Nobody Publishes Display Network Lead Quality, Not Even Google

Quick answers:

• Should I turn off Display in Performance Max?
• Are Display Network leads any good?
• Can I exclude Search Partners from Performance Max?
• What is the Search Partner placement report actually showing me?
• Is this ad fraud?
• What should I measure instead of conversions?

If you buy phone calls and form fills, you have almost certainly been told to leave the Display Network and the Search Partner Network switched on inside Performance Max. The advice is everywhere, it is usually right about e-commerce, and it rests on a claim nobody has ever tested in public: that the leads these two networks produce are the same leads.

No published measurement supports that claim. Not weak evidence, not contested evidence. None.

Key numbers – Google’s Search Partner placement report shows impressions at the domain level and no other metric (PPC Land, August 2025). – “Parked Domains (AFD) will cease to be an ad surface within the Search Partner Network effective February 10, 2026” (Google Ads Help). – “Over 51% of impressions came from Search Partners” across 801 managed accounts in a 30-day window, with mobile apps another 15 percent (Producthero, March 2025). – Google’s 2025 Ads Safety Report counts 8.3 billion ads blocked or removed, and contains no invalid-traffic figure at all (April 2026).

What one advertiser found when he checked his CRM

In April 2025 a Google Ads manager posted a full year of numbers to r/PPC under the title “$78K Wasted on Junk Leads from ‘Search Partners’ Network in Google Ads”. The account was mid-market and enterprise B2B SaaS, the year was 2024, and the leads were graded in HubSpot rather than in Google Ads. That last detail is the entire reason the post is worth your time.

Inside Google Ads, Search Partners looked like the better buy. In his reported figures it cost $188 per conversion against $575, converting at 3.1 percent against 1.7. Its click-through rate ran higher too, and on roughly a third of the spend it reported almost the same number of conversions. Judge that on the platform’s own numbers and you move budget toward Search Partners, and you would be doing competent, defensible optimization work.

Then he opened the CRM.

Source: u/aStormyKnight, r/PPC, 11 April 2025. One advertiser’s account, self-reported.

The number that matters is not the size of the gap. It is the direction of the error. The platform’s metrics did not merely fail to warn him. They actively recommended the network that produced 380 junk records and a single opportunity. Every in-platform signal available to that advertiser, conversion rate, cost per conversion, click-through rate, agreed with each other and pointed the wrong way, and nothing inside Google Ads could have corrected them, because the correction only exists in a system Google cannot see.

Treat this as exactly what it is: one well-documented, self-reported account from a single advertiser in a single vertical. It is not a rate and it does not generalize. What it establishes is narrower and still damning, which is that the failure mode is real, and that when it happens the platform’s own reporting flatters the network causing it.

He is not the only one saying this, though the record is thinner than it first appears. On 12 September 2024 the consultant Jon Kagan asked the #ppcchat community whether others were “seeing an abnormally high amount of fraudulent and suspected fraudulent traffic in the search partner network this year” (X). About an hour later Melissa Mackey replied in the same thread: “We hardly ever use search partners. On the surface it looks like that network does well but the leads are almost all junk” (X). Be clear about what that is. It is one conversation on one day between practitioners who know each other, not two independent findings, and it should carry the weight of a shared professional impression rather than evidence.

The oldest version of the complaint comes from inside Google’s own house. In a January 2022 thread in Google’s Ads Help community titled “Why is invalid traffic from Google search partners so bad these days,” a Google Ads Product Expert wrote: “I have seen plenty of fake conversions from the Display network, because they think they are less likely to be flagged” (Google Ads Help community). He immediately drew a boundary around it, adding that “there is no benefit for anyone to do so in Search,” so read him as making a distinction between surfaces rather than condemning the whole system.

What Google publishes about lead quality on these networks

Nothing, which is why one Reddit post is doing so much work in an article about a multi-billion-dollar ad network.

Google publishes plenty about these networks: reach, policy, aggregate conversion-lift claims, and since August 2025 the domains your Search Partner impressions landed on. What it has never published, in any form, is a comparison of lead outcomes by network. Not the share of form fills that turn out to be real, not the share of calls that reach a human who wanted the call, not the share a sales team would accept.

The report Google did ship stops exactly where the question starts. The Search Partner placement report gives you domain names and impression counts, with no cost, no clicks and no conversions attached to any of them. One practitioner quoted in PPC Land’s write-up summarized it as “the PMax version: impression data only.” You can read a list of names. You cannot price a single one of them.

Nobody else fills the gap either. The call-tracking platforms and lead-verification services sitting directly downstream of this traffic publish no split of qualified-lead rate by Google network, and neither does the trade press.

There is one by-network number Google publishes, and what it measures matters. The Invalid Activity Credit Report, in Report Editor’s template gallery as “Invalid Activity Credit Report: Search & PMax,” breaks invalid-activity credits down by campaign and by network, with columns for credited clicks, credited interactions and credited amount (Google Ads Help).

Read what that is, though. It reports credits Google’s own systems already decided to issue, applied “where appropriate and possible” after the invoice is generated. There is no claim to file and no dispute path, and Google states plainly that “you won’t receive refunds for invalid traffic” (Google Ads Help). So the one by-network figure you can pull is Google’s scorecard of what its own filters caught, and it says nothing about what got through. Read it as evidence the problem is real and persistent enough to need a standing credit mechanism, not as a remedy you can plan around.

Compare that against what Google does publish when it wants to. Its 2025 Ads Safety Report counts more than 8.3 billion ads blocked or removed in a single year, alongside tallies for suspended advertiser accounts and actioned publisher pages. That is a company entirely capable of counting things and publishing them at scale. The same report contains no invalid-traffic figure at all. It is a document about policy-violating content, not about traffic quality, and the distinction is worth holding onto: Google is not silent because measurement is hard, it is silent on this specific question while being loud on adjacent ones.

Absence of evidence is not the weak part of this argument. It is the argument. You are being asked to spend on inventory whose effect on a qualified lead has never been published by anyone, including the company selling it.

What you cannot see, and what you cannot switch off

You have less control here than you probably think, and Google’s documentation is unusually clear about how much less.

Display campaigns run in apps unless you go and stop them. Google’s documentation states that “Display Network campaigns are designed to show your ads in apps by default if the placement matches the targeting you’ve set,” and in the same breath that “Google Ads no longer supports targeting to app inventory using device settings and adsenseformobileapps.com placement” (Google Ads Help). That second sentence retired the blanket app opt-out many advertisers used. What survives is exclusion app by app and category by category, at account level inside Performance Max rather than campaign level.

This is not a rounding error in your media plan. The agency Producthero looked at placement data across 801 managed Google Ads accounts, 596 of them running Performance Max, covering 532,515 unique placements and 315,073,188 impressions in a 30-day window, and reported that “over 51% of impressions came from Search Partners” with “mobile apps” making up “another 15%,” naming Spider Solitaire and Solitaire Collection as typical examples (Producthero, 12 March 2025). Two caveats belong with that figure. It counts impressions rather than spend or waste, and Producthero sells Performance Max placement tools, so it is a census with a commercial interest in the answer. Taken only for what it measures, it says most of where your Performance Max ads appear is not Google Search.

Most advertisers never touch it either. Nils Rooijmans, who publishes Performance Max audits, wrote in December 2024 that “after conducting audits over hundreds of PMax campaigns, I know that over 80% of them still make this mistake; they DON’T exclude Mobile App placements.”

One inventory type cannot be excluded by an advertiser under any setting. Rewarded ads, the format where a user watches or taps in exchange for a game life or extra credits, are configured on the publisher side and bought programmatically (Google Ad Manager Help). Google’s documentation for the format addresses publishers throughout and describes no advertiser-side control anywhere in it.

Search Partners exclusions are coarse by design. Google’s placement-exclusion documentation notes that “Starting in March, 2024: Account level placement exclusions will now also apply to the Search partner network,” which sounds like progress until the line underneath: “Note that exclusions for subdomains, subsites and subpages do not work on the Search Partner Network” (Google Ads Help). On Display you can exclude a single page. On Search Partners you take the whole domain or none of it.

Google did remove one thing, and it deserves to be said plainly. Parked domains, the placeholder pages sitting on unused web addresses, were cut outright: “Parked Domains (AFD) will cease to be an ad surface within the Search Partner Network effective February 10, 2026” (Google Ads Help). That is a real cleanup of a real problem. It did not touch the other categories of partner site that Adalytics enumerated in its November 2023 research, which Marketing Brew reported and which Google disputed on scope rather than on existence. One surface was removed. The rest of the list was not.

For the mechanics of that alpha toggle, how to find it in your account and how to test it without wrecking your baseline, we wrote that up separately in the Performance Max partners setting playbook. This page is about whether you should want the inventory in the first place.

The detection is aimed at clicks, not at whether the person is real

Everything Google has built to protect you here counts clicks. Its definition of invalid activity is a definition of invalid clicks (Google Ads Help). Confirmed Click asks whether a tap was intended (AdMob Help). The Invalid Activity Credit Report pays you back in “credited clicks” and “credited interactions” (Google Ads Help). Every instrument asks one question: was this click genuine?

None of them asks the question your business runs on. Is the person named on this form a real human who wanted to hear from you? A click filter cannot answer that, because it is not looking at the form. A submission can arrive from an ordinary click, on a real browser and a real device, and still carry contact details that were invented outright or lifted from someone who never filled in anything.

Google concedes the gap in a single sentence. Its invalid-traffic documentation says: “In rare cases, a click may be deemed invalid and removed, but the conversion occurring from that click may not necessarily be” (Google Ads Help). Sit with what that describes. The system catches the bad click, strips it from your reporting and credits you for it, while the conversion that click produced can remain standing in your account, still counting and still feeding your bid strategy.

Then Google hands the problem to you. The same page’s lead-quality guidance tells advertisers to “implement server-side validation for web forms” and to use double opt-in, both of which are work you do on your own side of the form.

That is also how a reassuringly low invalid-traffic rate and a lead file full of junk coexist without either being wrong. The low figure is measured at the click layer. The junk sits one layer down, in the identity attached to the submission, where nothing is looking.

The incentives run the wrong way too. Google’s taxonomy already concedes the first rung, naming “manual clicks meant to increase your advertising costs or to increase profits for website owners hosting your ads” (Google Ads Help). It wrote that motive into its own documentation rather than leaving it to critics. A site paid per click has a reason to want clicks; a partner paid per lead has a far stronger reason to want leads, because a fabricated form is worth many multiples of a fabricated click.

Accidental taps are the mild version, and they are real, which is why Google warns publishers about ads sitting next to play buttons and video players. But a mis-tap at least represents a human who was there. The harder problem is the submission that represents nobody, and no published figure exists for how often that happens on any Google network.

Why the wrong lead does more damage than the wasted spend

This is why the setting matters more for lead gen than for retail.

Performance Max is a bidding system that learns from your conversion actions. Feed it a conversion action defined as “form submitted,” and it will go and find more of whatever produced form submissions, which is not the same population as whatever produced customers. This part is not controversial: Smart Bidding optimizes toward whatever you mark as a conversion. Google’s enhanced conversions for leads exists because the accuracy of that input is what bidding quality depends on, which is how Google’s own documentation describes it, saying the feature “uses user-provided data, such as email addresses, to supplement imported offline conversion data to improve accuracy and bidding performance” (Google Ads API documentation).

Follow it through. If a share of your form fills arrive from inventory where the person did not intend to be, and you count those form fills as conversions, the campaign is not merely spending money badly. It is being taught, by you, that the mis-tap population is the population to pursue. That damage spreads across the whole account rather than staying in the network that caused it, and it survives every budget adjustment you make, because you never changed what the system is optimizing toward.

The bid-strategy fix is the one thing on this page you can do on Monday. Stop optimizing to the raw form submission, and do it in this order:

1. Change the conversion action. Build one that fires only when your CRM marks the lead qualified, rather than when the form is submitted.
2. Feed it back to Google. Import that status through offline conversion import, with enhanced conversions for leads switched on so the match rate holds up.
3. Set the bid strategy. Maximize conversions with a Target CPA, pointed at that new conversion action rather than the old one.
4. Re-scale the target. Divide your old target by your qualification rate. If 40 percent of raw leads survive qualification, your qualified-lead target has to be about two and a half times the old raw-lead target to describe identical economics.
5. Wait out the relearning. The campaign will look worse for two to three weeks. Change it back only if qualified volume falls and stays down after that window, not during it.

This is the fix rather than a nice-to-have because it is the only lever that works whether or not you ever get the network toggle. You cannot exclude rewarded inventory, and you may never get the alpha. You can always change what you count.

The measurement defense, and where it fails for lead gen

The standard defense of these networks is weakest exactly where lead generation lives. That is the finding of this section, and it comes from the research usually cited to make the opposite case.

The defense itself is familiar. Your last-click reporting undercounts display advertising, the argument runs, because display works by influence rather than by capture. The poor numbers sitting next to Display in your account are therefore a measurement artifact rather than a performance problem, and turning it off will cost you real demand you were never able to see.

The first half of that has real support. A 2017 working paper by Garrett Johnson, Randall Lewis and Elmar Nubbemeyer analyzed 432 field experiments on the Google Display Network across 431 advertisers, and reported “median lifts of 17% and 8%” in site visits and conversions. The Display Network produces a real, causally measured effect, and we are not going to pretend otherwise. Two caveats travel with it. The paper was never peer-reviewed, and its outcome is a conversion, which is the very thing whose quality is in question here.

The second half is where the defense breaks. The relevant study is a 2019 paper in Marketing Science by Brett Gordon, Florian Zettelmeyer, Neha Bhargava and Dan Chapsky, two of whom worked at Facebook, whose data it uses. It compared the everyday way advertisers measure ads, by watching who saw them and who converted, against proper randomized experiments that hold back a control group. Those experiments are the closest thing to ground truth the field has, and the everyday method mostly failed to match them. “The observational methods we analyze mostly overestimate the RCT lift,” the authors write. The miss is large: the paper reports that “in 50% of our studies, the estimated percentage increase in purchase outcomes is off by a factor of three.”

That inverts the usual conclusion. When someone tells you your attribution is undercounting Display, the published evidence says any correction is more likely to run the other way, and that the method flatters itself most at precisely the shallow end of the funnel where your business lives.

What this argument does not do

An honest version of this page has to say what it cannot prove.

It does not prove Display and Search Partners leads are worse. We have no network-level lead-quality data either, and we are not going to manufacture some. What we can show is that the controls and the reporting needed to find out were never built.

It does not show that fabricated leads concentrate on these networks specifically. Manufactured contact data is a known problem across paid lead acquisition generally. The argument here is that click-level detection cannot see it and network-level reporting cannot price it, not that one network is provably dirtier than another. Anyone claiming a percentage split by network is quoting a figure that does not exist.

The practitioner record is real but it is not a study. The accounts above are self-reported, several come from people who know each other in the same professional community, and two of them are a single X thread on a single day. Nobody has run a controlled test. We are reporting a consistent pattern among named operators, which is worth something and is not the same thing as measurement.

It does not say blanket-disable. Practitioners genuinely disagree, and the disagreement is not ideological. Adalysis, the account-audit tool co-founded by Brad Geddes, walks through one account running a $185 cost per conversion on Search Partners against $11 on Google Search, and in the same guide shows another account where Search Partners ran the lower cost per acquisition (Adalysis). Neither example carries a sample size. The honest reading is that the answer is account-specific, and that the decision rule Geddes gives is right: judge the network on its own cost per acquisition, not on click-through rate.

It does not accuse the network of fraud, and Google’s rebuttal to the 2023 brand-safety research stands unrebutted. Google said the product at the center of those findings represents “a miniscule amount” of the network, and that for the average campaign spend “lands overwhelmingly on Google Search” (Marketing Brew). Nobody has answered that with better data.

It does not tell you what the alpha toggles default to, because that has never been announced. The partner-selection control is an unannounced pilot with no self-service signup (PPC Land), and anyone describing its rollout schedule is guessing.

What to do when you cannot get the toggle

Most accounts will not get alpha access, so the plan has to work without it.

Measure the channel, not the placement. You cannot get cost per qualified lead by partner domain and you never will, so stop trying. What you can get is the network-level split, which is exactly what the advertiser at the top of this article did: segment by network, take the cost Google reports at that level, and divide it by the leads your CRM later marked qualified. Almost nobody computes it, because it means waiting on the CRM instead of reading a column in Google Ads.

Then work the levers you do have, in this order:

1. Retrain the signal. Import qualified-lead status from the CRM as your conversion action and point the bid strategy at it, exactly as above.
2. Exclude the obvious. Apply account-level placement exclusions for app categories with no plausible relationship to your buyer. For a home-services or insurance advertiser that usually means casual and puzzle games, kids’ apps, and utilities like flashlights and battery savers. It is laborious and incomplete, and still worth doing.
3. Check the identity, not just the outcome. Google’s own lead-quality guidance tells you to “implement server-side validation for web forms” and to use double opt-in to confirm interest (Google Ads Help). Take the advice, and notice what it concedes: the only place a fabricated submission gets caught is on your side of the form. That check is also what makes step 1 trustworthy, because a qualified-lead signal built on unverified contact data just launders the same junk into your bid strategy.
4. Run the split long enough. Measure across a full sales cycle rather than two weeks, because a lead-gen sales cycle outlasts every reporting window Google’s interface encourages you to look at.

If the qualified-lead economics come out fine, leave the networks on and stop worrying about them. That is a real possible outcome, and we would rather you find it than take our word for anything.

If your spam volume is the immediate problem rather than the slow-burn quality question, the Performance Max spam-leads playbook covers the triage, and if you suspect the traffic is genuinely non-human rather than merely disinterested, the tests for that are in our guide to invalid clicks and verification against ad fraud. For the sibling problem of placement control in Demand Gen, see the placements exclusion audit. The same problem has a Meta counterpart, where the Audience Network is the placement in question. See blocking placements on Meta ads.

Why this argument never gets settled, and where the burden actually sits. Advertisers have been reporting the same complaint about this inventory for years, always with the same specifics, and it has never hardened into evidence anyone can point at. There is a structural reason for that, and it is not that the complainers are wrong or that Google is hiding a spreadsheet. It is that the placement report carries impressions and nothing else. To prove waste at the placement level you would need cost and conversions attached to a domain name, and no advertiser has ever been given those columns. So the people best positioned to document the problem are precisely the people who cannot, and the disagreement stays permanent by construction.

That is what makes the usual advice backwards. You are asked to accept an unmeasured risk on the grounds that nobody has proven it exists, while the only party able to publish the answer is the one selling the inventory, running the filters and controlling every column in the report. Demanding the number before you spend is not the cautious position here. It is the only one that survives contact with what the reporting will and will not tell you.

Frequently Asked Questions

Should I turn off Display in Performance Max?

Not on principle, and not before you have measured it. Fix the conversion signal first, since that works whether the networks are on or off, then compute cost per CRM-qualified lead segmented by network across a full sales cycle. If the qualified economics hold up, leave it on. Most accounts cannot turn Search Partners off inside Performance Max anyway, because the control sits in a limited alpha with no self-service signup (PPC Land), so the measurement work is not optional in the way the toggle is.

Are Display Network leads any good?

Nobody has published the answer, which is the honest state of the question in August 2026. The Display Network has real, independently measured lift on commerce outcomes, covered above in the measurement section. No comparable study exists for lead quality, connect rate, or the share of leads a sales team accepts. Your own CRM is the only place that number can currently exist, which is an annoying answer and also the true one.

Can I exclude Search Partners from Performance Max?

Only if your account has the limited alpha that adds partner-network checkboxes to campaign settings, which has no announced rollout and no self-service request path (PPC Land). Without it, your options are account-level placement exclusions applied domain by domain, and Google notes that “exclusions for subdomains, subsites and subpages do not work on the Search Partner Network” (Google Ads Help), so a partner property is an all-or-nothing call.

What is the Search Partner placement report actually showing me?

Domain names and impression counts, and nothing else, since the August 2025 rollout (PPC Land). It is genuinely useful for spotting a domain you want to exclude on brand grounds. It cannot tell you whether any domain on that list made or lost you money.

Is this ad fraud?

Not in the sense the phrase usually carries, and reaching for it weakens a better argument. We are not claiming these networks are riddled with fraud, and no published evidence would support that. The narrower point is structural: Google’s protections operate on clicks, while the thing that damages a lead buyer is a submitted identity that belongs to nobody. A click filter is not built to catch that, which is why a low invalid-traffic percentage and a junk-filled lead file can coexist without either one being wrong.

What should I measure instead of conversions?

Cost per CRM-qualified lead, segmented by network, measured over a full sales cycle. Raw conversion count is the metric most likely to reward the exact traffic you are trying to diagnose, because a low-intent form fill is cheap and plentiful and looks identical in the Google Ads interface to a lead your sales team would fight over. Import the qualified status back into Google Ads as your conversion action so the bid strategy optimizes toward it, which Google’s documentation describes as improving “accuracy and bidding performance” (Google Ads API).

Work with Elevarus

Elevarus buys media and delivers calls and leads in HVAC, solar, roofing, U65 and ACA health, auto insurance and life insurance. If you would rather buy the qualified outcome than run the network experiment yourself, talk to us about cost-per-call and cost-per-lead programs.