Lifetime Value Part 11: How to calculate LTV

Last year, I published a series of posts on the importance of knowing your users’ or players’ lifetime value, the key components and how to impact them and techniques to increase the accuracy of your customer lifetime value (LTV) predictions. I intentionally did not publish a formula for calculating LTV—while it is always a factor of retention, monetization and virality—as it is different by product and there are many alternative ways to get to an accurate customer lifetime value. Prompted by an infographic that I came across (see below) I did want to go into some details of the mechanics of calculating LTV.

The first step is to obtain your key variable metrics as averages across all users. The ones I prefer are ARPDAU (average revenue per daily active user), day 1 retention (how many people who use or install your website, app or game come back the next day), day 30 retention and k-score (how many free/organic users does a user bring in). Continue reading “Lifetime Value Part 11: How to calculate LTV”