Metric Guide

Contribution Margin


Contribution margin represents the difference between revenue and variable costs associated with producing a product or providing a service. It measures the amount of revenue that can be used to cover fixed costs like rent, insurance, utilities, and taxes. Thus, contribution margin is an important metric for understanding the overall profitability of a business as well as how much money can be allocated to other areas such as marketing or research and development.


The formula for calculating contribution margin is simple: Revenue - Variable Costs = Contribution Margin. So if a product has $$100 in revenue and $$90 in variable costs, the contribution margin would be $$10 ($$100 - $$90). This means that only $$10 out of every $$100 in sales will be left after paying off variable expenses like labor or raw materials. It also means that any additional sales beyond this point will provide additional profits for the company.


Break-even analysis helps businesses understand when their operations become profitable by measuring when expenses equal revenues. With break-even analysis, companies can determine their break-even point—the amount of sales needed to cover all expenses including both fixed and variable costs—and from there they can calculate their contribution margin ratio (CMR), which represents the portion of each dollar earned that goes towards covering fixed costs before any profit is made. A higher CMR indicates higher profitability because it means more money available before reaching break-even point; conversely, a lower CMR suggests lower profits since less money will remain after expenses are covered.

We're here to help!

Book a free consultation

We've helped hundreds of companies set up their data strategy

Schedule Now!

Metrics Frameworks

Modern Data Statck

Business Observability

Top 5 Metrics by Department

we're in Private beta

Get early access!

We're looking for Beta users to provide us feedback

Join Waitlist

Metrics Monitoring

Automated Insights

Business Observability