Predictive Routing
Study Notes
| Topic |
Description |
| Predictive Routing |
AI-powered routing system that optimizes agent assignment |
| Engine |
Machine learning algorithms analyze skills, availability, and contact history |
| Purpose |
Maximize first-contact resolution and customer satisfaction |
| Activation |
Requires Premium edition and Workforce Optimization module |
| Benefit |
Reduces handle time and improves customer outcomes |
Navigation
Admin → Architect → Routing → Predictive Routing
OR
Admin → Contact Center → Routing Configuration → Enable Predictive Routing
Predictive Routing Overview
Predictive Routing is an AI-powered contact routing system that dynamically matches incoming contacts to the most suitable available agent based on multiple factors:
Key Capabilities
- Skill-based routing - Matches agent skills to contact requirements
- Historical performance - Learns from agent interaction outcomes
- Availability prediction - Anticipates agent availability and readiness
- Real-time optimization - Adjusts routing in real-time based on system state
- Omnichannel support - Works across voice, chat, email, and messaging
How It Works
- Contact arrives at system
- Contact intent and requirements analyzed
- System evaluates all available agents
- Machine learning algorithm predicts best match
- Contact routed to optimal agent
- Interaction data captured for learning
Edition & Module Requirements
| Requirement |
Details |
| Minimum Edition |
Premium Edition required |
| Module |
Workforce Optimization add-on module |
| License Type |
Agent licenses with predictive routing enabled |
| Setup |
Admin configuration in Architect |
Study Notes - Routing Factors
| Factor |
Description |
Impact |
| Agent Skills |
Capabilities and certifications |
High - Core matching criteria |
| Proficiency Level |
Skill mastery degree |
High - Affects quality |
| Availability |
Agent ready state and status |
High - Real-time factor |
| Handling Capacity |
Available slots for new contacts |
High - Prevents overload |
| Historical Performance |
Past interaction outcomes |
Medium - Learning factor |
| Queue Wait Time |
Customer wait duration |
Medium - Fairness factor |
| Contact Type |
Voice, chat, email, etc. |
High - Channel match |
| Language Proficiency |
Supported languages |
High - Communication match |
| Customer History |
Previous interaction records |
Medium - Context factor |
| Agent State |
Idle, working, after-call work |
High - Real-time factor |
Implementation Guide
Step 1: Prerequisites & Planning
- Ensure organization has Premium edition
- Purchase Workforce Optimization module
- Audit existing agent skills database
- Document required skill sets
- Review current routing rules
- Plan migration from legacy routing
- Navigate to Admin → Architect → Skills
- Create skill categories (technical, language, product)
- Define skill levels (1-5 proficiency)
- Assign skills to agents
- Establish mastery thresholds
- Document skill requirements per queue
Step 3: Enable Predictive Routing
- Go to Admin → Contact Center → Routing
- Select queue to enable predictive routing
- Enable "Predictive Routing" toggle
- Configure routing rules (optional overrides)
- Set skill matching parameters
- Define fallback routing behavior
Step 4: Testing & Validation
- Route test calls through system
- Monitor agent assignment accuracy
- Verify skill matching
- Check queue distribution
- Validate omnichannel routing
- Review abandonment rates
Step 5: Monitoring & Optimization
- Review routing analytics daily
- Monitor first-contact resolution rates
- Track agent utilization
- Measure customer satisfaction
- Optimize skill assignments
- Adjust thresholds as needed
How to Implement
| Phase |
Description |
Timeline |
| Analysis |
Audit current routing and skills |
Week 1-2 |
| Configuration |
Set up skills, queues, and rules |
Week 2-3 |
| Testing |
Validate routing logic and assignments |
Week 3-4 |
| Pilot |
Deploy to test queue with monitoring |
Week 4-6 |
| Full Rollout |
Enable across all queues |
Week 6-8 |
| Optimization |
Monitor, tune, and improve |
Ongoing |
Predictive Routing Architecture
Incoming Contact
↓
Contact Metadata Analysis
├── Contact Intent
├── Contact Type (Voice/Chat/Email)
├── Language Requirements
└── Skill Requirements
↓
Predictive Routing Engine
├── Machine Learning Models
├── Real-time Agent Analysis
├── Skill Matching Algorithm
└── Performance Prediction
↓
Agent Evaluation
├── Available Agents
├── Skill Match Score
├── Proficiency Level
├── Historical Performance
└── Queue Load Balance
↓
Optimal Agent Selection
↓
Route Contact
↓
Agent Assignment
Routing Decision Flow
Contact Arrives
↓
Extract Contact Data
├── Intent
├── Channel Type
├── Language
└── Queue Assignment
↓
Predictive Routing Engine Evaluates
├── Agent Availability Status
├── Skill Compatibility
├── Proficiency Levels
├── Current Workload
└── Historical Performance Score
↓
Machine Learning Model Predicts
├── Best Agent Match
├── Estimated Resolution Probability
└── Customer Satisfaction Likelihood
↓
Route to Optimal Agent
↓
If No Optimal Agent Available
├── Queue with Priority Calculation
├── Monitor for Next Available Match
└── Apply Fallback Routing Rules
↓
Agent Accepts Contact
Routing Rules & Overrides
Hard Rules (Always Applied)
Rule Priority: High
├── Agent Availability
├── Required Skills Present
├── Language Match
└── Queue Assignment
Rule Priority: Medium
├── Skill Proficiency Threshold
├── Agent Capacity
├── Contact Type Capability
└── Channel Configuration
Rule Priority: Low
├── Load Balancing
├── Historical Performance
└── Fairness Rotation
Skill Configuration Example
Technical Support Queue
Required Skills:
├── Product Knowledge (Level 3+)
│ ├── Software (Level 4)
│ ├── Hardware (Level 3)
│ └── Cloud Services (Level 3)
├── Troubleshooting (Level 3+)
├── Customer Service (Level 2+)
└── English Fluency (Level 3+)
Optional Skills:
├── Advanced Certifications (bonus)
├── Spanish Fluency (secondary channel)
└── VIP Customer Experience (specialized)
Bilingual Sales Queue
Required Skills:
├── Sales Techniques (Level 3+)
├── Product Knowledge (Level 3+)
├── English Fluency (Level 4+)
├── Spanish Fluency (Level 4+)
└── Customer Service (Level 3+)
Optional Skills:
├── Enterprise Sales (bonus)
├── Account Management (bonus)
└── Negotiation (specialized)
Real Flow Scenario: Predictive Routing in Action
Customer Calls Support Line
↓
System Analyzes: "Technical issue with mobile app"
↓
Route Requirements:
├── Skill: Mobile Development (Level 3+)
├── Skill: Customer Service (Level 2+)
├── Language: English
├── Channel: Voice
└── Queue: Technical Support
↓
Predictive Engine Evaluates All Available Agents:
Agent 1 (Sarah)
├── Mobile Development: Level 4 ✓
├── Customer Service: Level 4 ✓
├── Current Load: 1 contact
├── Avg Handle Time: 8 mins
├── FCR Rate: 85% ✓ (BEST MATCH)
Agent 2 (James)
├── Mobile Development: Level 2 (Below threshold)
├── Current Load: 2 contacts
├── FCR Rate: 72%
Agent 3 (Maria)
├── Mobile Development: Level 3 ✓
├── Customer Service: Level 3 ✓
├── Current Load: 3 contacts
├── FCR Rate: 78%
↓
Route to Agent Sarah (Highest Probability of Resolution)
↓
Sarah Answers Call
↓
System Logs Interaction for Future Learning
Omnichannel Predictive Routing
Voice Channels
Inbound Calls
↓
Predictive Routing
↓
Skill-based Queue
↓
Agent Answer
Digital Channels
Chat/Email/Social Arrival
↓
Predictive Routing Engine
↓
Agent Availability Check (across channels)
↓
Route to Agent with Capacity
↓
Agent Manages Omnichannel Load
Agent Can Handle:
├── 1 Voice Call
├── 2 Chat Conversations
├── 1 Email Thread
└── 1 Social Media Message
Total Capacity: 5 Concurrent Contacts
Current Load: 3 Contacts
Available Slots: 2
Real Flow Scenario: Omnichannel Assignment
Multiple Contacts in Queue:
├── Inbound Call (Technical)
├── Chat (Billing Question)
└── Email (Complaint)
Predictive Engine Evaluates:
↓
Agent 1 Capacity: 2 slots available
├── Skills: Technical, Billing, Customer Service ✓
├── Current: 1 Call + 1 Chat
├── Assignment: Route Email (write capability available)
↓
Agent 2 Capacity: 1 slot available
├── Skills: Technical, Billing ✓
├── Current: 1 Chat
├── Assignment: Route Call (available)
↓
Queue Assignment Complete
Usage Scenarios
| Scenario |
Solution |
Outcome |
| High call volume with variable skill requirements |
Enable predictive routing with skill-based queues |
Reduced wait times, improved FCR |
| Multiple agent skill levels |
Set proficiency thresholds in routing rules |
Appropriate complexity matching |
| Omnichannel contact center |
Use predictive routing across all channels |
Optimized agent utilization |
| International operations |
Configure language skills and regional routing |
Better customer satisfaction |
| Seasonal staffing fluctuations |
Adjust skill assignments dynamically |
Maintained service quality |
| VIP customer handling |
Create specialized skill for VIP interactions |
Enhanced customer experience |
Predictive Routing Configuration Settings
Queue-Level Settings
Queue Configuration: Technical Support
Routing Mode: Predictive Routing ✓
Skill Matching:
├── Required Skills: Product Knowledge, Troubleshooting
├── Proficiency Threshold: Level 3+
├── Language Match: Required
└── Strict Matching: Enabled
Fallback Behavior:
├── If no perfect match: Lower proficiency threshold
├── Escalation path: Senior support queue
└── Timeout: 30 seconds to find match
Load Balancing:
├── Max contacts per agent: 3
├── Considering ACW time: Yes
└── Fair distribution: Enabled
Monitoring & Analytics Dashboard
Key Metrics to Track
| Metric |
Target |
Purpose |
| First Contact Resolution (FCR) |
>80% |
Measure routing effectiveness |
| Average Handle Time (AHT) |
Baseline - 5% |
Track efficiency |
| Agent Utilization |
80-90% |
Optimize resource use |
| Customer Satisfaction (CSAT) |
>85% |
Measure outcomes |
| Skill Match Rate |
>95% |
Verify routing accuracy |
| Queue Abandonment |
<5% |
Monitor wait times |
| Call Transfer Rate |
<10% |
Reduce routing errors |
Real-Time Dashboard View
Predictive Routing Performance (Live)
Queue: Technical Support
├── Active Contacts: 24
├── Available Agents: 8
├── Avg Match Score: 4.2/5 ✓
├── Current AHT: 9.2 mins
└── Skill Match %: 96.4%
Top Performing Skills Today:
├── Mobile Development (8 contacts, 87% FCR)
├── Cloud Services (6 contacts, 82% FCR)
└── Hardware Support (4 contacts, 85% FCR)
Agent Performance:
├── Sarah: 4 contacts, 8.1 avg mins, 88% FCR
├── James: 3 contacts, 9.5 avg mins, 79% FCR
└── Maria: 2 contacts, 8.8 avg mins, 84% FCR
Best Practices
Skill Management
- Keep skills current - Update agent skills quarterly or after training
- Avoid over-specialization - Limit skill count to 8-10 per agent
- Balance proficiency - Mix Level 3-4 and Level 2 agents in queues
- Document requirements - Clearly define skill needs per queue
- Regular training - Invest in skill development to improve proficiency
Routing Optimization
- Start with hard rules - Use required skills and language matching first
- Monitor thresholds - Adjust proficiency requirements based on performance
- Test changes - Implement rule changes gradually
- Leverage analytics - Use data to identify routing improvements
- Continuous tuning - Predictive routing improves over time with more data
Agent Management
- Clear skill assignments - Agents must know their assigned skills
- Growth paths - Provide training to increase proficiency levels
- Regular feedback - Share routing and performance data
- Incentivize learning - Reward skill development
- Load balance fairly - Ensure equitable work distribution
Monitoring & Reporting
- Daily reviews - Check key metrics and anomalies
- Weekly analysis - Identify trends and improvement opportunities
- Monthly optimization - Adjust skills and rules as needed
- Quarterly planning - Forecast and plan for seasonal changes
- Annual strategy - Evaluate overall routing effectiveness
Common Configuration Scenarios
Scenario 1: Small Team (15 agents, 3 skill levels)
Configuration:
├── Premium Edition ✓
├── Workforce Optimization Module ✓
├── Single Queue (Support)
├── 3 Skill Categories (Level 1-4 scaling)
└── Basic Routing Rules
Expected Results:
├── 20-30% improvement in FCR
├── 10-15% reduction in AHT
└── Higher agent satisfaction
Scenario 2: Large Enterprise (200+ agents, multiple queues)
Configuration:
├── Premium Edition ✓
├── Workforce Optimization Module ✓
├── 5-8 Queues (Technical, Billing, Sales, etc.)
├── 15+ Skill Categories with proficiency levels
├── Advanced Routing Rules and Overrides
└── Omnichannel Blending
Expected Results:
├── 25-40% improvement in FCR
├── 15-25% reduction in AHT
├── Significant CSAT increase
└── Better resource utilization
Scenario 3: Multilingual Contact Center (5 languages)
Configuration:
├── Language Skills for each agent
├── Language Matching in Routing Rules
├── Regional Queue Assignment
├── Skill + Language Combination Routing
└── Overflow to general queue if no match
Expected Results:
├── Improved customer satisfaction
├── Reduced transfers
├── Better first contact resolution
└── International service quality
Troubleshooting Guide
| Issue |
Cause |
Resolution |
| Contacts routing to wrong skill level |
Proficiency threshold too low |
Increase threshold in routing rules |
| Long wait times |
Predictive routing disabled for queue |
Enable predictive routing in queue config |
| High transfer rates |
Skill mismatch in routing |
Review and update skill definitions |
| Uneven agent load |
Skill imbalance among agents |
Provide training to level skill distribution |
| Poor FCR rates |
Insufficient skill matching |
Add more skill categories to definitions |
| Agents overloaded |
Capacity settings too high |
Reduce max contacts per agent |
| Low agent utilization |
Skill requirements too strict |
Relax proficiency thresholds slightly |
| Routing delays |
Too many hard rules |
Simplify rules and priorities |
| Language mismatch |
Language skills not configured |
Add language proficiency to agent setup |
| Module not working |
Feature not enabled |
Verify Premium edition and module purchase |
Real-World Implementation Timeline
Week 1-2: Assessment & Planning
Day 1-2: Kick-off meeting
Day 3-5: Audit current routing and skills
Day 6-10: Design new skill structure
Day 11-14: Plan change management
Week 3-4: Configuration
Day 15-18: Create skill definitions
Day 19-22: Configure queues and rules
Day 23-25: Set up monitoring dashboard
Day 26-28: Document configuration
Week 5-6: Testing & Pilot
Day 29-32: Conduct routing tests
Day 33-36: Deploy to pilot queue
Day 37-40: Monitor pilot performance
Day 41-42: Gather feedback and optimize
Week 7-8: Full Deployment
Day 43-44: Plan rollout schedule
Day 45-52: Deploy to remaining queues
Day 53-56: Monitor and support agents
Naming Convention
Queue Naming with Routing Type
<Department>_<Function>_<RoutingType>_Queue
Examples:
Support_Technical_PredictiveRouting_QueueSales_Enterprise_PredictiveRouting_QueueBilling_Collections_PredictiveRouting_Queue
Skill Naming Convention
<Category>_<SubCategory>_<Level>
Examples:
Product_MobileApp_SkillLanguage_Spanish_FluencyService_VIP_HandlingTechnical_CloudServices_Certification
Integration with Other Systems
Workforce Management (WFM)
Predictive Routing ←→ WFM
├── Share agent availability
├── Schedule compliance
├── Forecasting data
└── Staffing adjustments
Quality Management
Predictive Routing ←→ Quality Management
├── Interaction recordings
├── Performance metrics
├── Coaching opportunities
└── Training recommendations
Customer Data Platform
Predictive Routing ←→ Customer Data
├── Customer history
├── Preferences
├── Previous resolutions
└── VIP status
Industry Standard Improvements
| Metric |
Typical Improvement |
| First Contact Resolution |
+15-40% |
| Average Handle Time |
-10-25% |
| Customer Satisfaction |
+10-25% |
| Agent Utilization |
+5-15% |
| Queue Abandonment |
-20-50% |
| Cost Per Contact |
-10-20% |
Ramp-Up Timeline
Day 1-30: Learning phase, marginal improvement
Month 2-3: System learns patterns, 10-15% improvement
Month 4-6: Optimized configuration, 25-35% improvement
Month 6+: Mature state, 30-40% improvement
Predictive Routing vs. Traditional Routing
| Feature |
Predictive Routing |
Traditional Routing |
| Skill Matching |
AI-optimized |
Rules-based |
| Agent Selection |
Predictive |
Sequential |
| Learning |
Continuous |
None |
| Complexity |
High |
Low |
| Setup Time |
Medium |
Low |
| Optimization |
Automatic |
Manual |
| FCR Improvement |
25-40% |
Baseline |
| Cost |
Higher |
Lower |
Interview Cheat Sheet
| Question |
Answer |
| What is Predictive Routing? |
AI-powered routing system that optimizes agent assignment using ML |
| What are the requirements? |
Premium edition + Workforce Optimization module |
| How does it select agents? |
Analyzes skills, availability, performance, and predicts best match |
| What factors does it consider? |
Skills, proficiency, availability, workload, language, history |
| Can you use it with omnichannel? |
Yes, works with voice, chat, email, and messaging |
| How is it different from skill-based routing? |
Uses ML to predict best match vs. just checking skills |
| Where do you configure it? |
Admin → Contact Center → Routing |
| What's the expected improvement? |
FCR +25-40%, AHT -10-25%, CSAT +10-25% |
| How long does setup take? |
4-8 weeks depending on complexity |
| What are critical success factors? |
Accurate skills data, proper proficiency levels, continuous monitoring |
| How do you monitor performance? |
Daily dashboard review, weekly analytics, monthly optimization |
| What if no perfect agent match exists? |
System queues contact with fallback routing rules |
| Can you override predictive routing? |
Yes, hard rules take precedence (availability, required skills) |
| How does machine learning help? |
Learns from past outcomes to improve future routing |
| What's the ROI timeline? |
2-3 months to see significant improvements |
Key Takeaways
- AI-Powered Optimization - Predictive routing uses machine learning to match contacts to best-fit agents
- Skill-Based Foundation - Requires well-defined skills and proficiency levels
- Omnichannel Capable - Works across voice, chat, email, and messaging channels
- Continuous Learning - System improves routing decisions over time
- Premium Feature - Requires Premium edition and Workforce Optimization module
- Significant ROI - Typical improvements: FCR +25-40%, AHT -10-25%
- Real-Time Optimization - Routes contacts dynamically based on current system state
- Fallback Rules Matter - Hard rules ensure quality even without perfect matches
- Change Management Critical - Proper implementation and monitoring are essential
- Ongoing Monitoring Required - Daily reviews and monthly tuning maximize benefits
Migration Path from Traditional Routing
Phase 1: Preparation (Weeks 1-2)
├── Audit current routing rules
├── Document all skills currently used
├── Identify skill gaps
└── Plan queue restructuring
Phase 2: Setup (Weeks 3-4)
├── Create comprehensive skill definitions
├── Assign skills and proficiency to agents
├── Configure predictive routing queues
└── Establish monitoring dashboards
Phase 3: Pilot (Weeks 5-6)
├── Enable on low-risk queue
├── Monitor closely for issues
├── Gather team feedback
└── Optimize configuration
Phase 4: Rollout (Weeks 7-8)
├── Disable traditional routing rules
├── Enable predictive on remaining queues
├── Support agents through transition
└── Celebrate early wins
Additional Resources
Official Documentation Links
- Genesys Cloud Routing Guide: https://help.genesys.com/genesyscloud/current/en-us/Routing.html
- Predictive Routing Setup: https://help.genesys.com/genesyscloud/current/en-us/PredictiveRouting.html
- Workforce Optimization: https://help.genesys.com/genesyscloud/current/en-us/WFO.html
- Genesys Sales: [email protected]
- Genesys Support: https://support.genesys.com
- Community Forums: https://community.genesys.com
Document Version Info
Last Updated: March 2026
Source: Genesys PureCloud Official Documentation
Version: 1.0
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