lead-routing
Intelligently distributes sales leads, automatically routing based on AI scoring, regional attribution, round-robin rules, and load balancing to improve team response speed and conversion rates.
npx skills add claude-office-skills/skills --skill lead-routingBefore / After Comparison
1 组Manually checking the geographical location and product requirements of new leads, and assigning them one by one based on sales representatives' expertise and current workload. This often leads to omissions, long response times, and uneven distribution.
Automatically and intelligently distributes leads based on AI scoring, regional affiliation, round-robin rules, and real-time workload. Routing is completed in seconds, ensuring balanced team workload and rapid response to potential customers.
lead-routing
Lead Routing
Intelligent lead assignment and routing system with AI-powered scoring, territory mapping, round-robin distribution, and workload balancing. Based on n8n's HubSpot/Salesforce automation templates.
Overview
This skill covers:
-
Lead scoring and qualification
-
Territory-based routing
-
Round-robin distribution
-
Workload balancing
-
SLA monitoring and escalation
Routing Strategies
1. Rule-Based Routing
routing_rules:
# By Company Size
- name: "Enterprise Routing"
condition:
company_size: ">= 500"
OR:
annual_revenue: ">= $10M"
assign_to: "Enterprise Team"
priority: high
sla: 1_hour
- name: "Mid-Market Routing"
condition:
company_size: "100-499"
assign_to: "Mid-Market Team"
priority: medium
sla: 4_hours
- name: "SMB Routing"
condition:
company_size: "< 100"
assign_to: "SMB Team"
priority: standard
sla: 24_hours
# By Geography
- name: "APAC Routing"
condition:
country: ["China", "Japan", "Singapore", "Australia"]
assign_to: "APAC Team"
timezone_aware: true
- name: "EMEA Routing"
condition:
country: ["UK", "Germany", "France", "Netherlands"]
assign_to: "EMEA Team"
- name: "Americas Routing"
condition:
country: ["US", "Canada", "Brazil", "Mexico"]
assign_to: "Americas Team"
# By Industry
- name: "Healthcare Specialist"
condition:
industry: ["Healthcare", "Pharmaceuticals", "Medical Devices"]
assign_to: "Healthcare Sales"
- name: "Finance Specialist"
condition:
industry: ["Banking", "Insurance", "FinTech"]
assign_to: "Financial Services Sales"
2. Round-Robin Distribution
round_robin_config:
team: "SMB Sales"
members:
- name: Alice
capacity: 100%
max_leads_per_day: 20
- name: Bob
capacity: 100%
max_leads_per_day: 20
- name: Carol
capacity: 50% # Part-time
max_leads_per_day: 10
rules:
distribution: weighted # or equal
skip_if:
- out_of_office: true
- at_capacity: true
reset: daily
tracking:
log_assignments: true
balance_check: hourly
Distribution Algorithm:
┌─────────────────────────────────────────────────────────────┐
│ ROUND-ROBIN LOGIC │
├─────────────────────────────────────────────────────────────┤
│ │
│ 1. New lead arrives │
│ │ │
│ ▼ │
│ 2. Check team availability │
│ - Filter out: OOO, at capacity, off-hours │
│ │ │
│ ▼ │
│ 3. Calculate weighted position │
│ - Current assignments today │
│ - Capacity percentage │
│ - Last assignment time │
│ │ │
│ ▼ │
│ 4. Assign to rep with lowest weighted score │
│ │ │
│ ▼ │
│ 5. Update tracking, notify rep │
│ │
└─────────────────────────────────────────────────────────────┘
3. AI-Powered Lead Scoring
ai_scoring:
provider: openai
model: gpt-4
input_factors:
demographic:
- company_size
- industry
- job_title
- location
firmographic:
- annual_revenue
- employee_count
- funding_stage
- tech_stack
behavioral:
- pages_visited
- content_downloads
- email_engagement
- demo_requests
fit_score:
- icp_match_percentage
- competitor_usage
- budget_authority
scoring_prompt: |
Score this lead from 0-100 based on:
Our ICP (Ideal Customer Profile):
- B2B SaaS companies
- 50-500 employees
- Series A or later
- Using {competitor} or {similar_tool}
Lead Data:
{lead_data}
Return JSON:
{
"score": 0-100,
"fit_score": 0-100,
"intent_score": 0-100,
"tier": "A/B/C/D",
"reasoning": "...",
"recommended_action": "...",
"routing_suggestion": "..."
}
tier_thresholds:
A: 80-100 # Hot lead, immediate follow-up
B: 60-79 # Qualified, standard follow-up
C: 40-59 # Nurture, marketing sequence
D: 0-39 # Low priority, long-term nurture
4. Territory Mapping
territory_map:
north_america:
west:
states: [CA, WA, OR, NV, AZ, CO, UT]
owner: "West Coast Team"
reps: [Alice, Bob]
central:
states: [TX, IL, OH, MI, MN, WI]
owner: "Central Team"
reps: [Carol, David]
east:
states: [NY, MA, PA, FL, GA, NC]
owner: "East Coast Team"
reps: [Eve, Frank]
international:
emea:
countries: [UK, DE, FR, NL, ES, IT]
owner: "EMEA Team"
timezone: "Europe/London"
apac:
countries: [JP, SG, AU, KR, IN]
owner: "APAC Team"
timezone: "Asia/Tokyo"
overlap_resolution:
# When lead matches multiple territories
priority_order:
1: named_account_owner # If account already has owner
2: industry_specialist # If industry requires specialist
3: geography # Default to geography
5. Workload Balancing
workload_balancer:
check_frequency: hourly
metrics_tracked:
- current_open_leads
- leads_assigned_today
- leads_assigned_this_week
- average_response_time
- conversion_rate
balance_rules:
max_variance: 20% # Max difference between reps
rebalance_trigger:
- variance > max_variance
- rep_at_capacity
- rep_underperforming
rebalance_actions:
- pause_assignments: for_overloaded_rep
- increase_weight: for_underloaded_rep
- notify_manager: when_rebalancing
capacity_management:
per_rep:
max_open_leads: 50
max_new_per_day: 15
max_new_per_week: 60
team_level:
overflow_queue: true
overflow_notify: sales_manager
escalation_threshold: 2_hours
Workflow Implementation
Complete Lead Routing Workflow
workflow: "Intelligent Lead Router"
trigger:
- type: hubspot_contact_created
- type: form_submission
- type: api_webhook
steps:
1. enrich_lead:
providers: [clearbit, zoominfo]
fields:
- company_size
- industry
- revenue
- location
- linkedin_url
2. score_lead:
method: ai_scoring
store_result:
hubspot_property: lead_score
3. determine_tier:
A_tier: score >= 80
B_tier: score >= 60
C_tier: score >= 40
D_tier: score < 40
4. apply_routing_rules:
sequence:
- check: named_account_owner
- check: industry_specialist
- check: territory_match
- check: round_robin_availability
5. assign_owner:
hubspot:
update_contact:
hubspot_owner_id: "{selected_owner_id}"
lead_status: "New"
lead_tier: "{tier}"
routing_reason: "{routing_logic}"
6. create_task:
hubspot:
type: CALL
subject: "Follow up: New {tier} lead - {company}"
due_date: "{sla_deadline}"
priority: "{priority_based_on_tier}"
notes: |
Lead Score: {score}
Routing Reason: {routing_reason}
Key Info: {summary}
7. notify_owner:
slack_dm:
message: |
🎯 *New Lead Assigned*
**{contact_name}** at **{company}**
Score: {score} ({tier} Tier)
📞 SLA: Respond within {sla_time}
Quick actions:
• [View in HubSpot]({hubspot_link})
• [LinkedIn]({linkedin_url})
• [Schedule Call]({calendly_link})
8. start_sla_timer:
deadline: "{sla_deadline}"
escalation_path:
- 50%_elapsed: reminder_to_owner
- 80%_elapsed: notify_manager
- 100%_elapsed: reassign + alert
SLA Management
sla_tiers:
tier_a:
response_time: 1_hour
escalation_path:
- 30min: slack_reminder
- 45min: manager_alert
- 60min: auto_reassign
tier_b:
response_time: 4_hours
escalation_path:
- 2h: slack_reminder
- 3h: manager_alert
- 4h: auto_reassign
tier_c:
response_time: 24_hours
escalation_path:
- 12h: slack_reminder
- 20h: manager_alert
- 24h: move_to_queue
sla_reporting:
metrics:
- response_time_avg
- response_time_p90
- sla_compliance_rate
- escalation_count
report_frequency: weekly
recipients: [sales_manager, ops_manager]
Reporting Dashboard
# Lead Routing Report - {Week}
## Distribution Summary
| Rep | Assigned | Responded | Avg Response | SLA Met |
|-----|----------|-----------|--------------|---------|
| Alice | 45 | 43 | 1.2h | 96% |
| Bob | 42 | 40 | 1.8h | 90% |
| Carol | 38 | 38 | 0.8h | 100% |
| **Total** | **125** | **121** | **1.3h** | **95%** |
## By Tier
| Tier | Count | Avg Score | Converted | Conv Rate |
|------|-------|-----------|-----------|-----------|
| A | 25 | 87 | 12 | 48% |
| B | 45 | 68 | 15 | 33% |
| C | 35 | 52 | 5 | 14% |
| D | 20 | 28 | 1 | 5% |
## Routing Breakdown
- By Territory: 60%
- By Industry: 25%
- Round Robin: 15%
## Issues
- 3 leads waited >SLA (reassigned)
- Alice at 95% capacity (monitor)
- No coverage for Healthcare vertical (gap)
## Recommendations
1. Hire Healthcare specialist
2. Increase Bob's training (response time)
3. Adjust A-tier threshold to 85 (too many false positives)
Output Example
Request: "Route this lead: John Smith, CTO at TechCorp (500 employees, SF, SaaS)"
Output:
# Lead Routing Decision
## Lead Profile
- **Name**: John Smith
- **Title**: CTO
- **Company**: TechCorp
- **Size**: 500 employees
- **Location**: San Francisco, CA
- **Industry**: SaaS
## AI Scoring
```json
{
"score": 85,
"fit_score": 90,
"intent_score": 80,
"tier": "A",
"reasoning": "Strong ICP fit - CTO at 500-person SaaS company in our target market. High authority buyer.",
"recommended_action": "Immediate outreach - high-value prospect"
}
Routing Decision
Assigned to: Alice Chen (Enterprise West)
Routing Logic:
-
✅ Territory: San Francisco → West Coast
-
✅ Company Size: 500 → Enterprise tier
-
✅ Industry: SaaS → No specialist needed
-
✅ Availability: Alice has capacity (18/20 today)
Action Items Created
Task: Follow up call
Due: 1 hour (Tier A SLA)
-
Priority: High
Slack Notification: Sent to Alice
SLA Timer: Started (1h countdown)
Recommended Outreach
Subject: Quick question about {pain_point} at TechCorp
Hi John,
Noticed TechCorp is scaling fast - congrats on the growth.
CTOs at similar SaaS companies often tell us {common_challenge}.
Would a 15-min call this week make sense to see if we can help?
[Calendly Link]
---
*Lead Routing Skill - Part of Claude Office Skills*
Weekly Installs304Repositoryclaude-office-s…s/skillsGitHub Stars35First SeenMar 9, 2026Security AuditsGen Agent Trust HubPassSocketPassSnykPassInstalled onclaude-code259opencode121github-copilot120kimi-cli118gemini-cli118amp118
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