update actions (Thursday-Friday)"

    monthly:
      - "Week 1: Forecast accuracy review"
      - "Week 2: Mid-month adjust"
      - "Week 3: Final push planning"
      - "Week 4: Close month"

  accuracy_metrics:
    calculation: "Actual / Forecast"
    targets:
      acceptable: "85-115%"
      good: "90-110%"
      excellent: "95-105%"
    tracking: "Month over month trend"

Pipeline Analytics

pipeline_metrics:
  volume:
    total_pipeline: "Sum of all open opportunities"
    new_pipeline: "Created this period"
    pipeline_growth: "(Current - Previous) / Previous"

  velocity:
    formula: |
      (# Opps × Win Rate × Avg Deal Size) / Sales Cycle
    components:
      opportunities: "Count of qualified opps"
      win_rate: "Won / (Won + Lost)"
      deal_size: "Average closed won"
      cycle_time: "Days from creation to close"

  conversion:
    stage_conversion: "Moved to next stage / Started in stage"
    lead_to_opp: "Opportunities / Leads"
    opp_to_won: "Won / All closed"

  quality:
    average_deal_size: "Sum(Amount) / Count(Won)"
    discount_rate: "Average discount given"
    sales_cycle: "Average days to close"

pipeline_analysis:
  by_segment:
    - "By rep/team"
    - "By territory"
    - "By product"
    - "By source"

  trending:
    - "Pipeline created over time"
    - "Stage velocity trends"
    - "Win rate by cohort"
    - "Deal size trends"

  health_checks:
    - "Aging deals (no activity 14+ days)"
    - "Stalled opportunities"
    - "Close date slippage"
    - "Coverage by segment"

Deal Desk Operations

deal_desk:
  approval_matrix:
    standard_deal:
      criteria: "Within guidelines"
      approver: "AE manager"
      turnaround: "Same day"

    non_standard_pricing:
      criteria: "10-20% discount"
      approver: "Sales Director"
      turnaround: "24 hours"

    strategic_deal:
      criteria: ">20% discount or custom terms"
      approver: "VP Sales + Finance"
      turnaround: "48 hours"

    enterprise_deal:
      criteria: ">$100K or multi-year"
      approver: "CRO"
      turnaround: "48-72 hours"

  pricing_guidelines:
    discount_authority:
      ae: "Up to 10%"
      manager: "Up to 15%"
      director: "Up to 20%"
      vp: "Up to 25%"
      cro: "Unlimited"

    discount_justification:
      required_for:
        - "Any discount >10%"
        - "Custom payment terms"
        - "Multi-year deals"
      documentation:
        - "Competitive pressure"
        - "Strategic value"
        - "Reference potential"

  contract_management:
    templates:
      - "Standard subscription"
      - "Enterprise license"
      - "Professional services"
      - "NDA"
      - "MSA + Order Form"

    legal_review:
      standard: "Pre-approved, no review"
      modified: "1-2 business days"
      custom: "3-5 business days"

    signature_process:
      - "DocuSign/PandaDoc"
      - "Automated routing"
      - "Counter-signature SLA"
      - "Contract storage"

Performance Analytics

sales_dashboards:
  executive:
    metrics:
      - "Revenue vs target"
      - "Pipeline coverage"
      - "Win rate trend"
      - "Forecast accuracy"
      - "Headcount vs plan"
    refresh: "Daily"

  manager:
    metrics:
      - "Team attainment"
      - "Rep pipeline health"
      - "Activity metrics"
      - "Deal progression"
      - "Coaching opportunities"
    refresh: "Daily"

  individual:
    metrics:
      - "Personal attainment"
      - "Pipeline status"
      - "Activity tracking"
      - "Deal stages"
      - "Commission forecast"
    refresh: "Real-time"

rep_performance:
  quota_attainment:
    calculation: "Closed Won / Quota"
    targets:
      ramp: "50% (months 1-3)"
      full: "100%"
      stretch: "120%"

  activity_metrics:
    calls: "Dials per day"
    meetings: "Meetings held"
    proposals: "Proposals sent"
    demos: "Demos delivered"

  quality_metrics:
    win_rate: "Won / All closed"
    avg_deal_size: "Revenue / Won deals"
    sales_cycle: "Days to close"
    discount_rate: "Average discount"

  leading_indicators:
    pipeline_coverage: "Pipeline / Remaining quota"
    opportunity_creation: "New opps per month"
    stage_progression: "Velocity through stages"

Territory & Quota

territory_management:
  models:
    geographic:
      basis: "Region, country, state"
      pros: "Simple, clear ownership"
      cons: "Uneven potential"

    named_accounts:
      basis: "Specific account list"
      pros: "Focus on key accounts"
      cons: "Coverage gaps"

    segment:
      basis: "Company size, industry"
      pros: "Specialization"
      cons: "Complexity"

    hybrid:
      basis: "Combination of above"
      pros: "Balanced coverage"
      cons: "Administration overhead"

  balancing:
    factors:
      - "Total addressable market"
      - "Account potential"
      - "Historical performance"
      - "Rep capacity"
      - "Travel requirements"

    metrics:
      - "Accounts per rep"
      - "Potential revenue"
      - "Win rate by territory"

quota_setting:
  methodology:
    bottom_up:
      calculation: "Sum of rep quotas"
      basis: "Territory potential"

    top_down:
      calculation: "Company target / Reps"
      basis: "Growth objectives"

    blended:
      calculation: "Average of both"
      adjustments: "Territory factors"

  factors:
    - "Historical performance"
    - "Territory potential"
    - "Market growth"
    - "Product launches"
    - "Ramp time"
    - "Seasonality"

  quota_types:
    bookings: "New ARR"
    revenue: "Recognized revenue"
    pipeline: "Pipeline generated"
    activity: "Meetings, demos"

Лучшие практики

  1. Process before tools — определи процесс, потом автоматизируй
  2. Data quality first — мусор на входе = мусор на выходе
  3. Inspect what you expect — регулярные ревью pipeline
  4. Forecast accuracy focus — точность > оптимизм
  5. Enable, don't police — помогай продавать, не усложняй
  6. Continuous improvement — итерации на основе данных

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