Revenue analytics and unit economics Intro to Unit Economics

103. Intro to Unit Economics

Queries for most of the metrics will follow two paths:

  • join all necessary tables (yep, sometimes more than 2) and then apply grouping and counting or grouping and summing
  • calculate counts or sums in separate tables/subqueries, join intermediate results into one table and calculate final metric

and we know how to do both of them now! It’s a smooth sailing from now on – we’ve learned the details of INNER JOIN ✅, LEFT JOIN ✅ and even CROSS JOIN ✅ ⛵

So far we’ve successfully calculated ROI. Of course it’s not the only metric that helps us understand our business. Further more – ROI is flawed in a way that it doesn’t look into the future and considers renewal purchases.

This is why the de facto standard to look at a business performance is Unit Economics.

Unit Economics

ROI looks at our marketing performance as a whole – all revenues and all marketing spend. Unit Economics looks at revenues and costs per unit. In case of Bindle and the vast majority of Internet companies Unit is a user or a customer.

Positive ROI is a synonym of profitability – we earned more than we’ve spent. In Unit Economics terms we’re profitable if our customers pay us more than we pay to acquire these customers. It is reflected in the two main metrics of Unit Economics:


Life Time Value is a total revenue a customer generates during the entire time using the product (before customer cancels a subscription).


On the other side the business invests money to acquire a customer through some form of marketing. Unit Economics would say that the business pays Customer Acquisition Cost.

If our LTV is higher than CAC – we’re doing great. If not – there’s a problem and we need to fix it asap. We already know how to find problems with data – we can calculate Unit Economics metrics per country/per age groups/per marketing campaign and find the segments that have positive Unit Economics and the ones we need to improve.


CAC and LTV are just two numbers and if CAC is bigger than LTV it’s quite hard to say where the problem is. When working with Unit Economics we can increase our resolution by looking at our marketing funnels. Let’s look at an example. When we’re running a campaign on Facebook or other marketing platform this is what happens:

  • we pay for the ad
  • X people on Facebook see the ad
  • Y people click the ad and go to our website or AppStore page
  • Z people sign up
  • N people purchase a subscription

Each step has its own conversion or metric that could help us identify the problem with our Unit Economics. These metrics will be our agenda for the rest of the chapter 🚀

Anatoli Makarevich, author of SQL Habit About SQL Habit

Hi, it’s Anatoli, the author of SQL Habit. 👋

SQL Habit is a course (or, as some of the students say, “business simulator”). It’s based on a story of a fictional startup called Bindle. You’ll play a role of their Data Analyst 📊 and solve real-life challenges from Business, Marketing, and Product Management.

SQL Habit course is made of bite-sized lessons (you’re looking at one atm) and exercises. They always have a real-life setting and detailed explanations. You can immediately apply everything you’ve learned at work. 🚀

“well worth the money”

Fluent in SQL in a month

Master Data Analysis with SQL with real life examples from Product Management, Marketing, Finance and more.
-- Type your query here, for example this one -- lists all records from users table: SELECT * FROM users
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