lead-routing

3. Which territory does this belong to? (Territory assignment)

→ Evaluate geography, industry, company size, product interest

→ Assign territory

4. Which rep within the territory? (Assignment logic)

→ Round-robin, weighted, skills-based, or load-balanced

→ Assign owner

5. Is the assigned rep available? (Availability check)

→ Yes: Assign and notify

→ No: Route to backup or queue with SLA escalation

### Routing Models

| Model | How It Works | Best For | Watch Out For |
|-------|-------------|----------|---------------|
| **Geographic** | Route by region/country/city | Field sales with territories | Unbalanced territories |
| **Named Account** | Route to account owner | ABM, enterprise sales | New accounts fall through |
| **Round-Robin** | Rotate evenly across reps | Inside sales, equal territories | Doesn't account for capacity |
| **Weighted Round-Robin** | Rotate with weighting (e.g., senior rep gets 2x) | Mixed-tenure teams | Complex to maintain |
| **Skills-Based** | Route by product knowledge, language, vertical expertise | Multi-product, multi-lingual | Bottlenecks on specialists |
| **Load-Balanced** | Route based on current capacity | High-volume teams | Requires real-time capacity data |
| **Hybrid** | Territory first → round-robin within territory | Most B2B SaaS teams | More routing rules to maintain |

---

## Round-Robin Design

### Basic Round-Robin

Rotate leads evenly across a pool of reps:

Counter = 0

Reps = [Alice, Bob, Carol, David]

Lead 1 → Reps[0 % 4] = Alice (counter → 1)

Lead 2 → Reps[1 % 4] = Bob (counter → 2)

Lead 3 → Reps[2 % 4] = Carol (counter → 3)

Lead 4 → Reps[3 % 4] = David (counter → 4)

Lead 5 → Reps[4 % 4] = Alice (counter → 5)

### Weighted Round-Robin

Assign weights to reps (e.g., senior rep handles more, ramping rep handles fewer):

> *Illustrative example. Configure weights based on rep capacity, ramp status, and current quota attainment.*

| Rep | Weight | Share |
|-----|--------|-------|
| Alice (senior) | 3 | 37.5% |
| Bob (mid) | 2 | 25% |
| Carol (mid) | 2 | 25% |
| David (ramping) | 1 | 12.5% |

Implementation: Expand the rotation list proportionally:
`[Alice, Alice, Alice, Bob, Bob, Carol, Carol, David]`

### Round-Robin with Availability

Add availability checks before assignment:

Get next rep from rotation

→ Check: Is rep on OOO / vacation?

→ Yes: Skip, advance counter

→ Check: Has rep exceeded daily lead cap?

→ Yes: Skip, advance counter

→ Check: Is current time within rep's working hours?

→ Yes: Assign

→ No: Assign to queue, schedule assignment for next business hour

### Common Round-Robin Problems

| Problem | Symptom | Fix |
|---------|---------|-----|
| **Cherry-picking** | Reps grab "good" leads, leave others | Route directly to owner, not to shared queue |
| **Queue rot** | Leads sit in queue untouched | SLA timer + auto-reassignment |
| **Uneven distribution** | One rep gets more leads | Audit counter logic; check for timezone/filter issues |
| **New rep flooding** | Ramping rep gets same volume as veteran | Use weighted round-robin during ramp |
| **Timezone gaps** | Leads arrive outside business hours with no owner | Time-aware routing or follow-the-sun model |

---

## Territory Design

### Territory Variables

| Variable | Examples | Complexity |
|----------|---------|-----------|
| **Geography** | Country, region, city, postcode | Low |
| **Industry/Vertical** | SaaS, Healthcare, Financial Services | Low-Medium |
| **Company Size** | SMB (<100), Mid-Market (100-1,000), Enterprise (1,000+) | Low |
| **Product/Solution** | Product A vs Product B; platform vs point solution | Medium |
| **Named Accounts** | Strategic accounts assigned to specific reps | Medium |
| **Hybrid** | Geography × Size × Industry | High |

### Territory Balance Metrics

Check quarterly:
- **Pipeline per territory**: Should be ±10-15% of median across territories (Fullcast territory planning research, 2024-2025)
- **Lead volume per territory**: Even distribution within same segment
- **Win rate per territory**: Significant variance suggests territory design issue, not rep issue
- **Quota-to-pipeline ratio**: Coverage should be 1 divided by win rate (e.g. 25% win rate needs 4x, 60% needs 1.7x; Clari; Gradient Works; Fullcast, 2026). Reps starting a quarter at 3.2x+ weighted coverage hit quota 89% of the time; below 2.8x, 52%.

### Territory Assignment Methods

**Static assignment** (spreadsheet-managed):
- Pros: Simple, transparent
- Cons: Doesn't scale; manual updates; no automatic reassignment
- Best for: <10 reps, simple territories

**Rule-based assignment** (CRM automation):
- Pros: Automatic; consistent; auditable
- Cons: Rules can conflict; maintenance overhead
- Best for: 10-50 reps, moderate complexity

**Enterprise Territory Management** (Salesforce ETM or equivalent):
- Pros: Hierarchical; multi-territory assignment; forecasting integration
- Cons: Complex setup; expensive
- Best for: >50 reps, overlays, complex hierarchies

---

## Speed-to-Lead SLA Framework

### SLA Tiers

| Lead Tier | Definition | SLA (First Touch) | Escalation |
|-----------|-----------|-------------------|------------|
| **Tier 1 (Hot)** | High ICP fit + high engagement score; demo/pricing request | 5 minutes | 15 min: alert manager; 30 min: reassign |
| **Tier 2 (Warm)** | Good ICP fit + moderate engagement; content download | 1 hour | 2 hours: alert manager; 4 hours: reassign |
| **Tier 3 (Nurture)** | Low fit or low engagement | 24 hours | 48 hours: return to marketing; alert ops |
> *T1 (5-minute) threshold is research-backed: MIT (21× at 5 min), Justin Norris (10 min → 40% conversion lift), Chili Piper (instant booking → 66.7% conversion). T2 (1-hour) is backed by LeanData's MQL SLA recommendation. T3 (24-hour) represents common practitioner convention for lower-intent leads. All tiers should be calibrated to your team capacity and lead volume.*

### SLA Tracking Fields

| Field | Type | Purpose |
|-------|------|------