Serveza.AI
  • Introduction
  • Why Choose ServezaAI?
    • Mission and Vision
    • Relevance
    • Problems We Solve
  • Serveza AI Ecosystem
    • ServezaAI Voice Call Agent
      • How It Works: Step-by-Step
        • Step 1: Define Your Purpose
        • Step 2: AI Agent Customization & Campaign Design
        • Step 3: Deploy & Activate Your AI Agent
        • Monitor & Optimize Your AI Agent
    • ServezaAI Analytics Dashboard
      • ServezaAI Analytics Dashboard Metrics
    • ServezaAI Anonymous Call Routing
    • ServezaAI Function Calling
    • ServezaAI Data Marketplace
      • Data and AI Agent Monetization
  • ServezaAI Token
  • Tokenomics
  • Roadmap
  • Join Us
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  1. Serveza AI Ecosystem
  2. ServezaAI Analytics Dashboard

ServezaAI Analytics Dashboard Metrics

1. Call Metrics

  • Total Call Volume: Track the total number of calls handled by AI agents and human agents.

  • AI Call Completion Rate: The percentage of calls fully handled by AI agents without escalation.

  • Average Call Duration: Average length of each call, segmented by AI and human interactions.

  • Abandonment Rate: The percentage of calls abandoned by customers before they connect with an agent.

2. Lead Metrics

  • Lead Generation Rate: The number of leads generated through AI interactions compared to the total number of calls.

  • Lead Qualification Accuracy: The percentage of leads correctly identified as high-potential by the AI.

  • Conversion Rate: The percentage of qualified leads that convert into customers, segmented by AI vs. human handling.

  • Lead Status Overview: Track the progression of each lead from initial contact to closure.

3. Customer Interaction Metrics

  • Customer Satisfaction (CSAT): Measure customer satisfaction post-interaction through automated surveys or feedback.

  • First Call Resolution (FCR): The percentage of calls resolved on the first contact, without the need for a follow-up.

  • Escalation Rate: The percentage of calls that escalate from AI agents to human agents, providing insight into AI agent performance and areas for improvement.

  • Sentiment Analysis: AI-driven analysis of customer tone and sentiment during interactions (positive, neutral, negative).

4. Performance Metrics

  • AI Accuracy Rate: Measure how accurately the AI handles calls and meets predefined objectives, such as lead qualification, issue resolution, or service requests.

  • Agent Performance: Track human agent performance, such as average handling time, resolution rate, and customer satisfaction.

  • Call Transfer Efficiency: Measure how efficiently calls are transferred from AI agents to human agents, including time taken and success rate.

5. Operational Efficiency

  • Cost Per Interaction: Track the cost of each interaction (whether AI or human) and analyze efficiency improvements over time.

  • Time to Resolution: The average time it takes to resolve a customer’s issue or complete a sale from initial contact.

  • Call Routing Efficiency: Measure the accuracy and efficiency of AI-powered call routing, ensuring customers are connected to the right department or representative.

6. AI Optimization Metrics

  • Script Optimization Results: Show the impact of A/B testing or AI-driven script changes on call outcomes, conversion rates, and satisfaction.

  • AI Training Progress: Track the learning curve and continuous improvement of the AI agent based on customer feedback and new data.

  • AI Adaptability Rate: The AI’s ability to adjust scripts and responses based on different customer segments or evolving business goals.

7. Compliance and Security Metrics

  • Data Compliance Rate: The percentage of calls and data interactions fully compliant with privacy regulations like GDPR or CCPA.

  • Data Integrity: Track any instances of data breaches or unauthorized access to customer data, leveraging blockchain’s immutable audit trail.

  • Blockchain Transaction Logs: Real-time tracking of all data transactions recorded on the blockchain, ensuring complete transparency.

8. Scalability and Growth Metrics

  • Scalability Index: Measure how well the AI system scales with increased call volume or additional service channels.

  • Growth in Lead Pool: Track the growth of the lead pool over time, measuring both the quantity and quality of leads collected by AI.

  • Revenue Impact: Link AI performance to overall business revenue by tracking sales closed from AI-driven leads and support interactions.

9. Customer Retention Metrics

  • Repeat Interaction Rate: Track how many customers return after their first interaction, measuring loyalty and satisfaction.

  • Retention Rate: The percentage of customers retained through AI-driven customer support and personalized outreach.

  • Churn Rate: Measure the percentage of customers lost over a given period, allowing businesses to adjust strategies.

10. Customizable Dashboards

  • Custom Metrics Creation: Allow users to create and monitor specific metrics tailored to their unique business needs, whether related to sales, support, or specific KPIs.

  • Data Segmentation: Enable users to segment data by customer demographics, call type, AI vs. human interaction, etc., for deeper insights.

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Last updated 4 months ago