# How to Calculate Lifetime Value per Customer in Sage Intacct

## What is Lifetime Value per Customer?

Lifetime Value per Customer (LTV/C) is the amount of revenue a customer will bring in over the course of their lifetime with your company.

LTV/C is calculated by taking the total revenue a customer brings in over their lifetime with your company, and dividing it by the cost of acquiring that customer.

LTV/C is a very important metric because it shows you how much money you can expect to make from each of your customers. It's a good idea to track your LTV/C on a monthly basis and compare it to your net revenue retention.

If your LTV/C is higher than your net revenue retention, it means that you're making more money from your existing customers than you are losing from customers who churn.

If your LTV/C is lower than your net revenue retention, it means that you're losing more money from customers who churn than you are making from customers who stay.

## How do you calculate Lifetime Value per Customer in Sage Intacct?

It can be difficult to calculate Lifetime Value per Customer directly inside of Sage Intacct; that's where Causal comes in.

Causal is a modelling tool which lets you build models on top of your Sage Intacct data. You simply connect Causal to your Sage Intacct account, and then you can build formulae in Causal to calculate your Lifetime Value per Customer.

## What is Causal?

Causal lets you build models effortlessly and share them with interactive, visual dashboards that everyone will understand.

In Causal, you build your models out of variables, which you can then link together in simple plain-English formulae to calculate metrics like Lifetime Value per Customer. This makes your models easy to understand and quick to build, so you can spend minutes, not days, on your models.

When you're done, you can share the link to your model with stakeholders. They'll be able to view your model's outputs in a visual dashboard, rather than a jumble of tabs and complex formulae. The dashboards are interactive, letting viewers tweak your assumptions to see how they affect the model's outputs.

Causal lets you add visuals in a single click, letting you plot out graphs and distributions for metrics like Lifetime Value per Customer.

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