Stop sorting ads by CPA and ROAS

Howdy Haveaclues!

I hope you’re had a fun and/or relaxing weekend! Take a minute, take a breath, take a sip of a tasty beverage that is appropriate for the time of day you’re reading this.

I recently did an interview on the Marketing Mindset podcast and it's now available on YouTube and wherever you get your podcasts. I had a blast recording it and I think you’ll enjoy it. We dove into the practical aspects of implementing "Ugly Ads," the proliferation of post-it ads on DTC Twitter, my campaign testing structure, my ideal mindset for media buyers, and my thoughts on what marketing roles will have the most demand or opportunity in the coming years, annnd so much more. Let me know if you watch or listen!

In last week’s newsletter, I offered up some free stuff for my subscribers and I wound up giving away thousands of dollars worth of merch, my audit template, CreativeOS templates, and consulting calls to some of y’all. Stick around until the deep end of this email, but don’t skip ahead, I miiight have something to give away!

Today, we’re going to launch into the first of my bajillion-part series:

Numbers don’t lie, but marketers do. Annnd more frequently, marketers make mistakes.

Last week, I lightly touched on the “breakdown effect” and a bunch of you asked me for me to dig into it more. I also put this poll on Twitter:

62.9% of people don’t know what it is or want to know more about it. Is that number lying? No. Is the qualitative side of this data questionable? Maybe 🤷‍♂️

Today we dig into how seemingly clear performance data can be misleading due to black box machine learning systems.

Before we go further and talk about the breakdown effect, is today’s topic even for you? We’re about to dig into the weeds on ad data analysis. If you never need to analyze ad data or talk with anyone that ever does, then you can skip most of this email. If you’re subscribed to this newsletter and you have no interest/need for this topic and you’re not from my mom (hi mom!) please smash the reply button and let me know this isn’t for you and tell me what you want more of from me.

The breakdown effect is why it’s difficult to properly or easily analyze ad data.

The breakdown effect comes into play any time you let the system optimize your budget to get your more of your desired actions. I generally recommend letting Meta’s system optimize because it can do so better than your feeble human brain can do manually. Examples of areas the system optimizes budget for you:

• Ads in an ad set

• Ad sets in a campaign using budget optimization

• Platforms and placements

  • Desktop or mobile

  • Facebook, Instagram, Messenger, or Audience Network

  • Feed, Reels, Stories, etc

• Demographics

  • Age

  • Gender

  • Geography

• Relevance variables our human brains probably couldn’t understand