Metric Analysis Toolkit: Driver Trees & Diagnostic Algorithms
🔍 What is it?
A powerful analytical toolkit designed for e-commerce professionals, consultants, and analysts who want to understand, diagnose, and improve key business metrics. This product includes Driver Trees and Metric Analysis Algorithms, structured to provide clear insights and actionable strategies.
📖 How Does It Work?
Driver Trees = Diagnostic Maps
Driver Trees break down a key metric (e.g., LTV) into its components and drivers, showing how different factors influence it. Think of them as maps that highlight where to look when diagnosing performance issues.
Diagnostic Algorithms = Investigation Tools
Diagnostic Algorithms use the Driver Tree as a guide to systematically analyze metric changes, identify root causes, and suggest corrective actions. They turn insights into a clear step-by-step process for problem-solving.
- Driver Trees define what to check.
- Diagnostic Algorithms show how to investigate and fix issues.
Together, they provide a structured, actionable approach to metric analysis 🚀
📦 What’s Inside?
Metric Analysis Algorithms – step-by-step diagnostic flows that help identify causes of metric changes and suggest corrective actions:
- Conversion Rate (CR)
- Average Revenue per Customer (ARPC)
- Average Order Value (AOV)
- Customer Lifetime Value (LTV)
Driver Trees – structured breakdowns of key metrics into influencing factors and actionable drivers, making it easier to pinpoint opportunities for improvement:
- Conversion Rate (CR)
- Average Revenue per Customer (ARPC)
- Average Order Value (AOV)
- Customer Lifetime Value (LTV)
- Add to Cart Rate (ATC rate)
- Inventory Management
- Logistics Performance
🎯 Who is it for?
- E-commerce store owners & operators – optimize revenue and efficiency
- Marketing & growth teams – diagnose and improve conversion metrics
- Consultants & analysts – enhance decision-making with structured frameworks
📌 How to Use It?
- Run the Diagnostic Algorithm – Select the metric, follow the step-by-step checks, and pinpoint the root cause of changes.
- Use the Driver Tree – Once you've identified the problematic driver or component, explore detailed hypotheses and action steps to test solutions.
- Implement & Optimize – Apply insights, make data-driven changes, and track improvements over time.
🚀 What you get?
✅ Clear diagnosis – Quickly find the real cause of metric shifts.
✅ Structured action plan – Go beyond surface-level fixes with targeted hypotheses.
✅ Faster decision-making – Solve problems efficiently and optimize performance.
📑 Access & Usage
All materials are available in a single Miro board with easy copying and customization. You can use them as standalone resources or combine them for a comprehensive performance optimization approach.