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Metrics let you track patterns in conversations that would be impossible to capture with traditional event-based analytics. Define what you want to measure using plain text — just like policies — and White Circle handles the rest.

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Example Use Cases

  • Was the user’s issue resolved?
  • How often do users express frustration?
  • How often do users ask for help?
  • How often do users ask for bug fixes vs. new features vs. documentation?
  • Are users asking follow-up questions after code generation?
  • What programming languages are most requested?
  • Did the student understand the explanation?
  • How often do users ask for simpler explanations?
  • What topics generate the most questions?
  • Did the conversation lead to purchase intent?
  • What objections come up most frequently?
  • How often do users ask about pricing?

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How Metrics Work

Metrics let you define what you want to measure using plain text — just like policies. Each metric has two components:

Included Content

Describe what should count toward this metric.

Excluded Content

Describe what should be excluded, even if it seems similar.
Metrics are computed based on only the last message in the messages array. Previous messages provide context for the evaluation.
To track how often users request new features:
  • Included: “User asks for a new capability, requests functionality that doesn’t exist, suggests improvements or additions”
  • Excluded: “Bug reports, questions about existing features, general feedback without specific feature requests”

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Metrics vs. Policies

While metrics and policies use the same definition approach, they serve different purposes:
Metrics are processed in the background, which allows us to compute a large number of metrics at scale. There’s a delay before results become available in your dashboard.

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Getting Started

Creating a metric follows the same workflow as policies:
1

Open the Metrics Page

Navigate to the Metrics page in your White Circle dashboard.
2

Create a New Metric

Click Add Metric and give it a descriptive name like “Feature Requests” or “User Satisfaction”.
3

Define Your Metric

Write what should be included and excluded using plain language.
4

Save and Start Tracking

Once saved, metrics are automatically computed for all requests sent to the /api/session/check endpoint.

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Viewing Analytics

On the platform, you can view analytics for each metric individually. This includes trends over time and breakdowns of matched content.
We recommend sending user metadata with your requests from day one. This will allow you to segment metrics by user attributes and get meaningful insights as soon as dashboards with filtering capabilities become available.

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Next Steps

Create a Metric

Open the platform and define your first metric

Add Metadata

Learn how to attach user information for richer analytics