Cost per Transaction is the average cost of a single transaction. This is calculated by dividing the total cost of all transactions by the total number of transactions.
For example, if you had 100 transactions and your total cost was $1,000, your cost per transaction would be $10.
Cost per transaction is an important metric to track because it allows you to determine how much it costs your company to acquire a new customer. If you have a high cost per transaction, you'll want to figure out why and take steps to reduce it.
If you have a low cost per transaction, you'll want to figure out why and take steps to increase it.
It can be difficult to calculate Cost per Transaction 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 Cost per Transaction.
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 Cost per Transaction. 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 Cost per Transaction.