Hormozi's favorite analysis

There’s this business guru named Alex Hormozi who has gotten really popular recently.

How popular?

3M subscribers on YouTube and two of the best selling books on Sales and Marketing on Amazon right now 👀

And being the savvy finance guy I am, I like to pay attention to what my business partners are paying attention to (i.e. Alex). It helps me to play that middle-man between finance concepts and the business.

As I’ve listened to more of his content, I’ve noticed a clear trend…

He loves talking about LTV:CAC.

Nearly every lesson points back to this seemingly magical metric.

And today we’ll dive deep into what it is, how to calculate it, and how to use is to drive growth as a finance professional.

Let’s go!

What is LTV:CAC?

There’s levels to this one…

Like any great ratio, this one can be defined by the 2 things it contains - and the comparison of those to each other:

In plain English - it’s the relationship between how much you make per additional customer and how much it costs to acquire an additional customer.

In even more basic language - it’s how much profit you make per additional customer.

Anytime the ratio is above 1 you are making more money per additional customer. And a good floor for this metric is 3:1 (higher is better!).

Real-world example:

A great example is Starbucks who has an LTV of approximately $14,000 (you read that right!). Which means their average customer spends $14,000 at their stores.

How much would you pay to acquire a customer if you’re Starbucks? Probably up to $4k-$5k on the top end.

You can see how much clarity this KPI drives for a business leader!

How to calculate LTV

We already broke down the formula, so I want to stay high-level here and follow an example.

Let’s say you run a consulting practice that charges people $3,000 per month.

On average, you churn a customer every 6 months.

It costs you $1,000 per month to fulfill the work since you hire people to do the work for you.

That would give you ($3,000 - $1,000) * 6 months = $12,000 LTV

This assumes you don’t sell any other products or services to your customers beyond your core consulting package.

You can calculate this on a look-back basis (looking at your historical data in your P&L) or on a pro forma basis (knowing what your go-forward assumptions are) for all your metrics except churn (unless you’re totally confident it’ll change in the future).

It’s up to you as the savvy finance professional to pick the numbers that make the most sense here.

How to calculate CAC

This one’s simple - you’re looking at the Sales and Marketing cost in your P&L divided by the number of new customers acquired in that period.

So you can pick a time period that has enough history to give you credible data while also picking a recent enough time period that the data is representative of the business.

Let’s pretend the consulting business spends $3k per month on marketing and sales and generates 3 clients per month.

So CAC is $1k.

Hold that thought…

Bringing together LTV:CAC

Our LTV is $12,000

Our CAC is $1,000

So our LTV:CAC is 12:1 which is an excellent number.

For every $1 we invest in this business we get $12 in profit. It’s like a magic money-printing machine with a killer return!

We’ll need to eventually consider our operating expenses to run the business to support this growth, but for now we can ignore those as fixed costs.

That was 101… let’s move on to 201…

You might be wondering “why is this so powerful, Brett? It’s just a KPI that we can track and help a business increase through improving the LTV (higher revenue, lower direct costs, and lower churn) and decreasing the CAC (more efficient S&M spend)…”

You’re right, this is only a fraction of the power of LTV:CAC.

As savvy FP&A professionals we know that we can combine this with our powers of segmentation to identify our most profitable customers and acquisition channels.

(this is where every business is completely different so you’ll have to adapt it to your own).

Continuing with our example…

I asked Grok (Elon’s AI tool) to produce me a fake dataset that we can use to analyze.

It gave me a CSV with 100 customers, their lifetime revenue, and direct costs split between:

• Acquisition channel (direct outreach, linkedin organic, and paid ad webinar funnel)

• Company size (startup, mid-market, enterprise)

• Industry (bank, retail, and home services)

I simply threw that dataset into a pivot table to study our results:

What do you see?

I see a few things:

• Direct outreach seems to be our most profitable channel

• Mid-market customers seem to be our most profitable

• Home services companies seems to be the most profitable industry

And wouldn’t you know… our most profitable customer is: Middle-market home services companies who we acquired via direct outreach.

This group is almost 2x more profitable than the average ($120,833 versus $66,040)!

I almost want to shut off paid ads and linkedin organic right now…

Let’s finish this analysis!

Now we’re cooking!

But we’re missing 1 really important thing before we make a huge pivot in this business:

What’s our CAC??

We need this so we can appropriately understand which customer segment is most profitable per every dollar invested.

Remember, we’re building a magic money-printing machine. Let’s fine tune it to get the most out of it.

(again, this is super dependent on your business so please use your analytical brain to figure out how to get this data)

Let’s assume we have an overall CAC of $7,167 and the following CAC by channel:

• $12,000 in Direct Outreach

• $1,500 in Linkedin Organic

• $8,000 in Paid Ad Webinars

Now we can do LTV:CAC

From here, it’s simple math to get to LTV:CAC by each customer/channel segment!

Literally LTV divided by CAC - we’ll just assume the same CAC across customer segments for this example:

What do you see now?

Here’s my assessment:

• Linkedin Organic seems to be our most profitable channel by far with 38.2 LTV:CAC! Quite the shift from only looking at LTV results…

• Mid-market and home services still win but I’m also seeing enterprise home services looking solid

As a finance consultant, what would you recommend for this business?
(I’m not going to tell you my thoughts…)

In summary:

I’m a fan of Alex Hormozi and his relentless focus on data-driven decisions.

And we can learn a lot by studying what our business friends aspire to.

Use this LTV:CAC framework to drive better business decisions - I’m curious what you find!

Say hi 👋 on LinkedIn