# 3 Reasons Why Your #CAC Calculation is Wrong

CAC is the customer acquisition cost. Definitely one of the most important #metrics for eCommerce businesses.

For any eCommerce business to run profitability, it’s customer acquisition cost has to remain lower than the customer lifetime value.

But what happens if you are not calculating your CAC correctly?

A Lot of misinformed decisions can be made.

In this article, I want to show you why your CAC is wrong and that starts with the formula used.

Using “Platform last click” attribution model and Ad perspective attribution to ensure that their ads and platforms get full credit for conversions generated.

The reason is to maximize spending on their platforms.

But this is screwing up your CAC, here is how.

Most eCommerce marketing teams calculate CAC by dividing the total cost by the total number of conversions attained, a formula endorsed by Google:

CAC = Total costs / Total number of conversion

Let’s say you want to calculate our eCommerce company’s Facebook Ads CAC for last month:

• Number of orders: 1,000

In this scenario, you’d sum the total Facebook Ads spend and divide that by the total number of orders from Facebook over the month.

CAC= (\$5,000) / (1,000)

So the CAC would be \$5 per paying conversion for the month of September.

But this wrong

And here is why.

# 1. You want all of the channels involved in a conversion to take the credit based on their performance.

When you credit a conversion to a single interaction of your customer, you ignore the contribution all the other interactions had to that specific conversion.

The above scenario credits all the sales generated from the \$5000 Ad spend to Facebook yet there are so many interactions happen between your brand and the customers probably through other channels as they move along their buyer’s journey.

And all that is basically being ignored

The above CAC calculation only makes sense for products that are bought immediately after the Ad is served.

But doesn’t it apply today because most customers are taking longer and multiple channels to consider a brand before they buy.

Here is an example of a typical path to purchase:

To effectively compute the CAC for such a conversion, every channel involved here has to be assigned some kind of credit based on your attribution model.

Giving all the credit to the last traffic source does not give you the accurate cost of customer acquisition since it’s not an accurate representation of your customer journey.

Note that:

Google uses platform-specific last-click attribution to assign credit, meaning that it doesn’t consider other channel touchpoints for any conversion generated but only the ads they served within the last 30day window.

If you are working with a single platform, this data is close to accurate but if you are running multichannel marketing campaigns, you need to understand how each platform is contributing to your conversions.

Without considering the previous customer interactions you miss the opportunity to identify the best converting channels and risk using wrong CAC figures.

# 2. All conversions are back-attributed to the day of ad delivery, instead of conversion.

Simply put, not all conversions you see in your ad platform on any given day are attributed to the Ad spend of that day.

Ad platforms anchor their default 30-day or 7-day attribution window (whichever window you choose) on ad delivery instead of the occurrence of a conversion.

“How many conversions has a given ad generated?”

With a 30-day attribution window, any conversion that happens before the end of the window will be attributed to your first Ads regardless of whatever happens after the Ad is served.

Meaning that if a customer makes a purchase within the 30-day window, the ad they clicked on first will take credit for that conversion, regardless of whether the reason for the purchase is from another channel.

So even if the customer received an offer in an email or call your customer care to get more details or read a good review of your product online, at the end of the day Google will attribute that conversion to their Ad.

Do you still think your CAC is accurate?

Here is a simple multi-channel path to purchase:

For this example, with a 30-day attribution window, Google will credit the conversion that happens 5 days later to the first ad served on day 1 — with a first click attribution model.

And Facebook will also credit that conversion to their first Ad 1.

First of all, this is double counting of your conversions.

As long as more than one platform gets full credit for a single conversion, you’ll end up with more conversions than you actually have because that same order is being counted in every channel your Ads are running.

Secondly, if you are calculating CAC for Day 5, you will have to pull Ad costs from Day 1 and use that to accurately determine CAC for that specific conversion.

Yet the advised formula only considers costs and conversions of a given day.

If this is not screwing up your CAC already, here are two reasons why ad delivery perspective is leading to you the wrong CAC.

A. Your CAC is shifting every day until 30 days later after the ad is delivered.

Ad delivery perspective is the most common method and very easy to compute because conversions are attributed back to the day of Ad delivery

The formula is: spending of the day divided by conversions attributed to that day’s Ads.

With this Ad delivery perspective, your CAC is subject to change and will keep decreasing until the 30-day window.

Meaning that your CAC for today will not be the same as the CAC for tomorrow or the following day for the next 30 days.

So you will always be evaluating the spend and conversions generated to determine your CAC.

But when it comes to optimizing delivery across channels — as required by any multichannel marketing campaign, Ad perspective is very inadequate.

Because credit for your conversions will be attributed to ads from one channel instead of the entire customer journey.

This is why your CAC for any channel will always be inflated or lower than what it really is.

# 3. The way you are computing spending is wrong too. You are not spending on the ads that actually resulted in the conversion.

The first two points focus more on the conversion side of the CAC calculation, but let’s now look at the Spend.

Using spend of the day/order of day as seen in Google analytics or their eCommerce platforms.

CAC = Spend of the Day/ Number of orders of the day

So if on Tuesday, you spent \$1000 and generated 200 orders on the same, your CAC will be:

CAC = (\$1000)/(200)

Cost of acquisition for Tuesday is \$5

And as much as this seems to solve 1) and 2) above, it is still wrong.

Why? Because you are computing the cost of Ads incorrectly

The Ad cost you are using is not actually the money you spent on the Ads that resulted in the conversions you have today.

Because some of the Ads you have paid for today have not yet generated any conversions yet while others have not even been served yet.

To get the accurate Ad cost for the conversion, here is what you can do.

Since your advertising platforms are using Ad delivery perspective, you are also supposed to use cost on the first Ads the user interacted with in the first 30 days.

With ad perspective delivery, conversions are attributed to spending of the first Ads served on the 30-day window.

Otherwise, you risk including cost on Ads that have not been delivered or attributed any conversions yet.

A typical ad spend/conversion mismatch that’s way too common.

Here is an example:

If you run ads on Facebook and on Day 1 your cost is \$100 with no conversions.

On Day 2, you spend \$400 and get 100 conversions but none of those 100 conversions saw you the ad delivered on Day 2.

They only saw Ad 1 and conversions were registered on Day 2.

For CAC calculations, you should use spend on Day 1 since it’s responsible for the conversions achieved on day 2 not, Day 2 spend.

# Conclusion

There is a better and multichannel-focused perspective, the conversion perspective.

This perspective looks at the occurrence of conversion and looks back to every touchpoint that resulted in that conversion, then assigns credit to every interaction that happens.

Conversion perspective answers “How many touchpoints/channel resulted in a conversion”

It’s really good at optimizing delivery/budget across channels and fairly assigns credit to channels that resulted in the conversion based on the user experience.

It doesn’t credit one single channel but consider the user experience of every channel to assign credit for any conversion.

For example:

Using the same path to purchase:

Instead of assign all the credit of this conversion to Google Ad 1, all channels involved in this conversion will be considered and assigned credit based on user experience

The organic channel gets the highest credit for the conversion because the user spent the most time there, meaning that’s where they had the best experience with your brand.

With this credit attribution, the organic channel had the highest impact on the conversion generated and more resource allocation for future campaigns.

At Humanlytics we use a more data-driven conversion based perspective to assign credit to our client’s making channels helping them to better optimize ad delivery and budgets across channels — based on their user experience of course.

If you want to learn about our analytics approach, here is more about what we do.

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