analytics-interpretation

Analyze app performance metrics and generate data-driven recommendations.

Updated Mar 15, 2026
One-click install
npx skills add https://github.com/jtvaris/sunday-night-dynasty --skill analytics-interpretation-jtvaris
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: analytics-interpretation
Source: https://github.com/jtvaris/sunday-night-dynasty/tree/main/.agents/skills/growth/analytics-interpretation
Command: npx skills add https://github.com/jtvaris/sunday-night-dynasty --skill analytics-interpretation-jtvaris

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Interpret and translate complex app metrics into actionable growth insights, enabling data-driven decisions.

Core Features & Use Cases

  • Analyze DAU/MAU, retention, LTV, ARPU, and funnel health to diagnose growth blockers.
  • Compare App Store Connect analytics with third-party data or raw numbers to surface actionable strategies.
  • Produce diagnostic decision trees and cohort analyses to inform a data-driven growth plan.

Quick Start

Provide your app metrics data and I will generate an interpretation and a practical growth plan.

Frequently Asked Questions about analytics-interpretation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I interpret app metrics like DAU, MAU, and retention to find growth blockers?

Interpret app metrics by analyzing DAU, MAU, retention, LTV, and ARPU to diagnose growth blockers. This process translates complex performance data into a structured analytics health report with visualizable trends and actionable next steps for data-driven decisions.

What is the best way to analyze cohort analysis data for app retention scenarios?

The best way to analyze cohort analysis data is to produce diagnostic decision trees that compare App Store Connect analytics with third-party data. This surfaces actionable strategies and informs a comprehensive, data-driven growth plan for retention scenarios.

Can I use raw app numbers instead of App Store Connect analytics to generate a growth plan?

Yes, you can use raw app numbers. The analysis accepts App Store Connect analytics, third-party analytics, or raw numbers provided by you across onboarding, retention, and monetization scenarios to deliver a structured analytics health report.

How does funnel health analysis translate into actionable recommendations for app monetization?

Funnel health analysis translates into actionable recommendations by diagnosing drop-offs across onboarding, retention, and monetization scenarios. It generates a structured health report with defined metrics, visualizable trends, and practical next steps to improve app monetization.

Why do I need a diagnostic decision tree for my app's LTV and ARPU metrics?

You need a diagnostic decision tree for LTV and ARPU metrics to systematically diagnose growth blockers. It compares your data sources and surfaces actionable strategies, turning raw performance numbers into a structured, data-driven growth plan.