The aspiring startup founder is bound to one-day face questions like what is a unit economy, what ARPU and CAC stand for, and why they should be calculated.
Working at the international early-stage VC, I've seen more than 500 unit economy calculations from the applying founders and worked directly with over 100 financial models to refine them. This experience makes me realize that there are a few things that early-stage startup founders need to know from the beginning.
To help would-be founders navigate the darkness-covered financial modeling environment, I've created this introductory guide to the unit economy.
The essence of unit economics is simple
It may seem that unit-economy calculation is extremely complicated and overloaded with formulas and incomprehensible abbreviations. But as a matter of fact, the essence of the financial modeling method can be summed up in one sentence:
"Unit economy characterizes how much income and expenses a business earns and spends for one user during all the time of using the product."
This gives a general impression of what stage of development the business is at.
A unit is a basic revenue-generating item. It can be a user, when the company sells services (games, apps), or a product when it sells goods, and both — buyers and sellers for the marketplaces.
Let's focus on services.
When we say that unit economics don't add up, it means that the cost of attracting users exceeds the revenue they generate. To prevent this from happening, the marketing team attracts users at a reasonable price.
Of course, there are market capture and burnout strategies, where customers are taken away from competitors at all costs. But such tools don't work in the long term. For most businesses, unit profitability is a constant that must be addressed.
Generally, a unit economy helps to understand:
amount of profit one user generates;
what is the price limit to attract new users;
how we can improve the indicators mentioned above.
All tech startup founders should implement at least simple financial reports from the very beginning to understand the dynamics. It should digitize all activities, including marketing and user acquisition.
How to calculate the most basic unit economy
Let's imagine there is a user named John. The cost of acquiring John is $10. A monthly subscription to your app is $2. John has to use the app for five months (10/2=5).
If John stays with a project for less, a project is a leaky bucket, and acquiring other Johns at that price is like pouring money down the drain.
Suppose John stays your user for 8 months. According to financial statements, the project with one user, John, is considered unprofitable for the first five months and then becomes unit-positive.
A startup should grow, attract new users, and do it as effectively as possible. Being financially unprofitable in the current month is fine for the tech startup. Investors are not interested in profits now, but the project must scale fast, keeping a positive unit.
Four important unit economy metrics
Let's decompose 4 mysterious unit economy metrics using John's easy-to-understand example with the same numbers.
Customer acquisition cost (CAC, $) — the cost of attracting one paying client. These can be marketing costs or referral program bonuses. It cost the startup $10 to acquire another John.
Average revenue per user (ARPU, $) — how much money one user brings in per month or per purchase. In other words, this is the monthly price for your product or service. John was paying $2 per month. When a startup has a different price for a different set of services and clients do not pay the same amount, the ARPU is counted as an average check.
Lifetime — how long the average user stays with the startup, uses service, buys products, etc. John stayed for 8 months, so his lifetime (for the startup) is 8 months.
Lifetime value (LTV, $) — how much one user will pay us for the whole time of using the product or service. It is calculated as ARPU multiplied by the Lifetime. In John's case, 8*2 = $16.
The main principle of the profitable unit economy: LTV should be higher than CAC.
How to count users who churn
From the moment a John sees an ad until paying $2 to use the app or service, he'll go through several steps:
Downloading your app / opening your website.
Onboarding (registration, creating an account).
Signing up for a free trial (if there's any).
Purchase (one-time payment or subscription).
When passing from one stage to another, some users will churn because of different reasons. They might not understand how to use the service, dislike it, or just change their mind. The term conversion stands for the percentage of users who pass on through the onboarding funnel.
Let's break things down with an example.
After the advertising campaign, application N was downloaded by 1,000 users, and 5% of them installed a free trial version (it's 50 people). Out of those 50 people, 10% installed a paid subscription (it’s 5 people). Conversion rates here are 5% and 10%.
Let's imagine that you have paid $1,000 for 1,000 downloads. What would be the customer acquisition cost (CAC)?
No, it is not $1. To come up with CAC, we should include only paying users who generate income. That's 5 people who installed a paid subscription.
The real cost of attracting a paying user is $200. Is it a reasonable price? If it’s lower than LTV, yes. If no, then you should fix that.
One of the fundamental product managers’ tasks is to look for tips and approaches that help increase conversions. After all, even small improvements to the funnel can bring significant results.
The most important thing at this stage is to understand the reasons why potential users don't become paying clients and fix the problems such as bugs, payment issues, registration forms, etc.
Let's imagine that we found and fixed a certain number of problems that users had with app N. The conversion funnel changed by 1 percentage point, from 5% to 6% and from 10% to 11%. The cost of attracting one subscriber would drop by 25% and cost $150, instead of $200.
Three additional income calculating factors
In the example above, we calculated John's ARPU (average bill) based on a monthly subscription price of $2. However, in practice, it is more complicated and the profit cannot be calculated just by multiplying the subscription price by the number of users.
At the very least, there are 3 additional factors to consider:
Refunds & chargebacks. If users dislike the service, they might demand refunds. On average, it's 5% of payments, but if the product has an expensive subscription, the percentage of refunds can be higher. The main thing is that this percentage should not exceed 12% — this is a red flag for Apple to think the developer might be an unfair seller.
Commissions from app stores and payment systems. It is important to consider all the extra costs that third-party service providers require. For example, if you sell a subscription in App Store, you'll be charged a 30% commission.
Cost, packaging, and delivery. If your service involves the physical movement of any objects, the costs are accounted for here, including packaging, couriers, transportation, and fuel expenses.
Building a financial model is like car headlights in the middle of the night. The car may be moving without them. But in this case, the direction will be unknown. You may discover yourself driving into the tree because you have no idea how much a business earns, spends, and disposes of.
For anyone starting out on their own path to building a global tech startup, 4 basic metrics are enough for a general understanding of what the unit economy is all about.
Further, CAC, ARPU, Lifetime, and LTV are divided into many components, allowing to make forecasts and analyses of the quality indicators of business development.
Tech startup founders need to understand the net profit, which can be used to pay for all fixed costs and reinvest further. Knowledge of statistics, probability theory, and mathematics open up a lot of opportunities for business growth.
This story originally appeared on HackerNoon titled "Introductory Guide to Unit Economics and Financial Modeling for Early-Stage Tech Startups."
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