Metric Component Analysis: Complex Metrics

This is part 5 of our series on Metric Component Analysis, previous segments are available in our archives.

Even More Complex Metrics

This week we’ve covered how to break down various types of metrics, including sums, means and medians. You will, of course, have some metrics that are more complex and are harder to break down into their components.

For example, churn is a difficult metric to calculate because there are many different factors involved. A typical calculation of churn [1] might look like the following:

churnUnsurprisingly, many companies struggle to break their churn down into components and hence have trouble doing further analysis on what is driving churn. While I cannot give you any single method to break down these metrics, as it depends on how you calculate them, there are some common lessons you can apply.

  • Think in Components. Everything in your business is built of components, including your metrics. Use your intuition to help identify the components that should comprise your complex metrics and then determine how to break them down into those components. If you know what you are looking for, it’ll be easier to find.
  • Represent Metrics as Series. You’ve probably noticed that this week I’ve used a series representation for each metric calculation. This is not a coincidence, if you can transform a metric formula into a mathematical series it will get easier to break them down into components.
  • Track Populations. If you only track metric values, but not the populations represented by different customer segments, it may be hard or impossible to break down your metrics into components. As we have seen this week, sometimes the population is the most important factor you’ll have in your breakdown.

Easy, right? Nothing to it.

Hey, wait a second…

Okay, maybe we aren’t finished yet. This week we’ve only covered how to break down metrics into components. It’s been quite convenient that I always knew exactly what dimensions to use when breaking down our metric to find the right answers! In practice, the hardest part of understanding metric drivers is identifying those dimensions.

Next week we will dive into methods to do exactly that. They can get complex, but all of our detective work from this week should have you ready to tackle harder cases!

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.


[1] Churn calculations are so complex we’ll cover a variety of them in the coming weeks. However, if you don’t want to wait I recommend this blog post about different ways to calculate churn.


Quote of the Day: “A question that sometimes drives me hazy: am I or are the others crazy?” ― Albert Einstein