Intelligent lead assignment and routing - AI-powered scoring, territory mapping, round-robin distribution, and workload balancing
npx skills add https://github.com/claude-office-skills/skills --skill 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.
This skill covers:
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"
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 │
│ │
└─────────────────────────────────────────────────────────────┘
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
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
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: "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_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]
# 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)
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
{
"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**:
1. ✅ Territory: San Francisco → West Coast
2. ✅ Company Size: 500 → Enterprise tier
3. ✅ Industry: SaaS → No specialist needed
4. ✅ Availability: Alice has capacity (18/20 today)
## Action Items Created
1. **Task**: Follow up call
- Due: 1 hour (Tier A SLA)
- Priority: High
2. **Slack Notification**: Sent to Alice
3. **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*
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take claude-office-skills/lead-routing from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.