Customer Acquisition Cost (CAC) is the total cost it takes to acquire a new customer. CAC is calculated by dividing the total cost of acquiring a new customer by the number of new customers acquired during that time period.
CAC is a broad metric that is used to determine how much it costs your company to acquire a new customer. This metric is used to determine whether or not your company is spending too much money on acquiring new customers.
CAC is calculated on a per-customer basis, and is usually calculated on a monthly basis.
It can be difficult to calculate Customer Acquisition Cost directly inside of Google BigQuery; that's where Causal comes in.
Causal is a modelling tool which lets you build models on top of your Google BigQuery data. You simply connect Causal to your Google BigQuery account, and then you can build formulae in Causal to calculate your Customer Acquisition Cost.
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. 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.