Customer Acquisition Cost (CAC) is the amount of money it takes to acquire a new customer. CAC is calculated by dividing the total amount of money spent on customer acquisition by the number of customers acquired.
For example, if your company spends $100,000 on customer acquisition and you acquire 100 customers, your CAC is $1,000.
CAC is a great metric to track because it helps you to understand how much money you're spending to acquire a customer. If your CAC is too high, you might want to consider changing your customer acquisition strategy.
CAC is calculated on a per-lead basis. This means that if your company spends $100,000 on customer acquisition and you acquire 100 customers, your CAC is $1,000. However, if your company spends $100,000 on customer acquisition and you acquire 200 customers, your CAC is $500.
It can be difficult to calculate Customer Acquisition Cost per Lead directly inside of Stripe; that's where Causal comes in.
Causal is a modelling tool which lets you build models on top of your Stripe data. You simply connect Causal to your Stripe account, and then you can build formulae in Causal to calculate your Customer Acquisition Cost per Lead.
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 Acquisition Cost per Lead. 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 Acquisition Cost per Lead.