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Business & Growth Skills - Claude Code Guidance

This guide covers the 5 production-ready business and growth skills and their Python automation tools.

Business & Growth Skills Overview

Available Skills:

  1. customer-success-manager/ - Customer health scoring, churn risk analysis, expansion opportunities (3 Python tools)
  2. sales-engineer/ - Technical discovery, RFP analysis, competitive positioning, POC planning (3 Python tools)
  3. revenue-operations/ - Pipeline analysis, forecast accuracy, GTM efficiency metrics (3 Python tools)

Total Tools: 9 Python automation tools, 9 knowledge bases, 19+ templates

Python Automation Tools

Customer Success Manager Tools

1. Health Score Calculator (customer-success-manager/scripts/health_score_calculator.py)

Purpose: Multi-dimensional customer health scoring with trend analysis

Features:

  • Weighted scoring across 4 dimensions (usage, engagement, support, relationship)
  • Red/Yellow/Green classification with configurable thresholds
  • Trend analysis comparing current vs previous period
  • Segment-aware benchmarking (Enterprise/Mid-Market/SMB)

Usage:

python customer-success-manager/scripts/health_score_calculator.py customer_data.json
python customer-success-manager/scripts/health_score_calculator.py customer_data.json --format json

2. Churn Risk Analyzer (customer-success-manager/scripts/churn_risk_analyzer.py)

Purpose: Identify at-risk accounts with intervention recommendations

Features:

  • Risk scoring based on behavioral signals
  • Warning signal detection and categorization
  • Tier-appropriate intervention playbooks
  • Urgency-based prioritization

Usage:

python customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json
python customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json --format json

3. Expansion Opportunity Scorer (customer-success-manager/scripts/expansion_opportunity_scorer.py)

Purpose: Identify upsell and cross-sell opportunities

Features:

  • Adoption depth analysis across product modules
  • Whitespace mapping for unused features
  • Revenue opportunity estimation
  • Priority ranking by effort and impact

Usage:

python customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json
python customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json --format json

Sales Engineer Tools

4. RFP Response Analyzer (sales-engineer/scripts/rfp_response_analyzer.py)

Purpose: Score RFP/RFI coverage and identify gaps

Features:

  • Requirement coverage scoring (Full/Partial/Planned/Gap)
  • Effort estimation per requirement
  • Gap identification with mitigation strategies
  • Overall bid/no-bid recommendation

Usage:

python sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json
python sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json --format json

5. Competitive Matrix Builder (sales-engineer/scripts/competitive_matrix_builder.py)

Purpose: Generate feature comparison matrices and competitive positioning

Features:

  • Feature-by-feature comparison matrix
  • Competitive scoring with weighted categories
  • Differentiator identification
  • Battlecard-ready output

Usage:

python sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json
python sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json --format json

6. POC Planner (sales-engineer/scripts/poc_planner.py)

Purpose: Plan proof-of-concept engagements

Features:

  • Timeline estimation based on scope
  • Resource allocation planning
  • Success criteria definition
  • Evaluation scorecard generation

Usage:

python sales-engineer/scripts/poc_planner.py poc_data.json
python sales-engineer/scripts/poc_planner.py poc_data.json --format json

Revenue Operations Tools

7. Pipeline Analyzer (revenue-operations/scripts/pipeline_analyzer.py)

Purpose: Analyze sales pipeline health and velocity

Features:

  • Coverage ratio calculation (pipeline/quota)
  • Stage conversion rate analysis
  • Sales velocity metrics (4-lever model)
  • Deal aging analysis

Usage:

python revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json
python revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json --format json

8. Forecast Accuracy Tracker (revenue-operations/scripts/forecast_accuracy_tracker.py)

Purpose: Measure and improve forecast accuracy

Features:

  • MAPE (Mean Absolute Percentage Error) calculation
  • Forecast bias detection (over/under-forecasting)
  • Period-over-period trend analysis
  • Category-level accuracy breakdown

Usage:

python revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json
python revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json --format json

9. GTM Efficiency Calculator (revenue-operations/scripts/gtm_efficiency_calculator.py)

Purpose: Calculate go-to-market efficiency metrics

Features:

  • Magic number calculation
  • LTV:CAC ratio analysis
  • CAC payback period
  • Burn multiple assessment
  • Industry benchmarking

Usage:

python revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json
python revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json --format json

Quality Standards

All business & growth Python tools must:

  • Use standard library only (no external dependencies)
  • Support both JSON and human-readable output via --format flag
  • Provide clear error messages for invalid input
  • Return appropriate exit codes
  • Process files locally (no API calls)
  • Include argparse CLI with --help support
  • Marketing: Content creation, demand generation -> ../marketing-skill/
  • Product Team: User research, feature prioritization -> ../product-team/
  • C-Level: Strategic planning -> ../c-level-advisor/
  • Engineering: Technical implementation -> ../engineering-team/

Last Updated: May 10, 2026 Skills Deployed: 5/5 business & growth skills production-ready Total Tools: 9 Python automation tools