In the dynamic realm of modern marketing, the integration of Artificial Intelligence (AI) has emerged as a crucial asset for businesses seeking to secure a competitive edge. This series of blogs delves into the dynamic intersection of AI and marketing strategies, uncovering how intelligent algorithms and machine learning are reshaping the landscape. From crafting personalized customer experiences to facilitating data-driven decision-making, join us as we explore the transformative power of AI in marketing. These articles provide insights and practical applications, catering to both seasoned marketers and those embarking on their digital journey. By demystifying the role of AI, we aim to shed light on its profound impact on the future of marketing.
Google’s Performance Max (PMax) promises a massive $20 billion enhancement in programmatic advertising efficiency through advanced AI-driven decision-making. However, it also presents marketers with a challenging dilemma, forcing them to trust the opaque algorithmic ‘black box.’ Campaign explores.
Google's unveiling of Performance Max (PMax) in 2021 appeared to offer marketers the ideal solution—the ability to enhance marketing efficiency, elevate performance, and yield superior returns on investment (ROI) across the platform's diverse array of channels, spanning YouTube, Search, Shopping, and Discovery.
The crux of PMax's commitment centred around Google's AI, entrusted with critical decisions ranging from bidding strategies to creative elements, search query alignment, and media environment choices. This innovation encouraged many marketers to explore online video experimentation, exemplified by endeavours like YouTube Shorts.
Nevertheless, like other AI and machine learning-driven advertising platforms, whether they originate from Google, The Trade Desk, Yahoo, or others, marketers are compelled to rely on the enigmatic 'black box' of algorithms. Depending on a 'black box' of algorithms necessitates prudent scepticism.
The inherent challenge with all such black box systems lies in marketers effectively surrendering control to the algorithms. In the case of PMax, where Google takes the reins across the board, it entails an even greater faith in the system's capabilities.
As the rise of generative AI starts to influence programmatic media buying, Google recently announced more AI-powered ad products, including generative AI in PMax, enabling advertisers to develop creative assets and headlines through natural language conversations with AI.
Google plans to show AI-generated ad content across its platforms, testing AI-based search experiences like 'AI Snapshot' and providing AI-generated summaries and sponsored links in search results.
As Google hastily (Microsoft was first to market, with Google following swiftly suit inspite of existing issues with the PMax) adds generative AI to PMax, Campaign explores why it is essential to understand the genesis of ad fraud, and how marketers can have algorithmic transparency to truly make the most of their spending in their campaigns. More importantly, we dig into how marketers can make the most out of the PMax black box.
For the first part of the article, we talk to Sapna Chadha, vice president for Google in Southeast Asia and South Asia Frontier on how Google is fulfilling the promise of AI marketing in SEA.
In a separate interview, we speak to ad fraud platform TrafficGuard and SquareX, a browser-based cybersecurity platform, to investigate how PMax is performing for marketers. 
How Google approaches AI marketing
In a conversation with Campaign, Sapna Chadha, vice president for Google in Southeast Asia and South Asia Frontier, says Google firmly believes in the effectiveness of its AI solutions, which have been in development for a considerable time.
She argues this is not a fad or trend as it is a field Google has dedicated substantial effort to over the years. Chadha points out that in marketing, AI offers tremendous potential, particularly in key areas: Content creation and analysis, prediction, and decision-making.
"While AI is not a new concept for us, our products like Performance Max have quietly worked in the background, aiding advertisers in maximising their time and return on investment. Features like intelligent bidding have been seamlessly integrated over the years," says Chadha.
"Today, businesses are increasingly adopting advanced AI applications beyond predictive analytics. We are convinced that AI's role in empowerment and business success is more crucial than ever. Although we are in the early stages of this journey and continue to test and learn, we are committed to ensuring that AI not only drives substantial business value but also does so responsibly. Balancing both objectives is our ongoing mission."
Chadha claims on average, advertisers adopting PMax achieve 18% more conversions at a similar cost per action.
For example, she says Singapore's Coco and Eve increased revenue by 32%, and Thailand's Izuzu, a traditional auto player, boosted qualified leads by 67% while lowering costs by 49%. Hotels too, reap the rewards—like Minor Hotels, which increased sales by 86% and improved return on ad spend.
"With generative AI, now integrated into PMax. Advertisers simply provide their website and details about their brand, and AI takes it from there. It can generate professional-grade creatives across YouTube, display, and search. This marks a significant leap as AI ventures into content creation," says Chadha.
"With AI handling predictive analytics, marketers can shift their focus to strategic thinking. AI significantly reduces turnaround times while maintaining optimisation in today's fast-paced business landscape. Rushing to implement something incorrectly becomes less of a concern, thanks to robust predictive analytics support."
Chadha adds: "Ultimately, AI empowers marketers, advertisers, and agencies in profoundly different ways, enhancing their capabilities and effectiveness in navigating the evolving advertising landscape."
On how Google ensures privacy and content authenticity as AI becomes more integrated into search experiences, Chadha says a 'solid commitment' to responsibility underpins Google's approach, a value it holds in high regard.
Chadha says getting privacy and content authenticity right is paramount to Google, and the platform prioritises incorporating user and stakeholder feedback. She notes Google has been advancing AI in search for many years and maintains a rigorous evaluation process to uphold its high standards.
According to Chadha, Google has built these new capabilities upon its core ranking systems, which have existed for decades. These systems include robust protections against harmful or misleading information, ensuring Google prioritise returning high-quality information for topics where confidence in results is crucial.
In addition to privacy concerns, Chadha says Google is equally dedicated to representing data in a committed manner.
Independent third-party measurements are a part of Google's commitment, emphasising accuracy while safeguarding user privacy and assisting advertisers in measuring all impressions covering various areas.
"We are responsible for enforcing policies that enhance user safety when using our products and safeguarding the broader ecosystem. We have implemented privacy-preserving technologies that empower users to control how their data is used," explains Chadha.
"Initiatives like the My Ad Center, launched in 2023, offer users granular control over data for personalising ads, allowing them to opt-out anytime. In Ad Settings, users can manage data and choices within their Google accounts. Privacy and responsibility are fundamental principles that guide our actions."
The problems with 'black box' solutions
While PMax solutions aim to build-in protections for marketers, some in the industry feel marketers can only feel confident with greater visibility. An investigation by TrafficGuard reveals a disturbing trend of AI optimising to exploit, not empower, marketers.
In traditional programmatic, invalid traffic and click fraud occur daily, spanning search, mobile, and affiliate campaigns.
For example, in search, TrafficGuard has seen between 5% to 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.
When addressing affiliate fraud, specifically for high-payout categories such as sports and sports-fantasy betting, as well as subscription and entertainment services, TrafficGuard has seen click fraud and affiliate cookie stuffing through malevolent browser extensions siphon away $100,000 of affiliate payouts per month, harming marketers and publishers.
Mat Ratty, the chief executive officer of TrafficGuard, explains that limited granular reporting in PMax means that while marketers get broad campaign insights, they cannot see if display, search, video, or shopping ads drive clicks and conversions. 
"This would be great if the world was perfect or 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," Ratty tells Campaign.
"Marketers might not understand the factors influencing their campaigns' success without insight into how these algorithms operate. This lack of clarity can lead to misalignment between marketer goals and algorithm decisions."
Ratty says the most significant concern that the industry is grappling with is tackling ad fraud, as bad actors are shifting their focus from general programmatic fraud to targeting campaigns without insights.
The recent supply chain study conducted by ANA demonstrates waste and inefficiencies in the existing programmatic supply chain, and PMax is no exception.
Limitations in data reporting with PMax
There are genuine limitations of granular reporting in PMax, making it difficult for marketers to discern the specific channels driving clicks and conversions.
Google conveys that its machine learning comprehends value determinants, even if advertisers hold differing opinions, though they lack visibility into PMax's decision-making.
PMax prioritises conversions regardless of the channel, focusing on results rather than ad placement. This lack of granular data reporting means that inefficiencies and invalid traffic can creep in through all crevices of campaigns.
While up to 15% of search clicks come from bots, as mentioned above, not all instances of invalid traffic bear malicious intent.
For example, TrafficGuard concluded that 97% of a user's Google brand campaign ad budget was consumed by returning users 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 disturbing, particularly concerning 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% and, for one client, the claimed clicks and installs exceeded the population of the targeted geography in a week!" says Ratty.
"We have observed on PMax, a mix of new fraud tactics and some of the same types of invalid traffic and fraud that we see across programmatic. Given that PMax and most AI systems assume positive user intent, invalid traffic in PMax campaigns comes because AI thinks every 'user' engagement is positive."
Ratty explains when bad actors exploit the AI's conclusion that every 'user' engagement is positive and creates fake intent signals, it can train the algorithm to optimise towards the source of the invalid traffic.
Suppose the AI optimises towards the source of the invalid traffic. In that case, it can result in wrongly optimised campaigns that divert and deplete advertising budgets by driving more fake engagement and conversion events. 
"To be fair, this is not misconduct by Google or PMax. However, when AI optimises towards invalid traffic, budgets can be exploited when there is opacity and no real-time third-party oversight and intervention," says Ratty.
"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. They face the possibility of unknowingly running the risk that they will just be pumping money into a high-speed Ai-optimised invalid traffic infiltrated machine."
Indiscriminate data collection
Recent revelations about YouTube's challenges safeguarding children's privacy have sent ripples through the digital landscape. Following this, a privacy alert from IPG Mediabrands advised clients' should consider' a pause on campaigns using PMax. 
The fact that the PMax AI may have inadvertently been showing ads to children on YouTube is concerning, not only from a data privacy perspective and breaching the Children's Online Protection Act (COPPA), but also from the perspective of advertisers wanting to maximise their returns.  
The affected brands, including major advertisers such as Kimberly-Clark, General Motors and Procter & Gamble, have engaged in tactics that are not extraordinary.  
For example, taking a user who clicks on your ad to your website is standard practice. Once there, a website typically collects as much data as possible to market to them and convert them into customers.  
None of this is a revelation, but what has become apparent is that collecting all visitor data this way, regardless of how the visitor found your site, may open up businesses to many problems and liabilities. 
"To be clear, this issue is not simply a PMax issue, nor is it merely a Google issue. Advertisers need to take steps to distinguish between what data they can and cannot collect, and that distinction is not easy to manage,” explains Ratty. 
"Unfortunately for advertisers, placing blame on a third party for sending you the wrong types of visitors may not be enough. A choice was made to advertise on a platform, and a choice was made to collect and retain data automatically. Should an authority look into a business' data collection practices, ignorance will not be bliss!" 
Pragmatically, it is unlikely that any company could ascertain with 100% confidence that they can distinguish between visitors they can and cannot collect data on.  
Still, at the very least, businesses should demonstrate, through their processes and technology, that they take the matter seriously and are making a real effort to do so. 
Vivek Ramachandran, the founder of founder of SquareX, backed by Sequioa Capital, says unfortunately, it is very difficult for brands to avoid indiscriminate data collection, given that most users who operate online have a veil of anonymity, which is built into the way they access sites or information online. 
However, he says it is important for brands that wherever they advertise, to exercise clear privacy and data collection policy and to ensure that they have a history of following that policy. 
Ramachandran also advises brands must ensure that they are constantly monitoring the changing policies of these platforms on an on-going basis, to ensure that they are updated with the latest updates and changes. 
“Privacy is a very complex topic, but more importantly, it is very jurisdictional in nature. So advertisers need to be very cognisant of the legal jurisdiction of their target audience and what those jurisdictions allow,” Ramachandran tells Campaign.
“Of course, there is a moral aspect that even though data collection may be allowed in a certain way, do you morally want to go ahead and use that data and do targeted advertising? And this is really where it is important for advertisers to create their own moral code and system which they will follow above following the laws, where they are targeting their potential audience.” 
The concerns about PMax's AI operation raise a critical question for advertisers: Is the collected data beneficial or detrimental? If PMax targets children who click on ads more than adults, the algorithm may optimise for this engagement, resulting in wasted budgets on the wrong audience. 
This negative loop could erode ROI. Moreover, these child visitors, leaving quickly, taint genuine visitor data, weakening analytics and ROI.  
Beyond ethical concerns, avoiding this scenario is vital. It undermines transparency, focus, insights, and ad investment goals. Undoubtedly, advertisers should prevent this data. 
"Amidst the data-gathering frenzy, brands must evaluate their actual data needs. A resolution to balance optimisation and security involves adopting a decisioning engine upfront on the website's data path," says Ratty. 
"This engine assesses whether inbound visitor data should proceed downstream for collection by marketing and analytics tools. This approach doesn't hinder ad placement or visitor access but prevents low-confidence data from reaching downstream devices. The result? Diminished exposure to undesirable data, bolstering the data quality you desire, and more importantly, ensuring legal compliance. It's a mutually beneficial strategy." 
Is algorithmic transparency the road to success?
The industry should have a sense of optimism regarding the potential of what AI can bring to the table to drive better marketing performance. Automation and operational efficiencies offer tangible value to realise.
In addition to summarising search results, Google's AI-driven Search Generative Experience (SGE) will now provide article summaries when users click a link, making web reading more efficient.
Chadha says SGE has the potential to benefit both users and advertisers by offering valuable information and fostering meaningful connections in a novel and improved manner.
"Since ads serve as a bridge between people and businesses, their effectiveness is often linked to factors like commercial intent and user and advertiser interest," explains Chadha.
"Through these search experiences and our experimentation with new technologies, we can discover fresh ways to deliver relevant information and connect users with businesses and advertisers. The realm of possibilities that AI opens up is truly exciting. The principles applied in the search generative experience will align with how marketers leverage AI tools to enhance their campaign strategies. This will likely lead to more excellent optimisation, time savings, and improved content seamlessness. "
She adds: "Ultimately, this will help connect the dots between various complex topics and enable us to align diverse intents over time. However, it's important to note that we are still in the early stages of experimentation, with more insights to gain as we progress through our labs."
However, whether it's PMax or any other AI-led solutions, marketers must push for algorithmic transparency, invest in independent oversight, and not unquestioningly trust the little black box of algorithms if they genuinely want to drive the best fraud-free performance.
Transparency also benefits consumers, enhancing their understanding of how companies use their data and present content to them. Practising transparency fosters a sense of control, privacy, and ethical treatment, which are essential for maintaining positive brand-consumer relationships
"In essence, algorithmic transparency cultivates a healthier digital ecosystem where marketers can make informed decisions, consumers can trust their interactions, and technology evolves ethically, serving the interests of all parties involved," shares Ratty.
Editor's note: An earlier version of this article positioned Chadha's interview as a response to industry concerns. To clarify, Chadha had not yet been presented the industry concerns outlined in this article to reply to.  
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