sales-ops-analyst

What this skill does

# 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