Margin is the difference between a company's revenue and its costs. Margin is expressed as a percentage of revenue.
For example, if a company has $1,000,000 in revenue and $500,000 in costs, its margin is 50%.
Margin is an important metric because it tells you how much money your company is making. If your company is making a lot of money, it's a good sign. If your company is not making much money, it's a bad sign.
For example, if your company has $1,000,000 in revenue and $1,000,000 in costs, your margin is 0%. This is a bad sign because your company is not making any money.
If your company has $1,000,000 in revenue and $500,000 in costs, your margin is 50%. This is a good sign because your company is making a lot of money.
It can be difficult to calculate Margin 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 Margin.
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 Margin. 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 Margin.