What is AI Employee Matching?

AI Employee Matching is an intelligent feature that automatically recommends the best employees for appointments based on multiple factors. Instead of manually selecting employees, the AI analyzes various criteria to suggest the optimal match for each appointment.

This feature helps ensure appointments are assigned to the right employees, improving efficiency, client satisfaction, and workload balance across your team.

How AI Employee Matching Works

When you create an appointment or use AI Scheduling, the system automatically evaluates employees based on:

• Required Skills: Employees must have the skills and certifications needed for the service
• Availability: Employees must be available at the requested time
• Client Preferences: If the client has preferred employees, those are prioritized
• Historical Performance: Past performance and client satisfaction ratings
• Workload Balance: Distribution of work across employees to prevent overloading
• Experience: Experience with similar services or clients
• Location: Proximity to the appointment location (if location data is available)

When Employee Recommendations Appear

AI employee recommendations are automatically provided when:

• Creating a new appointment with a service that requires specific skills
• Using AI Scheduling to generate appointments
• Manually selecting an employee for an appointment (recommendations appear as suggestions)
• Rescheduling appointments where the original employee may not be available

Understanding Recommendation Confidence

Each employee recommendation includes a confidence score that indicates how well the employee matches the appointment requirements:

• High Confidence (80-100%): Excellent match - employee has all required skills, is available, and meets all criteria
• Medium Confidence (50-79%): Good match - employee meets most requirements but may have minor limitations
• Low Confidence (Below 50%): Partial match - employee may be missing some requirements or have conflicts

The AI also provides reasoning for each recommendation, explaining why a particular employee was suggested.

Using AI Employee Recommendations

1. View Recommendations

When creating an appointment, you'll see a list of recommended employees ranked by their match quality. The top recommendation is typically the best fit.

2. Review Match Details

Click on any recommended employee to see:

• Confidence score and reasoning
• Skills match status
• Availability confirmation
• Workload information
• Historical performance data
• Any warnings or considerations

3. Select an Employee

You can:

• Accept the top recommendation: Use the AI's top pick for the best match
• Choose an alternative: Select from other recommended employees if you prefer
• Select manually: Choose any employee, even if not recommended (you'll see warnings if there are issues)

Improving Recommendation Quality

To get better AI employee recommendations, ensure your data is complete and up to date:

• Employee Skills: Add all relevant skills and certifications to employee profiles
• Availability: Keep employee availability schedules current
• Client Preferences: Record any client preferences for specific employees
• Performance Data: The system learns from historical appointment data and client feedback
• Service Requirements: Clearly define required skills for each service

Understanding Match Factors

Each recommendation shows which factors influenced the match:

• Has Required Skills: Whether the employee can perform the service
• Is Available: Whether the employee is free at the appointment time
• Client Preference: Whether the client prefers this employee
• Workload Balance: How balanced the employee's current workload is
• Historical Performance: Past success rate with similar appointments

Alternative Recommendations

The AI typically provides multiple employee options, ranked by suitability. Alternative recommendations are useful when:

• The top recommendation is unavailable due to last-minute changes
• You want to distribute work more evenly across your team
• You need to consider other business factors not captured in the AI analysis
• You want to give opportunities to less-experienced employees for development

Best Practices

• Review recommendations but trust the AI for routine appointments - it learns from your patterns
• Use manual selection when you have specific business reasons that override AI suggestions
• Keep employee profiles updated with new skills and certifications
• Provide feedback through appointment outcomes to help the AI learn and improve
• Consider alternative recommendations when balancing team workload