Summer of Metrics: Average Lifetime Value

Lifetime Value, Customer Lifetime Value, and all of its ilk are often mixed up and misused.

The two big problems comes from calculating it differently in different places or calculating it as an average of averages. Both lead to problems.

The best way to think about Lifetime Value is the value of a single customer based on what they have spent with your company so far. Shopify calls this the Total Spent or Amount Spent (they keep renaming it). By using the actual amount spent and for a single customer, you side-step both of those problems.

This brings us to Average Lifetime Value (Average LTV) which is just the average of that metric. Or in basic words, how much an average customer spends with you.

Calculating Average Lifetime Value then becomes quite easy and doesn't have to get into messy statistics, AI, or machine learning. Just lots of addition and one division.

The nice thing about Average Lifetime Value is that is consolidates a lot of metrics into a single number that is very important to your business, how much revenue each customer will bring you.

Want to acquire another 100 customers per month? With Average LTV you can figure out how much revenue that'll bring in eventually.

Found an acquisition source but not sure if you can make a profit? Compare its costs and product costs to the Average LTV.

A problem with Average LTV is that while it accounts for all orders in a customer's lifetime, it doesn't tell you how long that'll be. If it takes 10 years to get $100 from the customer, you can't acquire them for $80/each without needing a deep war chest to survive the 10 years.

Another problem with Average LTV is that it constantly shifts as more orders and customers buy from you. You'd might not see rapid, major shifts but it will vary much more than Average Order Value or Customer Purchase Latency. That means you'd need to keep the calculation up-to-date, it's not a done-once-forever metric.

Eric Davis