measure-instrumentation-spec

Instrumentation Spec

An instrumentation spec defines what analytics events to track, when to fire them, and what properties to include. It serves as a contract between product and engineering, ensuring consistent data collection that enables accurate measurement. Good instrumentation specs prevent the "we can't answer that question because we didn't track it" problem.

When to Use

• Before engineering implements a new feature
• When defining analytics requirements for experiments
• When auditing existing tracking for gaps or inconsistencies
• When onboarding a new analytics tool
• Before launch to ensure measurement is in place

When NOT to Use

• You are specifying the dashboard built on top of the events -> use measure-dashboard-requirements
• You need experiment-specific metrics and variants, not product-wide tracking -> use measure-experiment-design
• The feature itself is not yet specified (no flows to instrument) -> use deliver-prd first
• You are analyzing data you already collect -> use measure-experiment-results or measure-survey-analysis

Instructions

When asked to create an instrumentation spec, follow these steps:

1. Define Analytics Goals Start with the questions you need to answer. What will you measure? What decisions will this data inform? This prevents over-instrumentation while ensuring nothing important is missed.

2. Identify Events to Track List each user action or system event that should be tracked. Follow consistent naming conventions (typically noun_verb or verb_noun in snake_case). Each event should represent a distinct, meaningful action.

3. Specify Event Triggers For each event, describe exactly when it fires. Be precise: "When user clicks Submit button" vs. "When form is submitted successfully." These are different events with different meanings.

4. Define Event Properties List the properties (attributes) attached to each event. Include property name, data type, description, and example values. Properties provide context that makes events useful.