In this op-ed, Matthew Ratty, CEO of TrafficGuard (pictured) explains that When Google announced Performance Max (PMax), it seemed like the answer to every marketer’s dream. But something has gone awry.
PMax offered marketers the chance to drive efficiency, performance and better ROI across all of Google’s channels including YouTube, Search, Shopping and Discovery.
At the core of the PMax promise was Google’s AI, making decisions on everything from bidding, to creative, to search query matching and media environments. For many marketers, this even helped open the door to experimenting with innovation in online videos, such as YouTube Shorts.
However, akin to all AI and machine learning-driven advertising platforms, whether originating from Google, the Trade Desk, Yahoo, or numerous others, PMax requires that marketers place trust in the enigmatic algorithmic ‘black box.’ This calls for a dose of prudent scepticism.
The problem with all black box systems is marketers are at the mercy of the algorithm. In the case of PMax, where Google manages everything, it requires an even higher level of faith in the system. Limited granular reporting in PMax means that while you get broad campaign insights, you won’t be able to see if it’s display, search, video, or shopping ads driving your clicks and conversions.
This would be great if the world was perfect or if you only spent money on Google channels. But marketing is complex, with multiple media partners in any one campaign, and we all know from experience that industry opacity can be exploited to the detriment of marketers and their budgets.
Transparency and accountability are indispensable for marketers to operate with utmost effectiveness. This is why we think marketers should have access to expert analysis allowing them to make more informed decisions about PMax and all AI-driven optimization platforms.
Invalid Traffic is targeting PMax campaigns
It should come as no surprise that bad actors are shifting their focus from general programmatic fraud to targeting campaigns with no insights. The recent supply chain study conducted by ANA demonstrates that there is waste and inefficiency in the existing programmatic supply chain.
PMax is no exception, with the same underlying risk from invalid traffic (IVT) as we have seen on traditional programmatic campaigns. For the purposes of this piece, the definition of invalid traffic is traffic that neither contributes to incremental growth nor originates from human sources, encompassing entities like bots and data centres.
In the realm of traditional programmatic, invalid traffic and click fraud occur on a daily basis, spanning search, mobile, and affiliate campaigns.
For context, in search, we have seen between 5-15% of search clicks come from bots seeking to exploit paid search campaigns to sign up or claim incentives within the ads or worse, deliberately exhausting clients’ search budgets as a “competitive” tactic.
Of course, not all instances of invalid traffic bear malicious intent. For instance, we found that 97 per cent of one user’s Google ad budget was being consumed by returning users who were just using Google as a front door to click on a paid ad to log in to their account.
In the mobile domain, the figures we observe are even more worrying, especially for app install campaigns within sectors like car sharing and food delivery.
Instances of fraudulent app installs have surged to alarming rates, reaching up to 50 per cent and, for one client, the claimed clicks and installs exceeded the population of the targeted geography in a week!
When addressing affiliate fraud, specifically for high-payout categories such as sports and sports fantasy betting as well as subscription and entertainment services, we have seen click fraud and affiliate cookie stuffing through malevolent browser extensions siphon away $100,000 of affiliate payouts per month – harming marketers and publishers. Both those marketers and publishers that are being targeted should be concerned, especially with so many publishers pivoting to affiliate sources to offset general advertising challenges.
What we have observed on PMax is a mix of both new fraud tactics and some of the same types of invalid traffic and fraud that we see across programmatic.
As with most AI systems, PMax assumes every “user” engagement is positive in intent. When bad actors exploit this and create fake intent signals, it can end up training the algorithm to optimize towards the source of the invalid traffic. This results in wrongly optimized campaigns that divert and deplete advertising budgets by driving more fake engagement and conversion events.
To be fair, this is not malfeasance by Google or PMax, however, when AI is optimising towards invalid traffic, budgets can be exploited when there is opacity and no real-time third-party oversight and intervention.
PMax is simply a microcosm of what happens across the entire internet. The challenge lies in marketers who employ AI buying systems without independent third-party auditing and analysis, increasing the risk of simply pumping money into a high-speed AI-optimized ‘invalid traffic machine’.
What our client data shows about PMax
Our trials of our PMax analysis platform focused first on providing transparency of what channel type (search, shopping, display, video) is driving the conversion results. While Google’s AdManager interface for Performance Max fails to display this information, we found a way to provide visibility into these insights – because transparency matters when fighting fraud.
This includes an ability to clearly, by channel, for each and every PMax campaign, in real-time, identify where your money is going and what is driving your performance. Solving for what the ANA recently highlighted as the inefficiencies and waste that would otherwise come from the lack of access to data.
Access to real-time channel data provides the transparency and insights needed for advertisers to protect their entire PMax spend. For example, with one of our clients, who had trusted their paid search budget entirely to PMax, we identified where PMax was cannibalizing their branded keywords and highlighted that these keywords would perform better in a stand-alone search campaign where there is full control and transparency.
Additionally, our client saw PMax bidding on low-performing search terms that resulted in rapid burning of daily budgets on terms any experienced search marketer would normally exclude. This was not fraud per se; it was AI optimizing to suboptimal outcomes. Armed with this data, marketers can then confidently add brand exclusions across PMax (to avoid the wasted overspend on branded keywords) and add account-level negative keywords for extremely poor-performing generic terms.
Within PMax we are seeing a tendency of the algorithm to over-optimize towards paying for clicks from customers you already have – this has been a historic issue with any search PPC campaign, but has accelerated with PMax.
Existing customers who are “lazy browsers” and use Google to simply get to the homepage by way of clicking on a paid ad to get to the login section, or to find the customer service details are a honeypot for PMax’s AI bias for clicks and engagement. Clearly, it’s not logical for marketers to invest in these outcomes from their existing customers, when they could allocate their marketing budgets towards acquiring new customers, it simply adds to the Customer Acquisition Cost (CAC).
One of our clients saw over 50 per cent of their invalid traffic via PMax being funnelled into paying for existing customers to come to the website. We have made it possible for marketers to dynamically set click frequency thresholds on returning users, as well as filtering out bot traffic, forcing the AI algorithm to search for new valid users across PMax.
In terms of outright fraud on PMax, our data shows 7.5 per cent of PMax clicks were invalid across various campaigns. This included clearly identified fraud or highly suspect user engagement where secondary on-site user behaviour was not consistent with a qualified adult human audience. The good news is that this can be stopped. Real-time analysis via our website tags and a direct Google Ad Manager integration made it straightforward to identify and then protect client’s spend across the entire PMax campaign. This includes automatically passing to Google PMax the necessary data points required to mitigate invalid traffic so they were no longer targeted, helping clients acquire real audiences and incremental conversions, and reducing wasted budgets in the process.
What should marketers do about PMax?
All things considered, the industry should be optimistic about AI’s potential to drive better marketing performance. There is real value to be realized in automation and operational efficiencies to be gained.
However, whether it’s PMax or any other AI-led solutions, marketers must push for algorithmic transparency, invest in independent oversight, and not blindly trust the little black box of algorithms if they truly want to drive the best fraud-free performance. Otherwise, bad actors, whether they target PMax or any other AI-led advertising solution, will exploit trust for their benefit, draining marketing budgets in the process.
