> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pylar.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Sales Territory Optimizer

> Build an AI agent that allocates territories, balances workload, and identifies growth opportunities

## Overview

A Sales Territory Optimizer agent powered by Pylar analyzes sales performance, geographic data, and account information to optimize territory allocation and identify growth opportunities.

## What the Agent Needs to Accomplish

The agent must:

* Analyze territory performance
* Balance workload across territories
* Identify growth opportunities
* Optimize territory boundaries
* Track account distribution
* Recommend territory adjustments

## How Pylar Helps

Pylar enables the agent by:

* **Unified Territory View**: Combining sales data, geographic data, and account information
* **Performance Analysis**: Real-time territory performance metrics
* **Workload Balancing**: Analyzing and optimizing rep workload
* **Growth Identification**: Identifying untapped opportunities

```mermaid theme={null}
graph LR
    subgraph "Data Sources"
        SALES[Sales Data]
        GEO[Geographic Data]
        ACCOUNTS[Account Info]
    end
    
    PYLAR[Pylar<br/>Unified Views]
    
    TOOLS[MCP Tools<br/>analyze_territories<br/>balance_workload<br/>identify_opportunities]
    
    AGENT[Territory Optimizer]
    TEAM[Sales Ops]
    
    SALES --> PYLAR
    GEO --> PYLAR
    ACCOUNTS --> PYLAR
    PYLAR --> TOOLS
    TOOLS --> AGENT
    AGENT --> TEAM
    
    style PYLAR fill:#FF4017,stroke:#CC3300,color:#fff
```

## Without Pylar vs With Pylar

### Without Pylar

**Challenges**:

* ❌ Manual territory analysis
* ❌ Complex data aggregation
* ❌ Limited visibility into territory performance
* ❌ Time-consuming optimization

**Implementation Complexity**: \~5-6 weeks

### With Pylar

**Benefits**:

* ✅ Automated territory analysis
* ✅ Real-time performance tracking
* ✅ Data-driven optimization
* ✅ Easy territory adjustments

**Implementation Complexity**: \~6-7 hours

## Step-by-Step Implementation

### Step 1: Connect Data Sources

1. **Connect CRM** (Accounts, deals, rep assignments)
2. **Connect Geographic Data** (Territory boundaries, regions)
3. **Connect Sales Performance** (Rep performance, quota data)

### Step 2: Create Territory Views

**Territory Performance View**:

```sql theme={null}
CREATE VIEW territory_performance AS
SELECT 
  t.territory_name,
  t.region,
  COUNT(DISTINCT a.account_id) as account_count,
  SUM(d.amount) as total_pipeline,
  SUM(CASE WHEN d.stage = 'Closed Won' THEN d.amount ELSE 0 END) as closed_won,
  COUNT(DISTINCT r.rep_id) as rep_count,
  AVG(r.quota_attainment) as avg_quota_attainment
FROM territories t
LEFT JOIN accounts a ON t.territory_id = a.territory_id
LEFT JOIN deals d ON a.account_id = d.account_id
LEFT JOIN reps r ON t.territory_id = r.territory_id
GROUP BY t.territory_name, t.region;
```

### Step 3: Create MCP Tools

**Tool 1: Analyze Territory Performance**

* `analyze_territory_performance(territory_name: string)`

**Tool 2: Optimize Territory Allocation**

* `optimize_territory_allocation(criteria: string)`

**Tool 3: Identify Growth Opportunities**

* `identify_growth_opportunities(region: string, min_value: number)`

**Tool 4: Balance Workload**

* `balance_workload(territory_id: string)`

## Example Agent Interactions

**User**: "Analyze territory performance in the West region"

**Agent**: "West Region Territory Analysis:

* Top Territory: California (45 accounts, \$2.1M pipeline)
* Underperforming: Nevada (12 accounts, \$300K pipeline)
* Recommendation: Redistribute 8 accounts from CA to NV
* Growth Opportunity: 15 untapped accounts in Oregon"

## Outcomes

* **Territory Balance**: 30% improvement
* **Rep Utilization**: 25% better distribution
* **Revenue Growth**: 20% increase in underperforming territories
* **Planning Efficiency**: 70% reduction in planning time

## Next Steps

* [Sales Assistant Example](/examples/sales-assistant)
* [Revenue Operations Agent Example](/examples/revenue-operations-agent)