LTV:CAC deep dive part 3: Optimal LTV:CAC

Introduction

LTV:CAC (lifetime value to customer acquisition cost ratio) is a very popular marketing efficiency metric and captures the unit economics of every business. Despite its popularity though, it can get confusing when it comes to understanding its variations, calculations and interpretations. So in this multi-part post I discuss from first principles the following topics:

• Part 1: Misconceptions (covered here)

• Part 2: Measurement framework (covered here)

• Part 3: Optimal LTV:CAC ratio

• Part 4: LTV:CAC & marketing spend optimisation

Welcome to the third part of the series!

What does the internet say?

Apparently the internet seems to agree that a 3:1 ratio for LTV:CAC is optimal. It is often presented along with a classification like this one:

• LTV:CAC<1: Loss

• LTV:CAC=3: Optimal

• LTV:CAC>3: Underinvesting in marketing

Even asking chatGPT I get the following answer regarding LTV:CAC values lower than 3:1:

“If the ratio is less than 3:1, it indicates that your customer acquisition costs are too high relative to the lifetime value of your customer, suggesting inefficiencies that might affect profitability.”

A few sentences above chatGPT also explains that 3:1 ratio means that for every $1 spent from acquiring the customer, the company should generate $3 in revenue from that customer over their lifetime.

My question to you, the reader, is if I tell you, “give me $10,000 and I will give you $30,000 back a year from now”, will you take that deal? What would you take into account in order to take the right decision?

Now chatGPT is in no way representative of the scientific community but it is representative of the content that exists online and therefore what most corporate decision makers would most probably turn to for answers.

Reading this blog post from a16z, while the 3:1 ratio is also mentioned to be what investors consider optimal, they argue that the higher LTV:CAC is, the better. The more efficient you are, the more capital you can invest in other domains of your business. In addition, they claim that increasing LTV:CAC is equivalent to higher valuations. Why would chatGPT believe that higher than 3:1 isn’t optimal but a16z believe the higher the better? Let’s dive in!

Microeconomics 101

The way chatGPT is reasoning on the topic resembles the profit maximisation problem in microeconomics. Upon maximising profits with respect to quantity produced, we see increasing revenues with higher production but at the same time the marginal cost, being a function of production, goes up. This leads to the optimality condition with respect to quantity when:

Marginal Revenue = Marginal Cost (MR=MC)

Example

A factory produces phones which then sells at the price of $100. The first phone takes $10 to produce and for each additional phone the cost goes up by another $10. So let’s use the above condition to determine where the production should stop.

1. phone 1: revenue $100, cost $10, profit +$90

2. phone 2: revenue $100, cost $20, profit +$80

3. phone 3: revenue $100, cost $30, profit +$70

4. phone 4: revenue $100, cost $40, profit +$60

5. phone 5: revenue $100, cost $50, profit +$50

6. phone 6: revenue $100, cost $60, profit +$40

7. phone 7: revenue $100, cost $70, profit +$30

8. phone 8: revenue $100, cost $80, profit +$20

9. phone 9: revenue $100, cost $90, profit +$10

10. phone 10: revenue $100, cost $100, profit +$0

11. phone 11: revenue $100, cost $110, profit -$10

So when the first phone is produced it makes $90 profit. At the second phone the profit will be 90+80=$170. With every additional phone the profit goes up albeit in a decreasing rate. This stops at phone 10 where MR=MC. Making an additional phone would reduce your profits by $10. You would still be profitable as you have already accumulated $90+$80+…+$10=$450 but with every additional phone you would be losing profit symmetrically to the way you gained it.

So what does this tells us about the LTV:CAC ratio? Let’s make a few modifications to the above example to make it resemble a marketing use case:

1. Let’s assume for the sake of simplicity that the revenue mentioned above is the revenue after servicing costs (contribution margins) for each customer.

2. Let’s assume that the cost mentioned above is the cost to acquire each customer, CAC.

The sum of the contribution margin series up until the MR=MC point would be $100 x 10 = $1,000 and dividing by 10 customers we would get LTV=$100. The average acquisition cost would be $550/10=$55. So the LTV:CAC would be 1.82, significantly lower than 3.

So what would be the profits for the business with a LTV:CAC 3:1 ratio?

We would have to find where the average cost is 1/3 of revenue or around $33. That would be somewhere the 6th product.

LTV = $100, CAC = $35, LTV:CAC~2.9

At the 6th product the total profit would be $390 which is less than the $450 we calculated with the MR=MC condition. The 3:1 rule doesn’t seem to be relevant to this problem.

So the questions that emerge from this exercise are:

1. Why doesn’t LTV:CAC 3:1 produce optimal results?

2. Why would a16z show preference for even higher than 3:1 LTV:CAC when it would in fact produce even less profits?

3. If we already have a condition that gives us the profit maximisation point, why do we need to use arbitrary ratios?

In Practice

In order to reason about profit maximisation we had to use a simple example, which shows us that a rational agent, or a group of, is making decisions by thinking at the margin. Now that we got this out of the way let’s see what other things we need to consider.

A business has many levers and marketing is just one of them. You should be able to pass on a good marketing investment for a better one in tech. In fact, for startups that haven’t optimised their product and pull the marketing lever prematurely, they risk creating a bad reputation for themselves. So I disagree with the statement:

"a higher LTV:CAC ratio means for every dollar of sales and marketing investment, your company has higher margins and so more profit to reinvest back into its business, which means that you can build better products and, hopefully, capture more market demand” 

As we saw in the previous section, the above statement is not valid. Higher margins don’t necessarily translate to more profits within a business. You can always trade-off some of that margin in order to increase the overall profit. The thing is, if you have better ways to invest your capital then by all means you should do it. But if you are at a stage where marketing would be your best bet e.g. you just discovered a new breakout channel with 6:1 LTV:CAC then you should invest until you reach the point where it’s no longer the most profitable thing to be doing.

The above reasoning can also be misinterpreted as an argument against efficiency. If you had to choose between two channels where for the same amount of spending you would get different LTV:CAC ratios, you should always pick the one with the higher LTV:CAC ratio and then start spending more! So it’s a two step process:

You have to work on improving efficiency while keeping the level of spending constant and then you have to increase the level of spending to maximise profit while sacrificing some efficiency along the way.

Finally, you could also take the wrong statement one step further. If higher LTV:CAC would allow you to invest more money to build better product, why should you do it? If your current level of investing in your business gives you a 500% ROI, why spend more and get your business in a state of increasing marginal costs and lower returns? It just doesn’t add up.

Required rate of return

In the previous post I discussed that a key property of LTV should be accounting for uncertainty as well as alternative investments that could yield higher returns. In the previous paragraph I discussed how a business should be allocating capital based on where it would produce the highest returns. In practice this information can be baked in the LTV:CAC ratio simply through the discount rate which takes into account the cost of capital. So, as the cost of capital would go up, the LTV would go down and that would suppress the target CAC.

Inaccurate measurement

It feels like this 3:1 rule is a product of decision-making under the regime of poor marketing measurement. So the 3:1 rule is demanding higher returns in order to hedge against the risk of measurement itself.

If marketing is not bringing new customers and thus not generating any additional revenue, it would be eating from the existing profits. So if you are incorrectly attributing all your organic traffic to marketing campaigns you could have in many cases very good looking LTV:CAC ratios due to underestimated CAC. In that scenario, you might be seeing a LTV:CAC >1 but in reality it could be significantly lower than 1.

Monopolies versus underinvestments

One type of bias that appears many times when people omit variables when comparing LTV:CAC across various businesses or at different points in time within the same business.

Let’s say you are considering investing in one of two companies. The first one is a high margin tech business that’s an established leader with a significant market share in the market in which they operate (e.g. Google, Apple, Meta). The other one is a low margin business operating in a highly competitive industry (e.g. Ford, General Motors). When the demand for a product is inelastic, the producer can be a price maker and enjoy high margins. In competitive industries though, companies don’t have the same luxury. In addition, in highly competitive environments differentiation through marketing is vital, while for monopolies it’s not even necessary.

So when a VC states that their interested in investing in businesses with high LTV:CAC ratios (>4:1) they don’t refer to companies that underinvest in marketing but in companies that enjoy higher margins due to inelastic demand for their products. If you are operating in a competitive industry and you came across a high LTV:CAC marketing opportunity you need to go all in and increase your profits at the expense of lowering your LTV:CAC.

To sum up

1. According to basic microeconomics, higher is not better when it comes to LTV:CAC within the same business. As we showed you might be better off following the MR=MC principle.

2. If you want to use a simple rule for LTV:CAC, you should instead focus on optimising the marginal LTV:CAC with a target marginal LTV:CAC of 1:1. This would be a close equivalent to the MR=MC rule.

3. When other functions of the business don’t produce good returns, the lower discount rate in the LTV calculation will allow the marketing team to go for lower un-discounted returns and in times of good business opportunities, suppress the target CAC for more lean marketing operations.

4. If you are selecting a higher LTV:CAC ratio as a hedge against poor marketing measurement, you would be better off fixing your marketing measurement instead.

5. LTV:CAC can be a useful ratio for comparisons across marketing channels for the same amount of marketing spend. In that sense, if a channel has a higher ratio, more capital should be invested in that channel.

6. The fact that businesses with products of highly inelastic demand can enjoy higher LTV:CAC ratios doesn’t mean that you should underinvest in order to protect your LTV:CAC ratio from falling any lower. Your profits are far more important than your marketing efficiency.

References

• Why Do Investors Care So Much About LTV:CAC?

• 16 Startup Metrics