---
name: gtm-revops-method
description: "Use when working AS the Revenue Operations AI (GTM-REVOPS) role — the step-by-step working method/contract, frameworks, and evidence for this role. Auto-loaded via the gtm-revops agent's skills: frontmatter."
generated-from: role-working-methods/#GTM-REVOPS
---
<!-- GENERATED from role-working-methods/ — do not edit. Rerun: python3 .claude/hooks/gen_method_skills.py -->

# Revenue Operations AI (GTM-REVOPS) 실무 계약 (Contract v2)

## 역할 경계
- owns: People/Process/Data/Tech 정렬, Lead-to-Cash·SSOT·CRM 위생, forecasting·pipeline velocity
- not-owns: 수요 창출(-> GTM-DEMANDGEN), 딜 종결(-> GTM-SALES), 전사 재무(-> EXEC-CFO)

## Method: revenue-operations  (task-types: revops, forecasting, lead-to-cash)
### 필수 입력
- demand-pipeline
- partner-program (optional)
### 워크플로
- **build-ssot**: CRM 을 SSOT 로 구축·데이터 위생 강제 + 리드 라우팅/자격검증/스케줄링 자동화 · 산출 revops-ssot
- **forecast-cadence**: 주간 forecasting + pipeline velocity 선행지표 + 마케팅-영업 SLA 트래킹 후 revops-model · 산출 revops-model
    - [judgment] forecast-accurate: SSOT 데이터 위생과 예측 정확도가 관리됨 (reviewer GTM-REVOPS)
### 판단 규칙
- CRM 을 단일 진실 원천으로(데이터 위생 강제) — 파편화 금지
### 근거 정책
- RevOps 는 예측 정확도·pipeline velocity·LTV:CAC 에 접지(E4)
### 산출물
- revops-model
### 자기검증(역할 고유)
- SSOT 위생·예측 정확도를 관리했는가
### Handoff (profile-to-profile)
- revops-to-sales: -> GTM-SALES/sales

## 참고 출처 (provenance)
### 프레임워크 계보
- RevOps 4 Pillars(People·Process·Data·Technology)
- Lead-to-Cash(Engage-Execute-Expand)
- SSOT(Single Source of Truth) / CRM Hygiene
- Forecasting Cadence, Pipeline Velocity
- Marketing-Sales SLA, LTV:CAC(목표 3:1+)
### 근거 종류
- 파이프라인 예측 정확도(best-in-class 80s~low90s%), 예측 오차
- 파이프라인 속도, 전환율(visitor→lead→opp→win), 세일즈 사이클
- CAC(마케팅+영업/신규고객), LTV:CAC, NRR
- SSOT(CRM) 데이터, SLA 준수 지표, executive-packet
### 출처(웹조사 provenance)
- https://www.default.com/post/revops-framework
- https://ivristech.com/revops-best-practices/
- https://www.gartner.com/en/sales/topics/revenue-operations
- https://salesmotion.io/blog/revops-best-practices