Transforming Sales Analytics: Empowering AI Sales with Data-Driven Insights

Goal

To build an analytics solution that provides AI Sales with internal and client-facing dashboards to monitor company-wide revenue, measure the effectiveness of AI bots, and identify performance gaps compared to human sales representatives.

Results 

The team delivered a comprehensive analytics system tailored to AI Sales’ needs:

  1. Revenue Tracking Dashboard:
    A company-wide revenue dashboard was implemented, allowing AI Sales to monitor its financial performance across all clients.

  2. Client Performance Dashboards:
    • Conversion Tracking
      Dashboards visualized AI bot vs. human sales conversion rates by time periods and UTM tags. This provided granular insights into performance across different lead sources.

    • Lead Reactivation Analytics
      Highlighted the percentage of leads reactivated after initial drop-offs, offering a clear comparison of AI and human handling.
    • Call and Message Analysis
      Provided detailed analytics on call and message statuses, delivery rates, and reasons for lead rejection.

    • Interaction Frequency Insights
      Visualized call frequency and its correlation to lead conversion rates.
  3. Alert System
    A Slack-based alert system was set up to provide daily updates on total revenue, ensuring the team stayed informed in real-time.
  4. Performance Research
    Machine learning models were employed to identify factors influencing conversion rates for both AI and human sales teams. Findings revealed:

    • “Fast reaction” tags and “night leads” negatively impacted AI performance.
    • Human sales representatives showed higher adaptability, such as offering discounts and engaging repeat leads, areas not accounted for in the bot’s scripts.
    • Enhanced prompts were developed with input from top-performing human sales representatives to improve bot communication strategies.

This multi-faceted approach resulted in a powerful analytics suite and actionable insights, boosting AI Sales’ product effectiveness and client satisfaction.

Tips

  • Prioritize Comparative Metrics: To effectively gauge AI performance, always benchmark it against human sales metrics to uncover actionable gaps.
  • Use Data to Refine Processes: Leverage insights to iteratively improve AI scripts, incorporating flexibility and human-like decision-making capabilities.
  • Automate Alerts: Daily alerts for critical metrics ensure teams remain aligned with performance objectives and can respond quickly to deviations.

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