| name | accelerating-pipeline |
| description | Use when pipeline velocity is flat or declining, win rates are below 20 percent, sales cycles are lengthening, deals are single-threaded, or lead routing is slow. Use when MQL volume is prioritized over pipeline quality, when marketing and sales define funnel stages differently, or when signal-based engagement has not replaced linear nurture drips. |
| user-invocable | true |
| metadata | {"version":"1.0.0"} |
Pipeline Accelerator
Overview
Pipeline velocity is four levers operating together: deal volume, win rate, deal size, and cycle time. A 15% improvement across all four produces a 75% velocity increase. This skill identifies the highest-leverage lever and applies AI-powered signal-based approaches to move all four.
When to Use
- Pipeline velocity is flat or declining quarter over quarter
- Win rate is below 20% overall
- Sales cycle length is increasing or exceeds 60 days
- Deals are single-threaded (one champion per opportunity)
- Lead response time exceeds 5 minutes for high-intent signals
- MQL volume is the primary marketing success metric
- Marketing and sales define pipeline stages differently
- No formal pipeline velocity measurement exists
- Lead scoring is manual, static, or nonexistent
Don't use when: You have fewer than 30 closed deals to analyze, or when the constraint is product-market fit rather than GTM execution.
Quick Reference
| Phase | Duration | Output |
|---|
| Pipeline velocity audit | Day 1-2 | Velocity, lever analysis |
| Intent-based ABM design | Day 3-5 | Account tiers, sequences |
| Signal-based engagement | Day 6-8 | Signal taxonomy, routing |
| Buying group orchestration | Day 9-10 | Coverage maps, playbook |
| Predictive lead scoring | Day 11-13 | Scoring model |
| Win rate improvement | Day 14-16 | Win/loss system |
| RevOps alignment | Day 17-19 | Dashboard, SLAs |
| AI agent deployment | Day 20-22 | Agent specs, metrics |
Core Deliverables
- Pipeline Velocity Audit -- Velocity calculation, lever analysis, conversion map
- ABM Program Design -- Account tiers, buying group maps, engagement sequences
- Signal Engagement System -- Signal taxonomy, scoring model, routing rules
- Buying Group Orchestration -- Coverage maps, role-based content, gap-filling playbook
- Lead Scoring Model -- Fit, intent, engagement layers with composite scoring
- Win Rate Playbook -- Win/loss analysis, personalization, deal acceleration
- RevOps Dashboard -- Pipeline, funnel, signal, attribution views
Common Mistakes
- Optimizing only top-of-funnel volume while ignoring other velocity levers
- Using MQL volume as success metric instead of pipeline created
- Building linear nurture drips that ignore buyer context and signal strength
- Routing all leads the same way regardless of intent level
- Single-threading deals instead of orchestrating the buying group
- Deploying AI agents without measuring baseline performance first
Integration
Feeds into: tracking-marketing-metrics, managing-marketing-ops
Refresh: Velocity weekly. Lever analysis monthly. ABM list quarterly. Lead scoring quarterly. Full system audit every 6 months.
See workflow.md for detailed phase-by-phase execution, velocity calculators, ABM templates, signal workflows, scoring architecture, and AI agent deployment plans.
