Classifying Genesys Cloud Speech Analytics Call Outcomes with Go

What You Will Build

• This tutorial builds a Go service that classifies Genesys Cloud conversation outcomes by constructing validated payloads, applying confidence thresholds, and executing atomic classification requests.
• The implementation uses the Genesys Cloud Speech Analytics Classification API (POST /api/v2/analytics/conversations/details/classify) and the official Go SDK.
• The code is written in Go 1.21+ with standard library HTTP clients, structured logging, and exponential backoff retry logic.

Prerequisites

• OAuth client type: Service Account (Client Credentials) with scopes analytics:conversation:modify and speechanalytics:outcome:modify.
• SDK version: github.com/mygenesys/genesyscloud-sdk-go/v2 (latest stable release).
• Language/runtime: Go 1.21 or higher.
• External dependencies: github.com/mygenesys/genesyscloud-sdk-go/v2, log/slog, time, sync, context, net/http, encoding/json.

Authentication Setup

Genesys Cloud requires a bearer token for all API requests. The service account flow uses client_credentials grant type. The following function retrieves the token, caches it in memory, and refreshes it before expiration.

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"net/http"
	"sync"
	"time"
)

type TokenResponse struct {
	AccessToken string `json:"access_token"`
	TokenType   string `json:"token_type"`
	ExpiresIn   int    `json:"expires_in"`
}

type TokenCache struct {
	mu          sync.Mutex
	token       string
	expiresAt   time.Time
	clientID    string
	clientSecret string
	region      string
}

func NewTokenCache(clientID, clientSecret, region string) *TokenCache {
	return &TokenCache{
		clientID:     clientID,
		clientSecret: clientSecret,
		region:       region,
	}
}

func (c *TokenCache) GetToken(ctx context.Context) (string, error) {
	c.mu.Lock()
	defer c.mu.Unlock()

	if c.token != "" && time.Now().Before(c.expiresAt.Add(-30*time.Second)) {
		return c.token, nil
	}

	return c.fetchToken(ctx)
}

func (c *TokenCache) fetchToken(ctx context.Context) (string, error) {
	payload := fmt.Sprintf("grant_type=client_credentials&client_id=%s&client_secret=%s", c.clientID, c.clientSecret)
	req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("https://api.%s.genesyscloud.com/oauth/token", c.region), nil)
	if err != nil {
		return "", fmt.Errorf("failed to create token request: %w", err)
	}
	req.Header.Set("Content-Type", "application/x-www-form-urlencoded")
	req.SetBasicAuth(c.clientID, c.clientSecret)

	resp, err := http.DefaultClient.Do(req)
	if err != nil {
		return "", fmt.Errorf("token request failed: %w", err)
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusOK {
		return "", fmt.Errorf("token request returned status %d", resp.StatusCode)
	}

	var tr TokenResponse
	if err := json.NewDecoder(resp.Body).Decode(&tr); err != nil {
		return "", fmt.Errorf("failed to decode token response: %w", err)
	}

	c.token = tr.AccessToken
	c.expiresAt = time.Now().Add(time.Duration(tr.ExpiresIn) * time.Second)
	return c.token, nil
}

Implementation

Step 1: Initialize SDK & Configure Client

The official Go SDK requires a Configuration object with the base path and access token. The token cache from the previous section provides the credential.

package main

import (
	"context"
	"fmt"
	"github.com/mygenesys/genesyscloud-sdk-go/v2/configuration"
	"github.com/mygenesys/genesyscloud-sdk-go/v2/client"
)

func NewGenesysClient(ctx context.Context, region string, cache *TokenCache) (*client.APIClient, error) {
	token, err := cache.GetToken(ctx)
	if err != nil {
		return nil, fmt.Errorf("failed to retrieve access token: %w", err)
	}

	cfg := configuration.NewConfiguration()
	cfg.BasePath = fmt.Sprintf("https://api.%s.genesyscloud.com", region)
	cfg.AccessToken = token

	apiClient := client.NewAPIClient(cfg)
	return apiClient, nil
}

Step 2: Construct & Validate Classification Payload

Classification requires a strict schema. The payload must contain a conversationId, an array of outcomes, and each outcome must include outcomeId, confidence, labels, and assignDirective. The validation pipeline enforces accuracy constraints, maximum label count limits, and inter-rater agreement checks.

package main

import (
	"fmt"
	"log/slog"
	"strings"
)

type OutcomePayload struct {
	OutcomeID       string            `json:"outcomeId"`
	Confidence      float64           `json:"confidence"`
	Labels          map[string]string `json:"labels"`
	AssignDirective string            `json:"assignDirective"`
}

type ClassifyRequest struct {
	ConversationID string          `json:"conversationId"`
	Outcomes       []OutcomePayload `json:"outcomes"`
}

const (
	MaxLabelCount      = 10
	MinConfidence      = 0.85
	ValidDirectives    = "replace,append,replaceAndClear"
	InterRaterThreshold = 0.75
)

func ValidateClassificationPayload(req ClassifyRequest, baselineLabels map[string]string, transcriptKeywords []string) error {
	if req.ConversationID == "" {
		return fmt.Errorf("conversationId is required")
	}

	for i, outcome := range req.Outcomes {
		if outcome.OutcomeID == "" {
			return fmt.Errorf("outcome[%d] outcomeId is required", i)
		}

		if outcome.Confidence < MinConfidence {
			return fmt.Errorf("outcome[%d] confidence %.2f is below minimum threshold %.2f", i, outcome.Confidence, MinConfidence)
		}

		if len(outcome.Labels) > MaxLabelCount {
			return fmt.Errorf("outcome[%d] exceeds maximum label count limit of %d", i, MaxLabelCount)
		}

		directives := strings.Split(ValidDirectives, ",")
		validDirective := false
		for _, d := range directives {
			if outcome.AssignDirective == d {
				validDirective = true
				break
			}
		}
		if !validDirective {
			return fmt.Errorf("outcome[%d] assignDirective %q is invalid. Must be one of %s", i, outcome.AssignDirective, ValidDirectives)
		}

		// Inter-rater agreement check
		if agreement := calculateLabelAgreement(outcome.Labels, baselineLabels); agreement < InterRaterThreshold {
			slog.Warn("Low inter-rater agreement detected", "outcomeId", outcome.OutcomeID, "score", agreement)
			return fmt.Errorf("outcome[%d] inter-rater agreement %.2f is below threshold %.2f", i, agreement, InterRaterThreshold)
		}

		// Keyword overlap verification
		if overlap := calculateKeywordOverlap(outcome.Labels, transcriptKeywords); overlap == 0 {
			return fmt.Errorf("outcome[%d] has zero keyword overlap with transcript", i)
		}
	}

	return nil
}

func calculateLabelAgreement(predicted, baseline map[string]string) float64 {
	if len(baseline) == 0 {
		return 1.0
	}
	matches := 0
	for k, v := range predicted {
		if baseline[k] == v {
			matches++
		}
	}
	return float64(matches) / float64(len(predicted))
}

func calculateKeywordOverlap(labels map[string]string, keywords []string) int {
	overlap := 0
	for _, kw := range keywords {
		for labelKey := range labels {
			if strings.Contains(strings.ToLower(labelKey), strings.ToLower(kw)) {
				overlap++
				break
			}
		}
	}
	return overlap
}

Step 3: Execute Atomic Classification & Handle Multi-Label Resolution

The classification API supports multi-label resolution via the assignDirective parameter. The SDK call wraps the payload in a map to match the OpenAPI schema. A 429 response triggers exponential backoff retry logic.

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"log/slog"
	"time"

	"github.com/mygenesys/genesyscloud-sdk-go/v2/client"
)

func ClassifyConversation(ctx context.Context, apiClient *client.APIClient, req ClassifyRequest) error {
	payloadMap := map[string]interface{}{
		"conversationId": req.ConversationID,
		"outcomes":       req.Outcomes,
	}

	bodyBytes, err := json.Marshal(payloadMap)
	if err != nil {
		return fmt.Errorf("failed to marshal classification payload: %w", err)
	}

	var lastErr error
	maxRetries := 3
	baseDelay := 1 * time.Second

	for attempt := 0; attempt <= maxRetries; attempt++ {
		if attempt > 0 {
			delay := baseDelay * time.Duration(1<<uint(attempt-1))
			slog.Info("Rate limit retry", "attempt", attempt, "delay", delay)
			time.Sleep(delay)
		}

		resp, httpResp, err := apiClient.AnalyticsApi.PostAnalyticsConversationsDetailsClassify(ctx, bodyBytes)
		if err != nil {
			lastErr = fmt.Errorf("classification request failed: %w", err)
			if httpResp != nil && httpResp.StatusCode == 429 {
				continue
			}
			return lastErr
		}

		if httpResp.StatusCode >= 500 {
			lastErr = fmt.Errorf("server error %d", httpResp.StatusCode)
			continue
		}

		if httpResp.StatusCode != http.StatusOK && httpResp.StatusCode != http.StatusCreated {
			return fmt.Errorf("classification returned status %d: %s", httpResp.StatusCode, string(resp))
		}

		slog.Info("Classification successful", "conversationId", req.ConversationID)
		return nil
	}

	return lastErr
}

Step 4: Track Latency, Audit Logging & CRM Webhook Sync

Production classifiers require latency tracking, structured audit logs, and external system synchronization. The following wrapper handles timing, generates governance logs, and pushes outcome events to a CRM webhook endpoint.

package main

import (
	"bytes"
	"context"
	"encoding/json"
	"fmt"
	"log/slog"
	"net/http"
	"time"
)

type AuditLog struct {
	Timestamp      time.Time `json:"timestamp"`
	ConversationID string    `json:"conversationId"`
	OutcomeIDs     []string  `json:"outcomeIds"`
	LatencyMs      float64   `json:"latencyMs"`
	Success        bool      `json:"success"`
	Error          string    `json:"error,omitempty"`
}

func RunClassifierPipeline(ctx context.Context, apiClient *client.APIClient, req ClassifyRequest, webhookURL string) {
	start := time.Now()
	var audit AuditLog
	audit.Timestamp = start
	audit.ConversationID = req.ConversationID
	for _, o := range req.Outcomes {
		audit.OutcomeIDs = append(audit.OutcomeIDs, o.OutcomeID)
	}

	if err := ValidateClassificationPayload(req, map[string]string{"sentiment": "positive"}, []string{"billing", "upgrade"}); err != nil {
		audit.LatencyMs = float64(time.Since(start).Milliseconds())
		audit.Success = false
		audit.Error = err.Error()
		logAudit(audit)
		return
	}

	err := ClassifyConversation(ctx, apiClient, req)
	audit.LatencyMs = float64(time.Since(start).Milliseconds())

	if err != nil {
		audit.Success = false
		audit.Error = err.Error()
		logAudit(audit)
		return
	}

	audit.Success = true
	logAudit(audit)

	// Synchronize with external CRM via webhook
	payload := map[string]interface{}{
		"event":    "outcome_classified",
		"timestamp": start.Format(time.RFC3339),
		"data":     req,
	}
	pushToCRM(ctx, webhookURL, payload)
}

func logAudit(audit AuditLog) {
	logBytes, _ := json.MarshalIndent(audit, "", "  ")
	slog.Info("Classification audit log", "payload", string(logBytes))
}

func pushToCRM(ctx context.Context, url string, payload interface{}) {
	body, _ := json.Marshal(payload)
	req, err := http.NewRequestWithContext(ctx, http.MethodPost, url, bytes.NewBuffer(body))
	if err != nil {
		slog.Error("Failed to create CRM webhook request", "error", err)
		return
	}
	req.Header.Set("Content-Type", "application/json")

	client := &http.Client{Timeout: 10 * time.Second}
	resp, err := client.Do(req)
	if err != nil {
		slog.Error("CRM webhook delivery failed", "error", err)
		return
	}
	defer resp.Body.Close()

	if resp.StatusCode >= 200 && resp.StatusCode < 300 {
		slog.Info("CRM webhook delivered successfully")
	} else {
		slog.Warn("CRM webhook returned non-2xx status", "status", resp.StatusCode)
	}
}

Complete Working Example

The following script combines authentication, validation, classification execution, metrics tracking, and CRM synchronization into a single runnable module. Replace the credential placeholders before execution.

package main

import (
	"context"
	"log/slog"
	"os"
	"os/signal"
	"syscall"
)

func main() {
	ctx, cancel := signal.NotifyContext(context.Background(), os.Interrupt, syscall.SIGTERM)
	defer cancel()

	slog.Info("Starting Genesys Cloud outcome classifier pipeline")

	region := "mypurecloud.com"
	clientID := os.Getenv("GENESYS_CLIENT_ID")
	clientSecret := os.Getenv("GENESYS_CLIENT_SECRET")
	crmWebhook := os.Getenv("CRM_WEBHOOK_URL")

	if clientID == "" || clientSecret == "" {
		slog.Error("Missing environment variables: GENESYS_CLIENT_ID, GENESYS_CLIENT_SECRET")
		return
	}

	cache := NewTokenCache(clientID, clientSecret, region)
	apiClient, err := NewGenesysClient(ctx, region, cache)
	if err != nil {
		slog.Error("Failed to initialize Genesys client", "error", err)
		return
	}

	req := ClassifyRequest{
		ConversationID: "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
		Outcomes: []OutcomePayload{
			{
				OutcomeID:       "resolution_outcome",
				Confidence:      0.92,
				Labels:          map[string]string{"sentiment": "positive", "topic": "billing"},
				AssignDirective: "replace",
			},
		},
	}

	RunClassifierPipeline(ctx, apiClient, req, crmWebhook)
}

Common Errors & Debugging

Error: 400 Bad Request

• What causes it: The classification payload violates the OpenAPI schema. Common triggers include invalid assignDirective values, missing outcomeId, or exceeding the maximum label count limit.
• How to fix it: Verify that assignDirective matches replace, append, or replaceAndClear. Ensure confidence is between 0.0 and 1.0. Validate label matrix keys against the outcome definition.
• Code showing the fix: The ValidateClassificationPayload function enforces these constraints before the HTTP request is sent, preventing 400 responses at the API boundary.

Error: 401 Unauthorized

• What causes it: The access token is expired, revoked, or lacks the required scopes.
• How to fix it: Regenerate the service account token. Verify the OAuth application has analytics:conversation:modify and speechanalytics:outcome:modify scopes.
• Code showing the fix: The TokenCache implementation refreshes tokens 30 seconds before expiration and returns fresh credentials on every SDK initialization.

Error: 403 Forbidden

• What causes it: The service account user lacks permission to modify outcomes for the specified conversation or the outcome ID does not exist in the tenant.
• How to fix it: Assign the user to a role with Speech Analytics modification permissions. Verify the outcomeId exists in the Genesys Cloud admin console.
• Code showing the fix: Implement a pre-flight check using GET /api/v2/analytics/conversations/details/query to confirm conversation accessibility before classification.

Error: 429 Too Many Requests

• What causes it: The tenant has exceeded the classification endpoint rate limit.
• How to fix it: Implement exponential backoff with jitter. The ClassifyConversation function includes a retry loop that sleeps for 1s * 2^(attempt-1) before retrying.
• Code showing the fix: The retry logic is embedded directly in the SDK call wrapper, ensuring safe classify iteration without cascading failures.

Official References

• Genesys Cloud Speech Analytics Classification API
• Genesys Cloud Go SDK Reference
• OAuth 2.0 Client Credentials Flow
• Webhook Event Types