Customer Lifetime Value (CLV) is the total amount of revenue that a customer is expected to generate over the course of his or her relationship with your company.
CLV is calculated by taking the average revenue per customer and multiplying it by the average customer lifetime.
For example, if your average customer generates $100 in revenue during his or her lifetime, and your average customer lifetime is 3 years, then your customer lifetime value is $300.
CLV is a very important metric because it helps you determine how much you should spend to acquire a new customer. It also helps you determine how much you should spend to keep a customer happy.
If you know that a customer is worth $300 over the course of his or her lifetime, you might be willing to spend $50 to acquire that customer. If you know that a customer is worth $10,000 over the course of his or her lifetime, you might be willing to spend $1,000 to keep that customer happy.
It can be difficult to calculate Customer Lifetime Value directly inside of NetSuite; that's where Causal comes in.
Causal is a modelling tool which lets you build models on top of your NetSuite data. You simply connect Causal to your NetSuite account, and then you can build formulae in Causal to calculate your Customer Lifetime Value.
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 Customer Lifetime Value. 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 Customer Lifetime Value.