Metric Component Analysis
Quick, what was your total revenue last month? I’m sure you were able to answer that question; understanding your Key Performance Indicators (KPIs) is one of the first steps in using data to make better decisions. Metrics like total revenue, revenue growth and gross margins are the basic tools of running a business.
However, few companies can list what the primary drivers were of those metrics. Which customer segments contributed the most to revenue growth? Which products had the highest gross margins in the past two months? What segments are most likely to reduce total revenue this month? The answers to these questions are the drivers of your metrics, but finding those answers can feel like trying to solve a mystery.
Understanding the drivers of your metrics is known as component analysis . The components for your metrics are all of the different dimensions and customer segments you can use to break down the metric, such as Revenue by Country and Gross Margin by Product. Even a moderately sized business may have dozens of dimensions and hence hundreds of components, which can make component analysis difficult. Luckily, we can help you improve your detective skills and find the answers more quickly!
This topic is complex, so it will take two weeks to cover everything. We’ll start this week by understanding how to break down metrics into their components which we’ll then analyze next week to find drivers. Specifically we will cover:
- Part 2 – The Case of the Missing Revenue (Sum Metrics)
- Part 3 – The Case of the Lower Conversions (Mean Metrics)
- Part 4 – The Case of the Disappearing Users (Median Metrics)
- Part 5 – Even More Complex Metrics
Tomorrow we will get started by trying to solve The Case of the Missing Revenue!
Do you do look for metric drivers in your business? Outlier is a product designed to help! Outlier looks deep into the dimensions of your data to identify the drivers and emerging trends that result in changes to your main KPIs. If you’re interested in seeing a demo, schedule a time to talk to us.
 Principal Component Analysis, which you may have heard of already, refers to a specific statistical technique for automatically extracting the primary drivers of a given data set. We’ll cover that next week..
Quote of the Day: “We’ve taken the world apart but we have no idea what to do with the pieces.” ― Chuck Palahniuk