My first job after a couple of years crunching numbers at Goldman Sachs was “Performance Marketing Manager” at Storm8, a mobile gaming company.
My first thought was “Why am I doing this? I don’t play mobile games...”
And my second thought was “Marketing? But my background is in Finance…”
Little did I know that this job was my introductory course into Unit Economics, a concept so important for building and running a tech company.
I’ve learned how to manage a $10mn annual ad budget profitably simply by understanding the fundamentals of CAC (Cost per Acquired Customer), LTV (Life Time Value per Customer), and ROI% (Return on Investment).
The days when investors overlooked profitability in favor of hypergrowth are behind us.
It is crucial for startup founders to understand their business’ unit economics, not just to fundraise successfully (or to avoid the need to fundraise), but to build a scalable and sustainable company that can survive the hard critique of public investors at the IPO stage.
How do I calculate cost per acquired customer (CAC)?
At the high-concept level:
- CAC = Total Sales & Marketing Costs / Total Customers Acquired
Sounds simple enough right? In reality, this calculation actually requires you to track and measure your customers’ journey carefully.
Why? It’s because customers find your product via different channels. Some find you organically, some click on a Facebook ad, some click on a Google search ad, and maybe some come in through a friend referral to redeem their discount.
That’s why at Hustle Fund, we always recommend our founders make sure their analytics tools are integrated correctly and early.
Let’s take a look at some examples for a mobile gaming app:
Organic Downloads: These are the customers that find you “organically”, or in other words, they cannot be attributed to paid advertising channels.
For the sake of simplicity, we will consider these customers “free”, even though there are hidden costs such as the effort your Product Managers put into App Store Optimization, SEO, or PR.
Paid ads (e.g. Google ads, Facebook ads): Here is where you’ll need to attribute the downloads and track the journey of these prospective customers to really get to the CAC.
For example, you run a $10,000 Facebook campaign. Your campaign was able to deliver at $10 CPM (cost per thousand impressions).
You might think that’s great because that means you got 1,000,000 impressions (anything in the millions sounds impressive right?)
But no, you can’t stop there and pat yourself in the back. You need to follow these impressions, to see how many people click your ads (CTR) and how many people actually download the app (CVR).
Let’s say your CTR is 5% (5% of people who see the ads click on it) and your CVR from clicks is 10% (10% of people who land on the app store listing installed your app).
- Total Installs = 1,000,000 impressions x 5% CTR x 10% CVR = 5,000
Mobile game business models are often “freemium” - free to download but you can pay for certain features to advance faster. Let’s say this is the first game you released so you don’t know what % of users actually pay.
You look up some industry data and see that similar games like yours have 50% paying customers.
- Paying customers = 5,000 downloads x 50% = 2,500
- CAC = $10,000 ad spend / 2,500 paying customers = $4.00
You can apply this same exercise across all of your advertising channels to get to the average CAC for your business (a useful metric to share with investors).
However, it’s important to track and measure each advertising channel separately in order to optimize for ad spend and ROI%.
After all, if you don't understand the differences in CAC across your channels, you won't know which one(s) to optimize, double-down on, or dump.
What about B2B businesses?
For B2B business models, you often rely on sales and business development (BD) people, rather than digital ad spend. The same concept still applies when calculating CAC.
Let’s say you have a team of 5 sales people. On average it costs $100k in annual salary for each salesperson.
- Annual cost of sales = 5 x $100,000 = $500,000
Let’s say each of your sales people approaches 10 potential customers per month and their win rate is about 50%. It also takes them 1 month to close a customer.
- Total customers = 5 sales people x 10 customers/mo x 50% win rate x 12 months = 300 customers
- CAC = $500,000 / 300 = $1,700
In this case, even though you did not pay for advertising, the cost of your team’s time is a cost that should be accounted for.
How do I calculate the life time value (LTV) of a customer?
At the high-concept level:
- LTV = Total Life Time Revenue / Total Customers Acquired
Let’s go back to the mobile game example. Let’s say you’ve been launching the game for a year, enough for you to collect data on your initially acquired customers via Facebook.
- Your Y1 revenue = ($5 x 30%) + ($8 x 15%) + ($10 x 5%) + (0 x 50%)
At this point, you look back at the $4.00 it costs to acquire a Facebook user. This means this spend is not profitable at the 1 year mark.
However, you look at industry data again and realize that similar mobile games like yours can retain customers for multiple years. Let’s say you can retain your customers for 2 years (total lifetime), but revenue in Y2 will only be half of Y1 (people get bored and stop playing, etc.).
- Your Y2 revenue = $3.20 x 50% = $1.60
- Your LTV = $3.20 + $1.60 = $4.80
You can apply the same calculation to the B2B business model. Let’s say you sell an annual subscription for $100/license to 300 customers in Y1, and your most loyal customers stay for 5 years.
- LTV = Total Life Time Revenue / Total Customers = $90,000 / 300 = $300
Now, is my ROI% (or unit economics) positive?
For my mobile game app’s Facebook campaign:
- CAC = $4.00
- LTV = $4.80
- ROI % = (4.80/4.00) - 1 = 20%
Great news! Your ad spend was 20% profitable on the unit economics level.
For my B2B company:
- CAC = $1,700
- LTV = $300
- ROI% = (300/1700) - 1 = -82%
Bad news! You will need to either make your sales people more efficient at winning customers (or change their compensation structure to commission-based), raise your product’s price, or retain your customers better.
So, what can I do?
First, we need to put things into perspective. Like I mentioned, it’s important that you track and measure your unit economics/ROI% for users that come through different advertising channels.
This will allow you to compare different advertising and sales channels so you can allocate more money to channels with higher ROI% of course. Knowing the funnel well also allows you to optimize each step of the way.
For example, if you see that your App Store CVR (% of people who land on the app page that download your app) is lower than that of competitors or industry average, it’s better to spend effort on optimizing the app listing page than to spend time changing the ad creatives.
Of course, when you first launch your product and do not have enough meaningful customer data, you can do industry research and use average industry comps or competitors comps to model out your LTV.
This will let you know how much money you can spend max on acquiring a customer (read: do not spend more than your expected LTV on CAC).
However, it’s crucial that your marketers, product managers, or data analysts track cohorts of users over time so you can adjust your LTV expectation.
Over time, with new competitors entering the market or new product features launching, your CVR and LTV will change.
Last but not least, for marketplace business models, the term “revenue” in this article refers to the actual money you take in (what matters of course!), not Gross Merchandise Value (GMV).
Now go forth and build positive ROI% companies!
Read the ClassPass case study in Part 1 here to learn why unit economics matter.
Are you raising money for your start-ups? Apply with Hustle Fund here.
Mai Ho is a Venture Partner at Hustle Fund, covering the Vietnam and Southeast Asia markets. Mai was born and raised in Vietnam, and later graduated college in the U.S. with a double major in Accounting and Finance. Mai has 10 years of experience working in London, Singapore, and San Francisco, from Equity Research at Goldman Sachs to Growth/User Acquisition at consumer tech companies in Silicon Valley. Previously, Mai co-founded and exited e-commerce marketplace BigBalo.