When Google introduced placement reporting for Performance Max, the announcement was welcomed — and with good reason. PMax had operated as a genuine black box for a long time. You could see aggregate campaign metrics, but not where, specifically, your budget was being spent across the Display Network, Discover feed, and other non-Shopping placements.
The placement reports gave e-commerce advertisers something they'd been asking for: domain-level visibility into where their ads were appearing.
Several months on, with data accumulated across multiple accounts, it's worth examining what the reports are actually showing — and what's worth acting on versus what's noise.
What the Reports Show (and Don't Show)
The placement report for Performance Max shows you domain-level data for Display and Discover-style inventory. You can see that your ads appeared on, say, a particular news site, a lifestyle blog, or a mobile app — along with impression counts and, where tracked, clicks.
What the report doesn't show is Shopping placements. The inventory Google uses to serve your product listings in Shopping search results doesn't appear at the domain level in placement reports. Given that Shopping is usually the largest and highest-converting channel within PMax for e-commerce accounts, this is a notable gap.
YouTube inventory appears within PMax, but domain-level granularity for YouTube is limited. You may see youtube.com appear, but not which channels or content categories your video assets appeared alongside.
So the placement report gives you a window into part of the picture — the Display and Discover portion — rather than a complete view of all PMax spend.
What the Data Tends to Reveal
Across the accounts I've reviewed, the placement reports show a consistent pattern: a long tail of mobile apps, lesser-known content sites, and niche publications with very low individual impression counts but collectively significant volume.
This is normal. Google's Display Network is enormous, and PMax draws from it. Many of these placements individually look innocuous — a puzzle game app, a recipe website, a regional news publication. But when you sort by impressions and start looking at conversion data, you often find that the long tail collectively has a substantial share of impressions and a very low conversion rate.
This isn't surprising. Display advertising in general has lower purchase intent than Search. Someone reading a news article or playing a mobile game is not in the same mindset as someone searching "buy leather wallet." The impression is real; the intent behind it isn't the same.
The question isn't whether these placements exist — they always did, even before the report was available. The question is whether the spend on them is proportionate, and whether there are specific placements dragging down overall performance.
Finding the Signal in the Data
The placements worth acting on are those with a meaningful combination of volume and zero conversions over a sustained period.
A placement that served 200 impressions over three months and converted zero times is too small to be meaningful. A placement that served 50,000 impressions over 30 days and converted zero times is worth examining.
The filter I'd suggest applying: look for any placement with more than 10,000 impressions over the last 30 days and zero conversions attributed to it. That's not a definitive signal — attribution in PMax is complex, and an impression on a Display placement may contribute to a conversion that's attributed elsewhere in the funnel — but it's a reasonable starting point for investigation.
If you find placements matching that description, the question to ask is: does this look like an audience that would plausibly buy my products? A gaming app audience for a homeware brand probably isn't the right fit. A home improvement site for a tool or hardware retailer might be — even with zero direct conversions, the brand exposure may have value.
How to Exclude Placements That Aren't Working
If you find placements you want to exclude, the process in Google Ads is straightforward. Within your PMax campaign, go to Placements, then add the domain or app as a placement exclusion.
This works for Display and Discover inventory. Adding reddit.com, a mobile game app, or a specific content site as an exclusion prevents your ads from serving there within that campaign.
One thing to be aware of: placement exclusions in PMax apply to the Display/Discover inventory type. They won't affect how your Shopping placements, Search placements, or YouTube ads are allocated. So even after adding exclusions, you're only adjusting one portion of where your PMax budget flows.
The Honest Reality Check
Here's the caveat that's worth stating clearly: placement exclusions are a marginal adjustment, not a structural fix.
If your PMax campaign has a ROAS of 200% and your target is 400%, the problem isn't that your ads appeared on a gardening website. The problem is more likely to be one of: weak product feed quality, poor conversion tracking, incorrect campaign structure, or a tROAS target that isn't calibrated to your actual margins.
Placement exclusions help at the edges. They can clean up obviously wasteful spend on irrelevant inventory. They won't rescue a campaign that has deeper structural problems.
The most valuable thing the placement report does isn't necessarily give you a list of domains to exclude. It's to give you a rough indication of how your PMax spend is distributed across channels. If you're seeing a large proportion of your impressions sitting in Display and Discover placements with low conversion rates, that tells you something about the overall campaign balance — and may prompt a broader conversation about whether PMax is the right structure for your specific situation, or whether a stricter Shopping-only campaign running alongside it would serve your goals better.
Transparency as a Starting Point
The placement reports are a step forward. They're imperfect — the Shopping and YouTube gaps are real limitations — but they give advertisers more visibility than they had before, and visibility is the prerequisite for any sensible optimisation decision.
Use the data to understand what's happening, not just to generate a list of things to exclude. The bigger picture — what percentage of your PMax spend is on Shopping versus Display versus YouTube — is often more valuable than any individual domain exclusion.
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