What are Unit Economics?

In startups you don’t have stable financial statements to make decisions with based off, nor a lot of history to compare with.  Assessing a startup based on sales growth or profitability can often be meaningless when trying to make decisions on where to spend your next dollar, cut costs or employ new people.  It’s often necessary to break down the financial statements into relevant, useful, actionable data.


Unit economics involves breaking down the financial numbers to a per unit basis rather than a simple dollar value. A unit doesn’t always have to be a customer, this can be per salesperson, company employee or even events such as trade shows or individual contracts.


An example of Unit Economics is Lifetime Value of a Customer (“LTV") and Cost to Acquire a Customer (CAC).  


LTV: Average Revenue per Customer / Customer Lifetime

CAC: Sales & Marketing Costs / New Customers


In a successful business the lifetime value of a customer will be many times the cost to acquire.  These metrics can be important to monitor in the early stages of your business to determine if your business model is correct, and that the assumptions you make will leave to eventual profitability.


Unit Economics provides a smell test for your business model.


Board members who are not working in the business day to day need reassurance on at least a quarterly basis that the business model strategy is financially viable.  Breaking down your financials into a per unit basis helps your advisors to see that although you are burning through cash, you will eventually make lots of money.


Unit economics are also helpful when building your 3-5 year forecast model.  Year on year revenue increases of 100%-200% cannot be assumed just because you will be in business next year.  Revenue and costs need to be backed up with at least one level of detail.  Using Unit Economics in your forecasting process also allows you to determine where you went right/wrong once actual financial data is available.  You can determine if your assumptions are correct or not and what impact that will have on the future direction of your startup.


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