IntelliVerseX Analytics Pipeline

2. Event Taxonomy

Taxonomy Categories

Every event belongs to one of six categories following the category.action.detail naming convention:

Defining Event Schemas

using IntelliVerseX.Analytics;

IVXEventTaxonomy.Instance.DefineEvent(new EventSchema
{
    Name = "progression.level_complete",
    Category = EventCategory.Progression,
    RequiredMetadata = new[] { "level_id", "score" },
    OptionalMetadata = new[] { "time_sec", "hints_used", "stars" },
    MetadataTypes = new Dictionary<string, MetadataType>
    {
        { "level_id", MetadataType.String },
        { "score", MetadataType.Number },
        { "time_sec", MetadataType.Number },
        { "hints_used", MetadataType.Number },
        { "stars", MetadataType.Number },
    },
});

Tracking Events

IVXAnalyticsManager.Instance.Track("progression.level_complete", new Dictionary<string, string>
{
    { "level_id", "world_1_boss" },
    { "score", "12500" },
    { "time_sec", "142" },
    { "stars", "3" },
});

In Strict taxonomy mode, events without a registered schema are rejected and logged as warnings.

Validating Events (Development)

var result = IVXEventTaxonomy.Instance.Validate("progression.level_complete", metadata);
if (!result.Valid)
{
    Debug.LogWarning($"Event validation failed: {string.Join(", ", result.Errors)}");
}

3. Pre-Built Funnels

IVXFunnelBuilder

Define multi-step funnels and query conversion rates:

using IntelliVerseX.Analytics;

var onboardingFunnel = IVXFunnelBuilder.Create("onboarding")
    .Step("engagement.session_start")
    .Step("progression.tutorial_step", metadata => metadata["step"] == "1")
    .Step("progression.tutorial_step", metadata => metadata["step"] == "3")
    .Step("progression.tutorial_complete")
    .Step("monetization.first_purchase")
    .Build();

IVXAnalyticsManager.Instance.RegisterFunnel(onboardingFunnel);

Pre-Defined Funnel Templates

4. Cohort Analysis

IVXCohortTracker

Track retention cohorts by install date, acquisition source, or custom dimensions:

var tracker = IVXCohortTracker.Instance;

tracker.DefineCohort(new CohortDefinition
{
    Name = "jan_2026_installs",
    Dimension = CohortDimension.InstallDate,
    StartDate = new DateTime(2026, 1, 1),
    EndDate = new DateTime(2026, 1, 31),
});

tracker.DefineCohort(new CohortDefinition
{
    Name = "organic_users",
    Dimension = CohortDimension.Custom,
    Filter = (playerProfile) => playerProfile.AcquisitionSource == "organic",
});

Retention Metrics

var retention = await IVXCohortTracker.Instance.GetRetentionAsync("jan_2026_installs");

Debug.Log($"D1: {retention.D1:P1}");   // e.g. "D1: 45.2%"
Debug.Log($"D7: {retention.D7:P1}");   // e.g. "D7: 22.8%"
Debug.Log($"D30: {retention.D30:P1}"); // e.g. "D30: 8.1%"

LTV Projections

var ltv = await IVXCohortTracker.Instance.GetLTVAsync("jan_2026_installs", days: 180);

Debug.Log($"Predicted 180-day LTV: ${ltv.Predicted:F2}");
Debug.Log($"Current ARPU: ${ltv.CurrentARPU:F2}");
Debug.Log($"Paying user %: {ltv.PayerRate:P1}");

5. Data Lake Export

Export Targets

Configure export to external data warehouses:

using IntelliVerseX.Analytics;

IVXDataLakeManager.Instance.AddTarget(new DataLakeTarget
{
    Id = "main_bigquery",
    Type = DataLakeType.BigQuery,
    Config = new BigQueryConfig
    {
        ProjectId = "my-gcp-project",
        DatasetId = "game_analytics",
        CredentialsJson = SecureConfigService.GetKey("BQ_CREDENTIALS"),
    },
    EventFilters = new[] { "monetization.*", "progression.*" },
    Enabled = true,
});

Supported Targets

Manual Export

var result = await IVXDataLakeManager.Instance.ExportAsync(limit: 1000);
Debug.Log($"Exported {result.EventCount} events to {result.TargetCount} targets");

6. Dashboard Templates

Pre-built Satori metric definitions for common KPIs:

Setting Up Dashboards

await IVXAnalyticsDashboard.Instance.ProvisionAsync(DashboardTemplate.Executive);
await IVXAnalyticsDashboard.Instance.ProvisionAsync(DashboardTemplate.Monetization);

This creates the corresponding metric definitions and alert thresholds in Satori.

7. Alerts

Metric Alerts

Set up threshold-based alerts for critical metrics:

IVXAnalyticsAlerts.Instance.SetAlert(new MetricAlert
{
    Name = "crash_rate_spike",
    MetricId = "system.crash_free_rate",
    Operator = AlertOperator.LessThan,
    Threshold = 0.95,
    WebhookUrl = "https://hooks.slack.com/services/...",
});

IVXAnalyticsAlerts.Instance.SetAlert(new MetricAlert
{
    Name = "revenue_drop",
    MetricId = "monetization.daily_revenue",
    Operator = AlertOperator.LessThan,
    Threshold = 500.0,
    WebhookUrl = "https://hooks.slack.com/services/...",
});

8. Cross-Platform Event SDK

The same taxonomy and tracking API is available across all engines:

All platform SDKs route events to the same Satori backend, so cross-platform funnels and cohorts work automatically.

Platform-Specific Analytics

VR Platforms

Console Platforms

WebGL / Browser

Checklist

• EnableAnalytics toggled on in IVXBootstrapConfig
• IVXAnalyticsConfig created with appropriate taxonomy mode
• Core event schemas defined for your game's key actions
• FTUE funnel defined and tracking verified
• Monetization funnel defined and tracking verified
• Cohort definitions created for current install window
• Data lake export target configured (if using external warehouse)
• Executive dashboard provisioned with metric definitions
• Critical metric alerts configured (crash rate, revenue)
• Cross-platform event names verified to match across engines
• GDPR/privacy consent flow integrated before tracking begins
• VR comfort metrics added (if targeting VR)
• Console telemetry disclosure included in privacy policy (if targeting consoles)
• WebGL offline queue and ad-blocker fallback configured (if targeting browser)