home / skills / ncklrs / startup-os-skills / sales-ops-analyst
This skill guides revenue teams in designing CRM workflows, dashboards, and forecasting models to accelerate sales with actionable insights.
npx playbooks add skill ncklrs/startup-os-skills --skill sales-ops-analystReview the files below or copy the command above to add this skill to your agents.
---
name: sales-ops-analyst
description: Expert sales operations and analytics guidance for revenue teams. Use when designing CRM workflows, building sales dashboards, optimizing pipeline analytics, creating lead routing rules, designing territories, calculating commissions, managing data quality, building forecasting models, or integrating sales tech stack. Covers Salesforce, HubSpot, Outreach, Gong, and RevOps best practices.
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# Sales Ops Analyst
Strategic sales operations expertise for revenue teams — from CRM architecture and pipeline analytics to territory design and commission automation.
## Philosophy
Great sales ops isn't about more data. It's about **actionable insights** that accelerate revenue.
The best sales operations teams:
1. **Enable, don't police** — Make it easier for reps to do the right thing
2. **Measure what matters** — Vanity metrics create vanity pipeline
3. **Automate the mundane** — Free reps to sell, not update fields
4. **Build for scale** — Today's workaround is tomorrow's technical debt
## How This Skill Works
When invoked, apply the guidelines in `rules/` organized by:
- `crm-*` — CRM architecture, data models, hygiene practices
- `pipeline-*` — Pipeline analytics, stage definitions, velocity metrics
- `dashboard-*` — Sales reporting, metrics, visualizations
- `process-*` — Automation, workflows, approval chains
- `routing-*` — Lead routing, assignment rules, territory design
- `commission-*` — Comp plans, calculation logic, tracking
- `data-*` — Data quality, deduplication, enrichment
- `forecast-*` — Forecasting methodologies, models, accuracy
## Core Frameworks
### The RevOps Data Hierarchy
| Level | What It Measures | Used By | Update Frequency |
|-------|------------------|---------|------------------|
| **Activity** | Calls, emails, meetings | Reps, managers | Real-time |
| **Opportunity** | Deal progress, value | Reps, managers | Daily |
| **Pipeline** | Forecast, velocity | Directors, execs | Weekly |
| **Revenue** | Bookings, ARR, churn | C-suite, board | Monthly/Quarterly |
### Pipeline Velocity Formula
```
Pipeline Velocity = (# Opportunities × Win Rate × Avg Deal Size) / Sales Cycle Length
Example:
(100 opps × 25% × $50K) / 90 days = $13,889/day potential revenue
```
### The Sales Tech Stack
```
┌─────────────────────────────────────────────────────────────┐
│ ANALYTICS LAYER │
│ (BI Tools: Tableau, Looker, Power BI, Salesforce Reports) │
├─────────────────────────────────────────────────────────────┤
│ CRM LAYER │
│ (Salesforce, HubSpot, Dynamics 365) │
├──────────────────┬──────────────────┬───────────────────────┤
│ ENGAGEMENT │ INTELLIGENCE │ ENRICHMENT │
│ Outreach, Salesloft│ Gong, Chorus │ ZoomInfo, Clearbit │
├──────────────────┴──────────────────┴───────────────────────┤
│ DATA LAYER │
│ (Integrations, ETL, Data Warehouse, CDP) │
└─────────────────────────────────────────────────────────────┘
```
### Lead Scoring Matrix
| Signal Type | Examples | Weight |
|-------------|----------|--------|
| **Fit** (firmographic) | Industry, company size, tech stack | 40% |
| **Engagement** (behavioral) | Website visits, content downloads, email opens | 35% |
| **Intent** (buying signals) | Pricing page views, demo requests, competitor research | 25% |
### Territory Design Principles
```
┌─────────────────┐
│ BALANCED │
│ OPPORTUNITY │
└────────┬────────┘
│
┌───────────────────┼───────────────────┐
│ │ │
▼ ▼ ▼
┌─────────┐ ┌─────────┐ ┌─────────┐
│ Account │ │ Revenue │ │ Travel │
│ Volume │ │Potential│ │ Load │
└─────────┘ └─────────┘ └─────────┘
```
## Key Metrics Overview
| Category | Metric | Target Range | Red Flag |
|----------|--------|--------------|----------|
| **Activity** | Meetings/week/rep | 10-15 | <5 |
| **Pipeline** | Coverage ratio | 3-4x | <2x |
| **Velocity** | Avg sales cycle | Industry dependent | Growing |
| **Quality** | Win rate | 20-30% | <15% or >50% |
| **Forecast** | Accuracy | ±10% | >25% variance |
| **Data** | Duplicate rate | <5% | >10% |
## Anti-Patterns
- **Field proliferation** — Adding fields without removing unused ones
- **Report graveyard** — Dashboards no one looks at
- **Process theater** — Mandatory updates that don't drive action
- **Excel dependency** — Critical processes outside the CRM
- **Garbage in, garbage out** — No data quality governance
- **Over-automation** — Automating bad processes faster
- **Single point of failure** — Tribal knowledge in one person's head
- **Metric gaming** — Optimizing for the number, not the outcome
This skill provides expert sales operations and analytics guidance for revenue teams, focused on turning data into action. It helps design CRM architectures, optimize pipeline analytics, automate routing and commissions, and build forecasting and dashboarding best practices. Use it to reduce friction for reps, improve forecast accuracy, and scale repeatable processes.
When invoked, the skill applies a set of modular rule groups (crm, pipeline, dashboard, process, routing, commission, data, forecast) to assess and recommend changes. It inspects CRM data models, stage definitions, activity tracking, routing logic, comp calculations, and reporting needs, then produces prioritized recommendations. Outputs include configuration patterns, metric definitions, automation templates, and data-quality checks tailored to Salesforce, HubSpot, Outreach, Gong, and common RevOps stacks.
Which CRMs and tools does this skill cover?
It covers Salesforce, HubSpot, Outreach, Gong, common BI tools (Tableau, Looker, Power BI) and enrichment providers like ZoomInfo and Clearbit.
How does it improve forecasting?
It standardizes stage definitions, calculates velocity using opportunities × win rate × average deal size / cycle length, and recommends signal-driven adjustments to improve accuracy.
What metrics are most important to track?
Track activity (meetings/calls), pipeline coverage (3–4x), win rate (20–30%), sales cycle length, forecast accuracy (±10%), and duplicate rate (<5%).