Analytics Overview
Freyavoice AI provides comprehensive analytics to help you understand call performance, agent effectiveness, user satisfaction, and business metrics. These insights enable data-driven decisions and continuous improvement.Key Metrics
Call Metrics
Call Volume: Total number of calls, calls per day/hour, and trends over time. This helps you understand usage patterns and plan capacity. Call Duration: Average call length, total talk time, and duration distributions. Longer calls might indicate complexity or inefficiency. Call Success Rate: Percentage of calls that complete successfully versus those that fail or drop. High success rates indicate good system health. Call Quality: Audio quality metrics, connection stability, and technical performance indicators.Agent Performance
Response Quality: Analysis of agent responses for clarity, accuracy, and helpfulness. This helps identify areas for prompt improvement. Goal Achievement: Percentage of calls where agents successfully achieve their goals (sales, support resolution, etc.). Function Usage: Which functions are called most often and how effectively they’re used. Context Management: How well agents maintain context throughout conversations.User Satisfaction
Sentiment Analysis: Analysis of caller sentiment throughout conversations. Positive sentiment indicates good experiences. Resolution Rate: Percentage of calls where user issues are resolved or goals are achieved. User Feedback: Direct feedback from users about their experience (if collected). Repeat Call Rate: How often users call back, which might indicate unresolved issues.Business Metrics
Cost per Call: Total cost divided by number of calls. Helps optimize spending. Conversion Rate: For sales or lead generation, the percentage of calls that result in conversions. Average Handle Time: How long it takes to handle each call. Lower times can indicate efficiency. First Call Resolution: Percentage of issues resolved on the first call without follow-up.Analytics Dashboard
Overview Dashboard
High-Level Metrics: Key performance indicators at a glance. Trends: Visualizations showing how metrics change over time. Comparisons: Compare performance across different time periods, agents, or workflows. Alerts: Notifications for important changes or anomalies.Detailed Reports
Call Reports: Detailed breakdowns of individual calls with transcripts, recordings, and metadata. Agent Reports: Performance analysis for specific agents including strengths and areas for improvement. Workflow Reports: Analysis of workflow execution including path taken, node performance, and bottlenecks. Cost Reports: Detailed cost breakdowns by workspace, agent, or time period.Using Analytics
Performance Monitoring
Track KPIs: Monitor key performance indicators regularly to ensure goals are being met. Identify Trends: Look for trends in metrics that might indicate issues or opportunities. Compare Periods: Compare current performance to previous periods to measure improvement. Set Alerts: Configure alerts for important metrics to catch issues early.Optimization
Identify Bottlenecks: Use analytics to find performance bottlenecks and optimization opportunities. Improve Agents: Use performance data to identify which agents need improvement and how. Optimize Workflows: Analyze workflow execution to find inefficiencies and optimization opportunities. Cost Optimization: Identify cost drivers and optimize spending without sacrificing quality.Business Intelligence
Understand Users: Analyze call patterns to better understand your users and their needs. Product Insights: Use conversation data to gain insights about your products or services. Market Research: Analyze call topics and trends to understand market needs. Strategic Planning: Use analytics data to inform strategic decisions and planning.Advanced Analytics
Custom Reports
Build Reports: Create custom reports with the metrics and visualizations you need. Schedule Reports: Automatically generate and deliver reports on a schedule. Export Data: Export data for analysis in external tools.Data Integration
API Access: Access analytics data programmatically via API. Webhook Events: Receive analytics events via webhooks for real-time processing. Data Warehouse: Integrate with data warehouses for advanced analysis.Predictive Analytics
Forecasting: Predict future call volumes and resource needs. Trend Analysis: Identify emerging trends before they become obvious. Anomaly Detection: Automatically detect unusual patterns that might indicate issues.Best Practices
Regular Review
Daily Monitoring: Check key metrics daily to catch issues early. Weekly Analysis: Perform deeper analysis weekly to identify trends and opportunities. Monthly Reviews: Conduct comprehensive monthly reviews to assess overall performance.Actionable Insights
Focus on Action: Don’t just collect data - use it to make decisions and take action. Prioritize: Focus on metrics that matter most to your business goals. Experiment: Use analytics to guide experiments and A/B tests. Iterate: Continuously improve based on analytics insights.Data Quality
Ensure Accuracy: Verify that analytics data is accurate and complete. Understand Metrics: Make sure you understand what each metric means and how it’s calculated. Context Matters: Consider context when interpreting metrics. A low metric might be good or bad depending on context.Next Steps
Campaigns
Learn how to create and manage outbound calling campaigns.