Skip to main content

​
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

​
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: 
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