product-analytics

Product Analytics

Overview

This skill covers designing and implementing product analytics systems that provide actionable insights into user behavior. It addresses event taxonomy design, analytics SDK integration with major platforms (PostHog, Amplitude, Mixpanel, Segment), funnel and cohort analysis, A/B testing and feature flags, user journey mapping, GDPR-compliant consent management, and custom metric definitions.

Use this skill when adding analytics to a new product, redesigning an event tracking system, setting up A/B testing infrastructure, implementing consent management, or building custom dashboards for product teams.

---

Core Principles

1. Design the taxonomy before writing code - A well-designed event naming convention and property schema prevents the #1 analytics failure: inconsistent, unqueryable data. Agree on naming conventions first.
2. Track actions, not pages - Page views tell you where users went. Events with context tell you what users did and why. Focus on user actions: project_created, file_uploaded, subscription_upgraded.
3. Identify before you track - Every event needs a user identity. Anonymous events before signup should be linked to the authenticated identity once the user logs in (alias/merge).
4. Consent is mandatory - GDPR and CCPA require explicit user consent before tracking. Build consent management into the analytics layer, not as an afterthought.
5. Less is more - Tracking everything creates noise. Track the events that answer specific product questions. You can always add events later; removing noise from existing data is much harder.

---

Key Patterns

Pattern 1: Event Taxonomy Design

When to use: Before implementing any analytics tracking. This is the foundation everything else builds on.

Implementation:

// Event taxonomy schema
// Convention: object_action (noun_verb in past tense)

// Core event types
type AnalyticsEvent =
  // Authentication
  | { event: "user_signed_up"; properties: { method: "email" | "google" | "github"; referralSource?: string } }
  | { event: "user_logged_in"; properties: { method: "email" | "google" | "github" } }
  | { event: "user_logged_out"; properties: Record<string, never> }

  // Onboarding
  | { event: "onboarding_started"; properties: { variant?: string } }
  | { event: "onboarding_step_completed"; properties: { step: number; stepName: string } }
  | { event: "onboarding_completed"; properties: { durationSeconds: number } }
  | { event: "onboarding_skipped"; properties: { lastStep: number } }

  // Core product actions
  | { event: "project_created"; properties: { template?: string; source: "dashboard" | "onboarding" | "api" } }
  | { event: "project_deleted"; properties: { projectAge: number; itemCount: number } }
  | { event: "file_uploaded"; properties: { fileType: string; fileSizeBytes: number; source: "drag_drop" | "file_picker" | "api" } }

  // Subscription
  | { event: "subscription_started"; properties: { plan: string; billingCycle: "monthly" | "annual"; amount: number } }
  | { event: "subscription_upgraded"; properties: { fromPlan: string; toPlan: string } }
  | { event: "subscription_cancelled"; properties: { reason?: string; plan: string; tenureDays: number } }

  // Feature engagement
  | { event: "feature_used"; properties: { feature: string; context: string } }
  | { event: "search_performed"; properties: { query: string; resultCount: number; source: string } }
  | { event: "export_completed"; properties: { format: "csv" | "pdf" | "json"; itemCount: number } };

// Type-safe tracking function
function track<T extends AnalyticsEvent>(
  event: T["event"],
  properties: T["properties"]
): void {
  // Implementation below
}

// Usage - fully typed, autocomplete works
track("project_created", {
  template: "blank",
  source: "dashboard",
});