## 2014/02/07

### LTV > CPI - a quick & dirty approach to calculate LTV This is a five minute note about how to calculate mobile app LTV of a specific cohort

Number of total acquired users = 600

Number of churned users per day. This can be found out via Churnrate = 1- retention rate
Day 1 --> 100
Day 2 --> 200
Day 3 --> 300

We assume they churn at the end of the day and that every user that does not churn is active on each day.
(free pic under CC)
Therefore number of days active or DAU is the following
Day 1 --> 100
Day 2 --> 400
Day 3 --> 900

Total days on which users have been active is therefore 1400 days (which equals DAU)

We assume that ehe sum of total revenues on those three days 140 €

Therefore ARPDAU = Revenues / DAU = 0.10cents

Average Life Time (LT) = Total days active / total users = 1400/600 = 2.3

LTV = average LT * ARPDAU = 2.3* 0.1cents = 23 cents

If we assume that 23 cents is excluding VAT (gross revenues) we have to deduct appstore fee
the net LTV is 16 cents

LTV > CPI (cost per install) is actually not quite ok, because we have to include a certain margin based on your costs

Based on current CPI's at ~ 2-3 \$ or Euro, this seems unrealistic. What are solutions?

Virality
In case the game is viral or gets featured by Google / Apple by a factor of 6 , then LTV in theory goes to 1.40€. If you are able to meet a net LTV of 1€ then fine

Getting featured
This is a no brainer

Push Campaigns
Has been discussed many times. Problem is the incentivized installs f*ck your stats

This means you are able to target those users which have a high LTV. There are certain companies that label this user acquisition strategy as "predictive LTV". We will see how it pans out