7 brutal truths about CAC

This is the stuff you can only learn through cuts, bruises, and scars

👋 Hey, it’s Sundar! Welcome to another article of experiMENTAL, a weekly newsletter on Marketing Strategy and Science in Consumer Tech

What we’ll dive into today

Last week we went deep on how to properly calculate CAC. This week, I wanted to share 7 brutal truths I’ve learned about CAC over a decade in Marketing Data Science.

Let’s go!

Truth 1: There is no good or bad CAC

Whenever I advise companies, the first question I ask is “What is your CAC?”. The second question is “What is your lifetime value?”.

You should never look at CAC in isolation. Without a corresponding value metric, you can not understand the efficiency of your marketing.

Without context, there’s no such thing as a good CAC or a bad CAC.

Only a dangerously misunderstood metric that will come back to haunt you.

Truth 2: Don't trust platform numbers

I just hosted a podcast guest who specializes in marketing measurement helping companies set up better tracking and conversions. She's been doing this for 9 years and said something something that I will now repeat every day when I wake up in the morning 10x before getting out of bed.

“The ad platform conversions and data is about helping the ad platforms target and convert better. It’s not for you. You need to use something else to measure how these campaigns are performing.”

Why is this? It's important to remember that the platforms that sell ads have one objectives which is to convince you to spend more money on ads through them. You would think that their best way to do that is to tell you the truth. It should be but it’s not.

But here's the real challenge: What is the truth? They’re not lying when they say “Based on the information you’ve provided to us, this person clicked / saw our ad and then converted on your platform.” They've taken the road of showing you numbers that are defensible AND in their best interest. It's why you see things like enhanced conversions or quantitative attribution modeling or whatever the new terminology that they've used might be.

The point is, don't trust their numbers. They're good for optimizing the channel and seeing relative differences in channel over time, but should not be your source of truth.

Truth 3: All attribution is lying.

Just like platform numbers aren't fully accurate, neither is any attribution model that you're using. I’ve been burned by this so many times that it’s now why I highly recommend just using Blended CAC.

Blended CAC can not be manipulated or fudged. It is the undeniable truth.

Here's a real-life example I've seen that can show you the power of just using blended CAC:

  1. We wanted to increase growth

  2. We doubled budget

  3. CAC 2Xed

If your CAC 2X when you double the budget, that means there is no incremental impact or a very imperceptible one.

Now, if your spend doubles and your CAC goes up let’s say 1.25x or 1.5x then you can see that there’s some impact (albeit not efficient). Blended CAC was still able to tell you this.

The counter-argument is going to be, "Shouldn’t we use more sophisticated things like MMM, etc.?".

Yes, if you have that resource available to you, then do it. But companies aren’t using MMMs to make daily decisions. The people running the channels are using platform metrics while the people leading Marketing functions still report using Monthly CAC numbers.

Get access to the rest of this article...

and the experiMENTAL paid subscriber community

Already a paying subscriber? Sign In.

A subscription unlocks:

  • • 2-3 monthly subscriber only articles
  • • Unlimited access to 30+ (and growing) articles
  • • Supporting a writer sharing experience from 15+ years in growth & data science

Reply

or to participate.