Ultimate Guide to LTV Part 3: How to identify high LTV users

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The Ultimate Guide to LTV

Hey everyone! Welcome to part 3 of my Ultimate Guide to LTV where I go deep on all things LTV. In case you missed it, last week I shared how to increase LTV with 18 different tactics and this week I’ll share how to identify high value users.

1. How to calculate LTV

2. How to increase LTV 

3. How to identify high value users ← today

4. How to leverage LTV in Marketing *

*For paid subscribers only

Let’s go!

How to identify high value user

One of my favorite parts of writing my newsletter is breaking down supposedly complex problems and debunking myths. Today’s article is exactly that. It might seem like a challenging task to identify high value users but it’s much easier than you think. I’ll show you a step by step process that will help you identify and better understand your users so you can go get more of them. Let’s go!

Step 1: Segment high value users

When you hear segmentation, your body does 1 of 2 things: flight or fight.

How come “give it a hug” is never one of the options? That’s because we’ve been conditioned to hear “segmentation” and think it’s going to be a data sciency thing that’s complicated or useless. My approach to finding high value users is neither of those. In fact, it’s so easy a caveman can do it.

In part 1, I shared how to calculate LTV. Now, you take the assumptions you’ve made there (including costs and margins, etc.) and calculate that on a per user level:

1. Take total life time value and divide it by total revenue (ensuring the time frames for LTV and revenue are the same).

   You’ll get an LTV to Revenue multiplier (which will be < 1)

2. Then for every user, calculate their 1 year revenue

3. Apply the multiplier from step 1 to this revenue. Boom. Now you have LTV at the user level.

Bonus: what you really want to do is do it on a cohort / user level so you can account for adjusting marketing channel mix and fluctuations in marketing spend. If you understand how to do this then please calculate at a cohort level. Otherwise, the version I have above will generally work.

Now, sort users from highest LTV to lowest. Then draw a line under the top 10% of users. Anyone below that line gets “thrown away” aka ignore that data. Take this top 10% and let’s move on to the next step…

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