2466 Sales 2212658b

# Sales Skills

**Total Skills:** 47

## Risk Distribution

| Risk Level | Count |
|------------|-------|
| 🔴 Critical | 28 |
| 🟡 High | 4 |
| 🔵 Medium | 8 |
| 🟢 Low | 7 |

---

## Skills

| # | Skill ID | Risk | Job to be Done |
|---|----------|------|----------------|
| 1 | `elg_co_sell_trigger` | 🔴 Critical | Initiates and manages co-selling workflows with partners for joint opportunities. |
| 2 | `elg_deal_registration` | 🔴 Critical | Manages partner deal registration workflow including submission, approval, protection, and expiration tracking. |
| 3 | `elg_referral_program` | 🔴 Critical | Manages partner referral programs including lead tracking, commission calculation, payout processing, and referral analytics. |
| 4 | `elg_nearbound_signal` | 🔴 Critical | Identifies partner-influenced opportunities from ecosystem signals including overlapping accounts, shared contacts, and partner activity data. |
| 5 | `elg_marketplace_integration` | 🔴 Critical | Manages marketplace listings and tracks integration-driven growth. |
| 6 | `elg_partner_mapping` | 🔴 Critical | Maps accounts between partners to identify overlaps and co-selling opportunities. |
| 7 | `elg_tech_partner_finder` | 🔴 Critical | Identifies and evaluates potential technology partners based on product synergies, market overlap, and integration opportunities. |
| 8 | `finops_arr_waterfall` | 🔴 Critical | Analyzes ARR movements including new, expansion, contraction, and churn for revenue visibility |
| 9 | `finops_investor_metrics` | 🔴 Critical | Compiles key SaaS metrics for investor reporting, board meetings, and fundraising |
| 10 | `cursor_rules/azure-pipelines` | 🟢 Low | This guide provides opinionated, actionable best practices for writing secure, performant, and maintainable Azure Pipelines using YAML, focusing on modern CI/CD patterns and common pitfalls. |
| 11 | `cursor_rules/seaborn` | 🟢 Low | This guide defines best practices for using Seaborn in Python for data visualization, emphasizing modern, reproducible, and performant approaches in AI/ML pipelines. |
| 12 | `cursor_rules/gitlab-ci` | 🟢 Low | This guide provides opinionated, actionable best practices for structuring, optimizing, and securing GitLab CI/CD pipelines, focusing on modern patterns and avoiding common pitfalls. |
| 13 | `cursor_rules/databricks` | 🟢 Low | Definitive guidelines for developing robust, performant, and secure applications and data pipelines on Databricks using modern best practices and native services. |
| 14 | `cursor_rules/lightgbm` | 🟢 Low | This guide provides opinionated, actionable best practices for using LightGBM in production-grade Python ML pipelines, focusing on performance, reproducibility, and maintainability. |
| 15 | `cursor_rules/jenkins` | 🟢 Low | Definitive guidelines for writing robust, maintainable, and secure Jenkins Pipelines using modern best practices. |
| 16 | `cursor_rules/github-actions` | 🟢 Low | This guide provides definitive, opinionated best practices for writing robust, secure, and performant GitHub Actions workflows. Follow these rules to build maintainable CI/CD pipelines. |
| 17 | `plg_pql_scoring` | 🔴 Critical | Identifies and scores Product-Qualified Leads (PQLs) based on product usage patterns and engagement signals. |
| 18 | `plg_self_serve_expansion` | 🔵 Medium | Identifies and enables account expansion opportunities through seat additions, plan upgrades, and add-on purchases without sales involvement. |
| 19 | `ai_conversation_intelligence` | 🟡 High | Analyzes sales and support conversations for insights, coaching, and deal intelligence. |
| 20 | `ai_meeting_intelligence` | 🔴 Critical | Analyzes meeting recordings and transcripts to extract insights, action items, and deal intelligence. |
| 21 | `revops_opportunity_scoring` | 🔴 Critical | Scores opportunities using AI-powered analysis of engagement signals, firmographics, and historical patterns. |
| 22 | `revops_territory_planner` | 🟡 High | Designs balanced sales territories optimizing for coverage, capacity, and revenue potential. |
| 23 | `revops_deal_inspection` | 🔴 Critical | Conducts thorough deal reviews with MEDDPICC analysis, risk assessment, and actionable coaching. |
| 24 | `revops_cpq_quote_generator` | 🔴 Critical | Generates accurate, compliant quotes with intelligent product configuration, pricing rules, and approval workflows. |
| 25 | `revops_forecast_intelligence` | 🟡 High | AI-powered revenue forecasting with deal-level predictions, risk analysis, and scenario modeling. |
| 26 | `revops_pricing_guidance` | 🔴 Critical | Provides real-time pricing guidance based on deal context, competitive dynamics, and win rate optimization. |
| 27 | `revops_multi_thread_tracker` | 🔴 Critical | Tracks and optimizes multi-stakeholder engagement to reduce single-threading risk. |
| 28 | `revops_sales_coaching` | 🔵 Medium | Provides AI-powered coaching insights based on call analysis, deal patterns, and performance metrics. |
| 29 | `revops_deal_velocity` | 🔴 Critical | Analyzes and optimizes deal velocity to accelerate sales cycles and improve conversion rates. |
| 30 | `revops_lead_routing` | 🔴 Critical | Routes leads by territory, skill, and capacity for optimal conversion using AI-powered matching. |
| 31 | `revops_quota_setter` | 🔵 Medium | Sets fair, achievable quotas using historical performance, market data, and territory potential. |
| 32 | `revops_renewals_handoff` | 🔵 Medium | Orchestrates seamless handoff from sales to customer success and manages renewal pipeline. |
| 33 | `revops_stage_duration` | 🔴 Critical | Analyzes deal stage durations to identify bottlenecks, optimize sales process, and improve forecasting. |
| 34 | `revops_meeting_scheduler` | 🔵 Medium | Schedules optimal meeting times considering availability, timezone, deal priority, and meeting type. |
| 35 | `revops_pipeline_health` | 🔴 Critical | Monitors pipeline health, identifies at-risk deals, and triggers proactive interventions. |
| 36 | `revops_lead_qualification` | 🔴 Critical | Qualifies leads using BANT, MEDDIC, or custom frameworks, combining firmographic and behavioral signals. |
| 37 | `revops_commit_accuracy` | 🔴 Critical | Tracks and improves forecast commit accuracy by analyzing historical patterns and deal signals. |
| 38 | `revops_handoff_orchestration` | 🟡 High | Orchestrates seamless handoffs between Marketing, Sales, and Customer Success teams. |
| 39 | `mon_discount_optimizer` | 🔴 Critical | Optimizes discount strategies to maximize conversion while protecting margins |
| 40 | `mon_commitment_tracker` | 🔵 Medium | Tracks minimum commitments, consumption vs commitment, and true-up obligations |
| 41 | `mon_contract_value_tracker` | 🔴 Critical | Tracks total contract value, recognized revenue, and remaining obligations |
| 42 | `mon_pricing_optimization` | 🔵 Medium | Analyzes pricing effectiveness and recommends optimizations for revenue growth. |
| 43 | `mon_upgrade_trigger` | 🔴 Critical | Identifies optimal moments to present upgrade offers and executes upgrade flows. |
| 44 | `boyce_multi_gtm_orchestrator` | 🔵 Medium | Orchestrates multiple GTM motions (PLG + Sales) in parallel. Based on Dave Boyce's FREEMIUM framework (Chapter 13): Run your multi-GTM business like a lean revenue factory. |
| 45 | `boyce_product_led_sales` | 🔴 Critical | Hybrid PLG+Sales motion using product usage signals to generate and qualify sales pipeline. Based on Dave Boyce's FREEMIUM framework (Chapters 14-15): 'To maximize Enterprise Sales, you need a self-service happy path.' |
| 46 | `plgf_paywall_upgrade_cro` | 🔴 Critical | Conversion rate optimization framework for paywalls including feature locks, usage limits, trial expiry, copy frameworks, and mobile patterns. |
| 47 | `scientific/pytdc` | 🔴 Critical | Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction. |

---

[← Back to Directory](../directory.md)