AI Agent Analytics in Tableau
When it comes to AI Agent Analytics, data is everywhere—but not all data is useful. In analytics, it's easy to drown in dozens of metrics and dashboards that look impressive but say little. Instead of tracking everything, we focus on a few high-impact KPIs that directly reflect user engagement, automation efficiency, and performance trends.

Metrics That Matter

For platforms like Cognigy AI and Kore.ai, we've identified four core metrics that deliver meaningful insights:

Goal Completion Rate (%)
Measures how often users complete their task using the chatbot (e.g., resetting a password, updating an address). This is the best proxy for overall chatbot success.
Human Handover Rate (%)
Tracks how frequently the bot escalates to a human agent—either automatically or by user request. A rising handover rate can flag automation gaps or trust issues.
Number of Conversations
A basic usage metric showing how much volume the chatbot is handling. Important for understanding adoption trends and seasonality.
Exit Rates (by interaction depth)
We break this down into:
- Exited after 1 message
- Exited after 2 messages
- Exited after 3–5 messages
- Exited after 6+ messages
  
  This helps pinpoint where users drop off in the flow—whether due to confusion, disinterest, or chatbot failure.

⚠️ Attention: Metrics vs. KPIs

Many teams use the terms metric and KPI interchangeably—but they’re not the same.

A metric is a number you track.
Example: Goal Completion Rate = 70%
A KPI (Key Performance Indicator) is a metric with context—a benchmark, a goal, or a standard.
Example: Goal Completion Rate = 70% vs. Target = 65%

Only with a reference point does a metric become a KPI. This distinction is critical when communicating success or identifying underperformance.

Real-World Example: Goal Completion Rate
Here’s a demo snapshot of one of our Tableau dashboards:

In this view, we highlight trends, annotate key insights, and instantly communicate whether performance is improving or at risk. The use of a trend line and target benchmark makes the story clear—even to non-technical stakeholders.

🚀 Why It Matters

By focusing on just a handful of well-defined KPIs, your chatbot analytics go from noise to narrative. This is especially crucial for enterprises using platforms like Cognigy AI or Kore AI, where clarity and outcomes drive value.

Whether you're optimizing service automation or preparing a stakeholder demo, fewer metrics—if chosen well—lead to better decisions.

Franco