Annual Recurring Revenue (ARR) is the total amount of revenue that your company has generated from your existing customers in a given year.
ARR is calculated by adding up the total revenue from your customers in a given year, and then dividing that number by 12.
For example, if you have 100 customers in January of 2014, and you have collected $10,000 from them, your ARR is $10,000 / 12 = $833.33.
ARR is a very important metric for your company because it shows you how much revenue you're generating from your existing customers. This is a great metric to use when you're trying to determine whether or not your company is growing.
ARR is also a great metric to use when you're trying to determine whether or not your company is profitable. If your ARR is higher than your total revenue, then your company is profitable. If your ARR is lower than your total revenue, then your company is losing money.
It can be difficult to calculate Annual Recurring Revenue 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 Annual Recurring Revenue.
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 Annual Recurring Revenue. 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 Annual Recurring Revenue.