Mobile App Ad Spend Optimization Guide

The most important metrics for mobile apps and recurring revenue (SaaS) businesses are retention, cLTV and CAC. Both the Excel templates below offer powerful insights and frameworks for such businesses to use in order to better understand how much they can spend on ads as well how to calculate their primary KPIs. 


(Mobile App Version)
$45.00 USD


(SaaS Version)
$45.00 USD

The templates will be immediately available to download after purchase. This is included in the SaaS financial model template bundle.


ltv and cac

The user can enter their own historical data by monthly cohort. Once entered, the model will use that data to produce customer lifetime value and LTV to CaC outputs. Mobile apps have a different revenue profile than SaaS businesses and that is why there are two separate templates. For example, a SaaS business typically has users paying the same amount every month for as long as they are a customer. A mobile app usually has varying customer spend over time. Accounting for each correctly requires separate historical data inputs and data fitting.

The mobile app version is more complicated and, in that template, the user can enter historical cohort data for:
  • Customers left over time by cohort (up to 60 months' worth of data)
  • Revenue earned from each customer cohort over time.
  • Total cost to service each customer cohort over time (you can apply your gross margin average to derive this input)
The SaaS version is easier because the retention curve that best fits the historical data can simply be applied to the average gross recurring revenue per customer based on a few inputs and there is no need to account for varying customer spend over the customer life.
  • For the SaaS version, the user only needs to input the customers that existed over time by monthly cohort.
The model outputs the following data:
  • Present Value of Customer Lifetime Value
  • Average CaC
  • LTV to CaC Ratio
There are also sensitivity tables in both models that are designed to help the user understand how much they can spend on ads and at what point the customer LTV equals the average customer acquisition cost (essentially the break-even point).

Both versions also have the ability for the user to enter in their new data each month and use historical curves to estimate the LTV and LTV to CaC ratio over time.