analytics-strategy

Analytics Strategy

Design measurement frameworks that produce decisions, not just dashboards. Stack-agnostic. Tool-agnostic.

This skill is for measurement planning. For conversion optimization, use cro-optimization. For SEO measurement specifically, use seo-onpage and adjacent SEO skills.

When to use

• Setting up analytics on a new product or site
• Auditing existing analytics setup
• Designing dashboards for a team or business
• Defining KPIs and a north star metric
• Building event taxonomies for product analytics
• Designing attribution models for marketing
• Translating business questions into measurement plans

When NOT to use

• Conversion testing or optimization (use cro-optimization)
• SEO performance measurement (use SEO skills)
• Pure data infrastructure decisions (different domain)

Required inputs

• The business or product context (what does success look like)
• The audience for the analytics (who needs to make what decisions)
• The current measurement state (existing tools, tracking, gaps)
• The questions the team needs to answer

The framework: 4 layers

A complete measurement strategy covers all four. Each layer feeds the next.

1. North star and KPI hierarchy

The single metric that captures the most important outcome, plus the supporting metrics.

North star metric:

• One metric. Singular.
• Captures customer-perceived value.
• Leads to revenue, but isn't revenue itself (revenue is too far downstream).
• Examples: weekly active users, completed jobs, revenue-generating sessions, hours of value delivered.

Underneath the north star, the KPI hierarchy:

North star metric
├── Acquisition KPI (how new users enter)
├── Activation KPI (when new users get value)
├── Engagement KPI (how often users return)
├── Retention KPI (how many stick over time)
└── Monetization KPI (how value translates to revenue)

This is the "AARRR" or "pirate metrics" framework. It works because it covers the full lifecycle.