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How to Calculate Revenue per Active User in Google BigQuery

Making the most of your Google BigQuery data

What is Revenue per Active User?

Revenue per Active User (RPU) is the average revenue generated by each of your active users.

Revenue per Active User is calculated by dividing the total revenue generated by your company by the number of active users.

Revenue per Active User is a good indicator of how much revenue your company is generating per customer. If your company is generating $10,000 in revenue per active user, you know that your customers are spending a lot of money with your company.

Revenue per Active User is also a good indicator of how much money your company is making from its customers. If your company is generating $10,000 in revenue per active user, and you have 100 active users, you know that your company is making $1 million in revenue.

How do you calculate Revenue per Active User in Google BigQuery?

It can be difficult to calculate Revenue per Active User 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 Revenue per Active User.

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 Revenue per Active User. This makes your models easy to understand and quick to build, so you can spend minutes, not days, on your models.

A comparison of formulae in Excel and Causal

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.

A gif showing how users can adjust model inputs, and how they're reflected in dashboards

Causal lets you add visuals in a single click, letting you plot out graphs and distributions for metrics like Revenue per Active User.

A gif showing how you can build visuals in Causal

Start building models with your 

Google BigQuery

 data

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