How to Calculate Customer Acquisition Cost (CAC)

Calculating customer acquisition cost is vital to understanding the viability and profitability of your business.

The simplest formula to calculate customer acquisition cost (CAC) is to add the total cost of sales and marketing over a set period and then divide that by the number of new paying customers acquired in that same period. It would look like this:

Customer Acquisition Cost = total spent on marketing and sales in period/number of new customers in that same period

Take a look at this sample spreadsheet I prepared to get an idea of what CAC looks like in practice.

However, various other customer acquisition cost formulas could be more relevant to your business model. But before we get into these variations, let’s break down the fundamentals of customer acquisition cost.

What is Customer Acquisition Cost?

Customer acquisition cost (CAC) is how much a business spends to make a customer perform a transaction, usually purchasing a product or service. CAC is the total cost of all the Sales and Marketing expenses involved to acquire that paying customer.

By calculating the CAC, you will have a better idea of how much money you need to charge that customer to break even or turn a profit. From there, you can begin to adjust spending and focus on optimizing specific parts of your business to lower your CAC.

CAC is typically compared to the total monetary worth of your customer, also known as the lifetime value (LTV) of a customer. For now, let’s just focus on CAC, and then towards the end of this article, I will discuss how LTV complements calculating your CAC.

How do I calculate Customer Acquisition Costs?

The most common way to calculate customer acquisition cost is a simple equation of total marketing and sales costs divided by the number of paying customers acquired in that same period :

Customer Acquisition Cost (CAC) = total spent on marketing in period/number of new customers in the period

This formula is the most widely used, and when looking at an annual report can give you a general idea of your overall CAC. It does, however, have a few faults when trying to get some granularity. For one, you cannot consider customers that convert outside of your specific time window.

If you spend aggressively on marketing at the end of the month and users convert in the next period, you could calculate an inaccurate CAC. Using the simple formula will give you a general CAC, but your data could be sending you the wrong signals.

The better CAC formula to use

As USC Professor Paul Orlando recommends, one of the better methods to calculate customer acquisition cost considers the number of users who have engaged with a marketing or sales event, like a click on an ad. Then divide by the percentage of users who converted into paying users.

The formula would look like this:

CAC = cost to get potential customer “in the door” / conversion rate to being a paid customer

For digital ad platforms, they boil this down to:

CAC = Cost per click / Conversion rate

Or for acronym lovers:


The customer acquisition cost is most valuable when the cost of acquiring a customer is identified by channel. If, for example, you are buying ads on Facebook and Google Adwords, you would want to know what your CAC is for each channel so you can focus your efforts on the more successful channel.

Implement your customer acquisition formula

Let’s run through an example where you built an app and are now buying digital ads on a few different platforms. A snapshot of your marketing costs may look something like this:

ChannelCost Per ClickConversion RateCAC
Google UAC$0.701.50%$46.67
Apple App Store Ads$1.202.85%$42.11

Granted, each of these ad platforms will provide you with the CAC at the ad and campaign levels. So let’s kick it up a notch and add some less straightforward marketing and sales expenses.

Let’s say you paid $1500 for a famous influencer in your niche to do some paid promotions over three months. In total, you can attribute 500 clicks to the campaign, which would divide out to $3 a click. But say it was super effective and converted at 5.6%.

One of the better low-cost methods for a low CAC is referral programs, so you also implement a referral program where you pay $10 every time a user converts someone into a paying user, and that new user gets $5 in free credit. This referral program has a flat CAC of $15.

ChannelCost Per ClickConversion RateCAC
Google UAC$0.701.50%$46.67
Apple App Store Ads$1.202.85%$42.11
Referral Program$15

This use case obviously makes CAC a critical metric to watch for companies that use affiliate platforms like Impact Radius or Commission Junction to drive sales on a pay-for-performance basis.

Weighted CAC relative to the total conversions

From here, we have a decent level of understanding of how our CAC is performing by channel. To improve this analysis further, we can provide a weighted average CAC by adding the total number of converted users from each channel.

Weighting helps because we could, for example, have a channel with a higher CAC and a lower number of conversions. If we weighted each channel as the same, that more expensive but lower converting channel would inflate our total average CAC. Or the inverse could occur, and a low-cost channel with a high amount of conversions would get lost in the noise.

ChannelCost Per ClickConversion RateCACNumber of conversionsWeighted Percent
Google UAC$0.701.50%$46.675627.30%
Apple App Store Ads$1.202.85%$42.114421.50%
Referral Program$154522%

If we wanted to calculate each of these channels monthly, we could pivot this table to have a month-by-month breakdown of the above CAC metrics. For example, here is what Instagram could look like for Q1.

Number of Conversions$32.0031$27.00
CAC metrics example based on Instagram performance as an acquisition channel.

How to calculate customer acquisition cost (CAC) in Google Sheets

If you want to start tracking your marketing and sales costs, I have created a Google Sheet that organizes five channels for marketing or sales.

In the example sheet, I projected out some data for the above channels over a year. I then weighed each channel against the total conversions to give a more accurate monthly, quarterly, and yearly CAC.

Note that even though each channel fluctuated for cost per click, conversion rate, and customer acquisition cost, the CAC continued to improve. By having this macro-level view of your CAC metrics available, you can work on improving conversion rates and cost per click by channel.

I provided a second blank template sheet for your use. The template is a good starting point to get a birds-eye view of your marketing and sales costs contributing to your CAC.

Lastly, you have the simple CAC formula on the third sheet, which I discussed at the beginning of the article. I added a few marketing and sales categories to get you started if you decide to use this formula.

Common mistakes when calculating CAC

Some managers will try and sidestep the issue of conversions happening outside of your desired period by trying to pindown their conversion window for users and then working that conversion lag time into their CAC formula.

For example, suppose your users convert on average 60 days after signing up. In that case, a marketing manager might propose dividing the past marketing and sales expenses that have influenced users to convert today and adding that to your current CAC. You would essentially assume that every month like clockwork, half of your past marketing and sales expenses are paying off 60 days later.

However, in practice, I have found this is rarely the case. Sales, marketing content with a strong CTA, big discount promotions like Black Friday, and other influences on user behavior will constantly move your conversion data. Having an inflexible CAC formula based on assumptions will not provide meaningful data. It might work sometimes but certainly not all the time.

Using a relative cost per click and conversion rate channel by channel avoids the inflexibility by attributing the conversion to the user in the door and using a fluid conversion rate to project conversion success.

I will admit that this raises the question of how do we attribute the user to a single ad and not the five ads they saw before. The easiest attribution methodology for most businesses is to keep it simple. The user is attributed to the most recent ad they engaged with, and the relative conversion rate for that ad or campaign is used accordingly.

It doesn’t matter if they take one hour to convert or sixty days. The conversion rate is relative to the ad, campaign, or channel period by period.

If you try and start to split up attributions and time periods, your CAC will become overly complicated. Attribution is a giant rabbit hole of a topic, and unless you are a substantial business with a lot of free engineering time to invest, it’s probably not worth it right now.

Which metrics complement Customer Acquisition Cost?

Lifetime Value (LTV) is an essential metric that creates a clearer picture of how profitable and viable your business will be with your CAC. If your LTV is lower than your CAC, your current methods of acquiring paid users are way too costly, or users are paying way too little for the product or service.

LTV is the amount of money a user will give you over the total time they maintain the relationship with your business.

If your users are paying you a monthly subscription, this means the total amount of money they pay you until they churn. If they just buy one single product, then it’s the amount of revenue from that purchase.

Now that you have an LTV, you want to compare that to your CAC and make sure that, at the very least, your LTV is three times larger than your CAC.

Takeaways and further reading

There are multiple CAC formulas out there for a base level of business analysis. It is important to identify which you think is best suited for your business and current needs. The simple formula of measuring your costs per event (click) divided by the conversion rate is a great place to start.

If you want to know more about calculating CAC, I recommend checking out Paul Orlando’s 2020 book Growth Units which I cited here a few times.

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