Event Tracking
A method of recording specific user actions like clicks, page views, and form submissions to understand behavior patterns in analytics platforms.
Definition
Event tracking captures specific user actions within a product - clicks, form submissions, feature usage, purchases, and other interactions. Events form the foundation of product analytics, enabling teams to understand what users actually do.
Event Structure
Events typically include:
| Component | Example |
|---|---|
| Event name | button_clicked, purchase_completed |
| Timestamp | When the action occurred |
| User ID | Who performed the action |
| Properties | Additional context (button_name, amount, etc.) |
Common Event Types
User Actions
signup_completedfeature_useditem_added_to_cartsearch_performed
System Events
page_viewedsession_startederror_occurred
Event Tracking Approaches
| Approach | Pros | Cons |
|---|---|---|
| Manual instrumentation | Precise control, clean data | Developer time required |
| Auto-capture | Quick setup, comprehensive | Noisy data, privacy concerns |
| Hybrid | Balance of both | More complex to maintain |
Tools for Event Tracking
Analytics platforms with event tracking:
- Mixpanel - Event-centric analytics with powerful querying
- Amplitude - Behavioral analytics with event schemas
- PostHog - Open-source with auto-capture option
Frequently Asked Questions
How many events should I track?
Start with 10-20 core events that map to your key user journeys. Add more as you identify specific questions to answer. Too many events creates noise; too few limits insight.
Should I use auto-capture or manual tracking?
Manual tracking gives cleaner, more intentional data. Auto-capture is faster to implement but requires filtering. Many teams use auto-capture initially, then add manual tracking for critical flows.
How do I name events consistently?
Use a naming convention like object_action (e.g., button_clicked, form_submitted). Document your schema. Some tools enforce schemas to prevent inconsistency.