Why (I think) you should love Performance Max

This week I set a very ambitious goal for myself by attempting to make this newsletter one that will completely (or at least partially) change the way you think and feel about Performance Max.

What follows is a four-part thought process on how and why I believe PMAX and other similar “fully-automated / smart” campaign types are being rolled out throughout the digital ad industry.

Before we dive in, this quote from a recent episode of Andrew Faris’ podcast titled “You Don’t Need an Attribution Tool” does an excellent job of summarizing where my head’s at:

“The idea of [marketers] parsing out which ads are best performing and assigning budgets there is so rife with problems. Humans are terrible at using backward looking data to forecast the future — particularly using small sample sizes and [especially] when they have strong biases and incentives towards certain outcomes.”

Part One: Things Changed

Since every marketing conversation is a measurement conversation, it’s only right that we start by addressing the major changes that have hit the digital marketing landscape in recent years.

TLDR; Requirements for sharing data are becoming more stringent, limiting the data available for personalized marketing and have impeded the ability of ad platforms to observe certain cohorts of users.

  • Some browsers like Safari & Firefox don’t allow conversion measurement using third-party cookies
  • Safari limits the amount of time first-party cookies are allowed
  • Regulations in the EU require that advertisers obtain consent for use of cookies related to advertising activities
  • Apple’s App Tracking Transparency (ATT aka iOS 14) requires developers to ask for permission to use other companies’ apps and websites for advertising purposes

A simple example of the impact here can be seen with cross-device conversions, when a user begins their journey on one device with an ad interaction, and completes the conversion on another. Without the ability to account for these behaviors, it’s basically impossible to attribute the conversion to the original ad interaction.

So ad platforms have lost the ability to observe certain cohorts of users (for example, unconsented users, or users using particular device types or browsers).

And without taking any action, these blind spots would result in automated bidding algorithms needing to make optimization decisions based on incomplete data, resulting in biased learning.

Part Two: How Ad Platforms Responded

Faced with gaps in the ability to connect the dots between ad interactions and conversions, platforms turned to good ole statistics to model for a non-observed slice of data.

They take the data from observable behaviors and compare them to the unobservable ones to gain an understanding of the similarities and differences.

For example, let’s say you have a slice of conversions that aren't observable on one browser type, but can be observed on other browser types. Modeling will first identify the trends between users' behavior (for example, conversion rates) across browser types.

It will then use observable data from measurable browsers, together with any systematic biases, and incorporate other aggregate dimensions like device type, time of day, geographic location, operating system, and more, to predict the likelihood of conversion events from ad interactions on the unobservable browser type.

If interested, you can read more about how Google and Meta do this in more detail.

All in all, this approach plugs the gaps in important behaviors that enable bidding and targeting algorithms to drive more success for your business - resulting in more accurate holistic measurement efficient campaign optimization all while protecting user privacy.

Part Three: The Third Party Attribution Tool Bubble

Amidst all of this change, a wave of third-party attribution tools hit the market promising to solve the common measurement struggles. Here are a few website headlines and promises from the popular players in this space:

  • “Measure Everything, Scale Everywhere”
  • “Attribution You Can Trust”
  • “Maximize Media Efficiency and Find New Ways to Grow”

Yes, a dashboard that aggregates information from all of your marketing activities and de-duplicates duplicative platform conversion data is valuable. But perhaps you’ve heard of Google Analytics? Or just checking your bank account?

I clearly have some biases and perspectives here but we can save that for another week…

I more so wanted to call attention to the fact that most of these tools are only using click-based ad interactions to inform their dashboards and models.

This presents a problem, because as you know, all I really care about is helping advertisers move beyond the bottom-of-the-funnel into a land where ads aren’t clicked on as often.

So regardless of which tool, attribution model, or shiny new object your boss heard about — you’re always going to be limited by your need to tie everything back to a click. (unless you geo-test).

Click-based attribution is a crisis and is holding so many advertisers back from success.

So to move away from this analysis paralysis that is keeping advertisers at the bottom of the funnel where audiences get saturated, costs go up, competition gets stronger, and efficiency becomes more elusive we need a mechanism that can solve for all of the measurement, targeting, attribution, and funnel-building at scale.

Part Four: Enter Performance Max

Today there are 11 campaign types in Google Ads and it can often take at least 4 campaign types to get the best of what Google’s inventory has to offer.

Having this many campaign types can bring unnecessary complexity and reduce performance for advertisers who may not be fully optimizing for their goal across every surface.

So wouldn’t it be great if there was one advertising campaign that did all of these things?

And what if it only required you to tell it how much to spend, what ROI you wanted, and which creative assets to use?

Google, Meta, and TikTok all sure seem to think so.

But, based on the themes mentioned above, this solution needs to look and act differently from any other type of campaign anyone’s run before.

And a change of this magnitude is hard — especially during a time of economic uncertainty where it’s difficult to tell if your ads aren’t working as well OR if people just don’t have the same needs/wants as they did a 0% interest rate environment.

Either way, this could be a significant shift in the way digital marketing works forever.

So if I were running a business, I’d be paying close attention to what’s changing…

So while I do know that many of you believe in the theory and need for a solution like this, there are of course major changes to the fundamental way we optimize and analyze performance.

Here are the top three challenges I hear most often and my personal perspectives in response:

1. Does not give insights

It does. In fact, there’s a completely revamped insights tab built to provide specific insights from Performance Max campaigns.

However, these insights are not the ones we’re used to seeing (eg. specific keyword data) when trying to analyze and optimize Google Ads campaigns.

Check out Search terms insights to see which current search categories and search terms are converting at higher rates. See what people are searching for when you show an ad. Use this insight to influence decisions for your creative assets, landing pages and shopping feed descriptions.

Check out Demand forecasts to see future trends relevant to your unique business that are expected to start over the next 180 days. Use this forward-looking insight to see upcoming predicted demand for the products and services you offer and to identify growth opportunities.

Check out Search trends to see if you are keeping up with increased demand in current and recommended categories relevant to your business. Use this insight to plan budgets, inventory, promotions, and landing pages based on trending customer search interest.

Check out Performance shifts to see what assets groups, product groups, and products are driving the campaign’s performance changes.

Check out Asset audience insights to see which assets are resonating most with your audience. Use this insight to help generate new creative assets to attract high-performing audiences.

Check out Audience insights to see which audiences are converting at higher rates. The 'Signals' label next to an audience segment shows you which segments are converting that you inputted as audience signals yourself. Focus on segments labeled as 'Optimized' to learn the new audience segments that automation discovered for you that you may not have known about before to help inform your broader business strategy.

2. Can't control creatives based on stages of user journey

This is actually a major benefit. I’m sorry, but there is no way that anyone could optimally map out, build, implement, test, and analyze the best creatives for users at every stage of the now incredibly messy purchasing journey.

There are THOUSANDS of different inventory types across Google channels…

multiplied by THOUSANDS of creative combinations to experiment with and see what converts best…

PMAX is managing MILLIONS of creative touch points at any one time in an always-on, always-optimizing campaign…

allowing you to move away from crafting individual ads and move towards machine-powered creative.

3. Forcing my ads on to inventory and placements that I don’t think will work

PMAX’s overall objective is to invest in the touchpoints that are going to drive the best outcomes from your investment.

Just because you’ve tried an ad placement in the past, doesn’t mean that it’s not going to work. That test you did was in isolation from your other touchpoints, probably wasn’t given enough time or budget, and was likely destined to fail from the jump. I’m sorry but I see it all the time.

Since PMAX is blending inventory and placements together across all of Google’s inventory it will eventually find the pockets that yield both short-term and long-term results by reaching potential customers throughout the funnel with the right message and at the right time and frequency.

With proper controls like new customer bidding, conversion value rules, optimal ROAS targets, and negative keywords AND the right segmentation/signals in place, you can prescribe what you want the campaign to do for you.


Congratulations if you’ve made it this far. I do all of my writing in one session and have just hit a wall. Next week I’ll build on this by getting more in the weeds on the tactics and controls you can take.

Hi! I'm Ben

I’m a CMO (and former Googler) helping DTC brands and online retailers make sense of the things that matter. Subscribe to my newsletter for my unique perspectives, relevant data, and ways to grow your business.

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