I’m currently transitioning our client accounts to PMax, but I’m worried about the lack of keyword-level data. For those in the digital marketing space, have you found that the AI-driven automation actually results in a lower Cost Per Acquisition (CPA), or are you seeing a lot of wasted spend on junk placements like low-quality mobile apps and YouTube shorts?
3 answers
From my experience running high-budget campaigns throughout 2023, PMax is a double-edged sword. It excels at finding "lookalike" audiences that a manual campaign might miss by analyzing signals across the entire Google ecosystem. However, if you don't use "Brand Exclusions" and "Negative Keyword Lists" at the account level, you will definitely see a spike in irrelevant traffic. We saw a 15% drop in CPA after three months of the machine learning phase, but only because we were aggressive with our first-party data signals. You have to feed the algorithm high-quality conversion data, or it will optimize for clicks rather than actual sales.
This is exactly what I've been debating. Are you finding that the "Search Themes" feature in PMax is actually replacing the need for traditional phrase-match keywords?
PMax is great for e-commerce with visual assets, but for service-based lead gen, I still prefer the transparency of standard Search campaigns where I can see exactly what users typed.
I agree with Heather. For niche B2B services, the transparency of knowing which exact search terms triggered the ad is vital for refining the sales funnel and qualifying leads.
Gregory, Search Themes are helpful but they don't give you the same control. In my latest audit, I noticed that themes act more like a "hint" for the AI. To answer your question, they aren't a 1:1 replacement; I still run standard Search campaigns alongside PMax to capture specific high-intent long-tail keywords that the automation tends to overlook in favor of broader reach.