Recording Metrics

Overview

Metrics let you measure how well your prompts perform. When you record metrics with the same subject used for prompt execution, Switchport automatically aggregates them per prompt version.

Basic Usage

Record a metric:

package main

import (
	"fmt"
	"log"

	"github.com/switchport-ai/switchport-go/switchport"
)

func main() {
	client, err := switchport.NewClient("")
	if err != nil {
		log.Fatalf("Failed to create client: %v", err)
	}

	result, err := client.Metrics.Record(
		"user_satisfaction",
		4.5,
		map[string]interface{}{"user_id": "user_123"},
		nil, // timestamp (nil = current time)
	)
	if err != nil {
		log.Fatalf("Failed to record metric: %v", err)
	}

	fmt.Printf("Metric recorded: %s\n", result.MetricEventID)
}

Metric Types

Switchport supports three types of metrics:

Float Metrics

Numerical values (e.g., ratings, scores, response times):

// User satisfaction (1-5 scale)
client.Metrics.Record(
	"satisfaction",
	4.5,
	map[string]interface{}{"user_id": "user_123"},
	nil,
)

// Response time in milliseconds
client.Metrics.Record(
	"response_time_ms",
	125.7,
	map[string]interface{}{"request_id": "req_abc"},
	nil,
)

// Can also pass int values
client.Metrics.Record(
	"response_time_ms",
	125,
	map[string]interface{}{"request_id": "req_abc"},
	nil,
)

Boolean Metrics

True/false values (e.g., conversions, success rates):

// Conversion tracking
client.Metrics.Record(
	"conversion",
	true,
	map[string]interface{}{"user_id": "user_123"},
	nil,
)

// Email opened
client.Metrics.Record(
	"email_opened",
	false,
	map[string]interface{}{"email_id": "email_456"},
	nil,
)

Enum Metrics

Categorical values (e.g., sentiment, outcome):

// User sentiment
client.Metrics.Record(
	"sentiment",
	"positive",
	map[string]interface{}{"user_id": "user_123"},
	nil,
)

// Outcome classification
client.Metrics.Record(
	"outcome",
	"resolved",
	map[string]interface{}{"ticket_id": "ticket_789"},
	nil,
)

Creating Metric Definitions

Before recording metrics, create a metric definition in the dashboard:

Navigate to Metrics

Go to Metrics → New Metric in the dashboard

Configure the metric

Key: Unique identifier (e.g., satisfaction)
Name: Human-readable name (e.g., “User Satisfaction”)
Type: float, boolean, or enum

Create

Click Create to save the metric definition

Linking Metrics to Prompts

To link metrics to prompt versions, use the same subject for both:

// Execute prompt with subject identification
subject := map[string]interface{}{"user_id": "user_123"}

response, err := client.Prompts.Execute(
	"welcome-message", subject,
	map[string]interface{}{"name": "Alice"},
)
if err != nil {
	log.Fatalf("Failed to execute prompt: %v", err)
}

// Show message to user...
fmt.Println(response.Text)

// Later, record metric with SAME subject
result, err := client.Metrics.Record(
	"satisfaction",
	4.5,
	subject, // Same subject!
	nil,
)
if err != nil {
	log.Fatalf("Failed to record metric: %v", err)
}

Always use the same subject when executing prompts and recording metrics. This ensures metrics are correctly attributed to the right prompt version.

Custom Timestamps

You can provide a custom timestamp for metrics:

import "time"

// Record metric with custom timestamp
timestamp := time.Now().Add(-1 * time.Hour) // 1 hour ago

result, err := client.Metrics.Record(
	"satisfaction",
	4.5,
	map[string]interface{}{"user_id": "user_123"},
	&timestamp, // Custom timestamp
)

If you pass nil, the current time is used.

Response Object

The Record method returns a MetricRecordResponse:

result, err := client.Metrics.Record(
	"satisfaction",
	4.5,
	map[string]interface{}{"user_id": "user_123"},
	nil,
)
if err != nil {
	log.Fatalf("Failed to record metric: %v", err)
}

// Check success
fmt.Printf("Success: %v\n", result.Success)

// Unique event identifier
fmt.Printf("Event ID: %s\n", result.MetricEventID)

Error Handling

Handle common errors when recording metrics:

package main

import (
	"errors"
	"log"

	"github.com/switchport-ai/switchport-go/switchport"
)

func main() {
	client, err := switchport.NewClient("")
	if err != nil {
		log.Fatalf("Failed to create client: %v", err)
	}

	result, err := client.Metrics.Record(
		"satisfaction",
		4.5,
		map[string]interface{}{"user_id": "user_123"},
		nil,
	)
	if err != nil {
		var metricNotFound *switchport.MetricNotFoundError
		var authErr *switchport.AuthenticationError
		var apiErr *switchport.APIError

		switch {
		case errors.As(err, &metricNotFound):
			log.Println("Metric definition not found - create it in the dashboard")
		case errors.As(err, &authErr):
			log.Println("Authentication failed - check your API key")
		case errors.As(err, &apiErr):
			log.Printf("API error (status %d): %v", apiErr.StatusCode, apiErr)
		default:
			log.Printf("Unknown error: %v", err)
		}
		return
	}

	log.Printf("Metric recorded: %s\n", result.MetricEventID)
}

Common Patterns

Pattern 1: User Feedback

func handleUserFeedback(client *switchport.Client, userID string, rating float64) error {
	_, err := client.Metrics.Record(
		"satisfaction",
		rating,
		map[string]interface{}{"user_id": userID},
		nil,
	)
	return err
}

Pattern 2: Conversion Tracking

func trackConversion(client *switchport.Client, userID string, converted bool) error {
	_, err := client.Metrics.Record(
		"conversion",
		converted,
		map[string]interface{}{"user_id": userID},
		nil,
	)
	return err
}

Pattern 3: Email Campaign

func sendEmailAndTrack(client *switchport.Client, user User) error {
	subject := map[string]interface{}{
		"user_id":  user.ID,
		"campaign": "summer_2025",
	}

	// Execute prompt
	response, err := client.Prompts.Execute(
		"marketing-email", subject,
		map[string]interface{}{"name": user.Name},
	)
	if err != nil {
		return err
	}

	// Send email
	if err := sendEmail(user.Email, response.Text); err != nil {
		return err
	}

	// Track if opened (later)
	if emailWasOpened(user.ID) {
		_, err := client.Metrics.Record(
			"email_opened",
			true, subject, // Same subject
			nil,
		)
		return err
	}

	return nil
}

Pattern 4: Multi-Metric Tracking

type InteractionData struct {
	Rating    float64
	Converted bool
	Sentiment string
}

func completeInteraction(client *switchport.Client, userID string, data InteractionData) error {
	subject := map[string]interface{}{"user_id": userID}

	// Record satisfaction
	if _, err := client.Metrics.Record("satisfaction", data.Rating, subject, nil); err != nil {
		return err
	}

	// Record conversion
	if _, err := client.Metrics.Record("conversion", data.Converted, subject, nil); err != nil {
		return err
	}

	// Record sentiment
	if _, err := client.Metrics.Record("sentiment", data.Sentiment, subject, nil); err != nil {
		return err
	}

	return nil
}

Pattern 5: Goroutine for Async Recording

func recordMetricAsync(client *switchport.Client, metricKey string, value interface{}, subject switchport.Subject) {
	go func() {
		_, err := client.Metrics.Record(metricKey, value, subject, nil)
		if err != nil {
			log.Printf("Failed to record metric %s: %v", metricKey, err)
		}
	}()
}

Best Practices

Use the same subject

Always use the same subject for prompt execution and metric recording to ensure proper aggregation.

Record metrics asynchronously

Consider recording metrics in a goroutine to avoid blocking your main application flow.

Handle failures gracefully

Don’t let metric recording failures break your application. Use error handling and logging.

Choose appropriate metric types

Use the right metric type for your use case:

Float (or int) for numerical measurements
Boolean for yes/no tracking
String for categorical data (enum)

Define metrics early

Create metric definitions in the dashboard before recording metrics in your code.

Use type-safe wrappers

Consider creating wrapper functions with specific types for your metrics to avoid interface everywhere.

Viewing Metrics

Metrics are automatically aggregated per prompt version in the dashboard. You can:

View average values for float metrics
View success rates for boolean metrics
View distribution for enum metrics
Compare metrics across different prompt versions
Identify winning versions based on metric performance

Getting Started

Core Features

Examples

Overview

Basic Usage

Metric Types

Float Metrics

Boolean Metrics

Enum Metrics

Creating Metric Definitions

Linking Metrics to Prompts

Custom Timestamps

Response Object

Error Handling

Common Patterns

Pattern 1: User Feedback

Pattern 2: Conversion Tracking

Pattern 3: Email Campaign

Pattern 4: Multi-Metric Tracking

Pattern 5: Goroutine for Async Recording

Best Practices

Viewing Metrics

Next Steps

A/B Testing

API Reference

Getting Started

Core Features

Examples

​Overview

​Basic Usage

​Metric Types

​Float Metrics

​Boolean Metrics

​Enum Metrics

​Creating Metric Definitions

​Linking Metrics to Prompts

​Custom Timestamps

​Response Object

​Error Handling

​Common Patterns

​Pattern 1: User Feedback

​Pattern 2: Conversion Tracking

​Pattern 3: Email Campaign

​Pattern 4: Multi-Metric Tracking

​Pattern 5: Goroutine for Async Recording

​Best Practices

​Viewing Metrics

​Next Steps

A/B Testing

API Reference

Overview

Basic Usage

Metric Types

Float Metrics

Boolean Metrics

Enum Metrics

Creating Metric Definitions

Linking Metrics to Prompts

Custom Timestamps

Response Object

Error Handling

Common Patterns

Pattern 1: User Feedback

Pattern 2: Conversion Tracking

Pattern 3: Email Campaign

Pattern 4: Multi-Metric Tracking

Pattern 5: Goroutine for Async Recording

Best Practices

Viewing Metrics

Next Steps