Analytics Suite

The Analytics Suite provides visibility into how Relational Agents perform across projects. It combines usage statistics with qualitative signals, allowing teams to evaluate both the efficiency of conversations and the outcomes they generate. Analytics can be viewed globally at the project level or drilled down to individual agents, making it possible to track overall adoption while also refining specific experiences.

At the highest level, analytics show how users move through the conversational funnel — from entry into a session through to completion. This helps identify points of friction where users disengage or abandon the process.

Filter by agent version

What it is

You can now filter analytics by a specific agent version or view all versions together.

Why it matters

Compare performance across versions, validate changes, and identify what improved or regressed.

How to use

Open Analytics. Use the Version selector in the top-right corner to choose a specific version or All versions to view project-wide performance.

Core Metrics

  • Conversational Funnel – visualises the conversational throughput of all sessions (how many clients started the interaction and when they left).

  • Session Length – total and average duration of conversations, showing the depth of engagement.

  • Bounce Rate – proportion of sessions abandoned before any meaningful interaction.

  • Relational Metrics – qualitative measures such as turn balance, pacing, or user sentiment.

  • Global vs. Per-Agent Views – compare aggregate performance across a project with the results of individual agents.

  • Multimodal Activity – counts of structured actions such as forms filled, images displayed, or web views opened.

  • Memory Usage – tracks how often memories and Knowledge Graph connections are accessed by agents and their impact on personalization or resolution times.

  • Conversion Summaries – high-level indicators of how conversations connect to business outcomes (resolved cases, completed workflows, influenced sales).

These metrics allow product teams to continuously improve agents: reducing drop-off, shortening resolution times, and optimising relational quality. They also provide evidence for business leaders on how relational intelligence contributes directly to KPIs like customer satisfaction, efficiency, and conversion.