The new Gross Profit Optimisation (GPO) setting in Google Ads shifts the focus from revenue-based metrics to profit-driven performance. By integrating Cost of Goods Sold (COGS) and cart data, businesses can optimise campaigns with greater precision, making data-informed decisions to maximise profitability. Initially in limited release, GPO aims to improve ad efficiency by aligning spend with profit margins rather than just revenue targets. While GPO promises efficiency, higher returns, and more intelligent use of data, it raises important questions about data privacy, regulatory risks, and control. A significant concern is how Google’s Gross Profit Optimisation (GPO) setting could influence both public policy and the company’s own product pricing strategies. Much like financial institutions assess credit risk to determine loan eligibility or interest rates, Google’s access to granular business data—such as profit margins, cart sizes, and cost of goods sold (COGS)—gives it a unique and potentially influential vantage point. smL delves deeper into these issues in the analysis below.
Key Features and How It Works
The GPO campaign setting shifts the optimisation metric from traditional ROAS (Return on Ad Spend) to POAS (Profit-based tROAS), aiming to maximise campaign profitability. To implement this, advertisers need to feed COGS and cart data into Google Ads, allowing for more accurate profit measurement and dynamic bid optimisation. Early trials indicate a 15% uplift in profit using this model, demonstrating its potential for enhancing campaign performance.
However, the shift to GPO comes with a new set of challenges and considerations, particularly in terms of data sharing and the implications of Google’s access to such detailed commercial information.
Implications for Digital Marketers and Brands
For digital marketers, this new setting (potentially) provides greater precision in ad targeting and profitability. Agencies and marketing teams can optimise campaigns toward profit rather than top-line revenue, reducing inefficiencies in ad spending. Brands may benefit from leaner budgets focused on high-margin products, improving their overall return on investment (ROI).
However, the GPO feature introduces operational complexities. Marketers need to invest in data integration tools to pass COGS and cart data into Google’s ecosystem. The setting also demands continuous monitoring to ensure that the automated bidding aligns with business goals.
Potential Risks for Brands: Data Privacy and Loss of Strategic Control
Sharing COGS and product-level margin data with Google raises concerns about data privacy and confidentiality. Brands may inadvertently expose critical business intelligence—such as product profitability or operational margins—providing Google with an unparalleled view of their financial health. This could give Google the ability to forecast business vulnerabilities or strategically adjust bidding algorithms to maximise its own revenue, much like banks assess credit risks and pricing opportunities based on customer profiles.
Influence on Government Policy
There is a possibility that the aggregated data from GPO campaigns could be utilised by governments in ways beyond market regulation, particularly in areas such as taxation. With detailed insights into a business's profitability and operational efficiency, tax authorities may gain an unprecedented level of visibility into which companies might owe additional taxes or require stricter financial audits. This could introduce new regulatory risks for businesses that are unknowingly sharing commercially sensitive data with Google, which could eventually be leveraged by external bodies under data-sharing or regulatory compliance agreements.
In some jurisdictions, governments are increasingly scrutinising digital platforms as part of a larger push for transparency in business operations and tax accountability, such as Australia’s ATO compliance initiatives and the OECD's BEPS (Base Erosion and Profit Shifting) framework. There is a conceivable risk that the type of data gathered by Google through these campaigns—detailed revenue streams, operational margins, and profit drivers— could align with government priorities for tax enforcement, raising concerns about privacy and overreach.
Google's Potential Use of Commercial Data: A Competitive Advantage?
On the commercial side, the data Google collects may also be used to refine its own pricing models for advertising products. Having intimate knowledge of what a business can afford and how much profit it generates gives Google a strategic advantage in setting ad rates. Just as banks tailor credit offerings based on a borrower’s financial profile, Google could theoretically develop nuanced pricing strategies that reflect not only market conditions but also the financial health and performance metrics of individual businesses. For instance, advertisers with higher gross margins might be charged higher rates, justifying the pricing as "performance-based" or "profit-aligned."
Moreover, Google’s deeper insight into business operations could shift the power dynamics between advertisers and the platform. Companies might find themselves at a disadvantage, with fewer opportunities to negotiate ad pricing, as Google would have clearer knowledge of how much advertisers can afford to pay. This raises ethical concerns about transparency and fairness in ad pricing, especially for smaller businesses that may already struggle to compete against larger, well-funded competitors.
Industry Concerns: Balancing Opportunity with Risk
While GPO offers potential profit increases and enhanced campaign targeting, it also transfers significant control over campaign outcomes to Google’s algorithms. Marketers need to adopt a cautious approach by carefully balancing automation with strategic oversight.
Furthermore, industry watchdogs and privacy advocates are likely to scrutinise this feature, particularly if it appears that Google is using shared data for purposes beyond campaign optimisation. Businesses should also be prepared for potential legal challenges, especially in regions with strict data privacy regulations such as the GDPR in Europe or the Privacy Act in Australia.
Recommendations for Marketers
Given the potential opportunities and risks associated with GPO, businesses should take the following steps to maximise benefits while minimising risks:
Data Sensitivity Audits: Review what data is shared with Google and assess the potential risks to business confidentiality.
Strategic Oversight: Maintain control over campaign goals and budgets to prevent misalignment with automated bidding.
Engage with Legal Counsel: Ensure that the use of GPO complies with regional data privacy laws and industry regulations.
Pilot-Test the Feature: Start with a small-scale campaign to evaluate performance before rolling it out more broadly.
Monitor for Pricing Changes: Track Google’s pricing behaviour to detect any patterns that suggest the platform is leveraging shared data for competitive advantage.
A Double-Edged Sword for Digital Advertising
Google’s Gross Profit Optimisation setting represents a major innovation in campaign management, offering advertisers the ability to target profitability directly. However, the feature introduces new risks, including data privacy concerns, regulatory oversight, and the potential for Google to use commercial insights to shape its own business strategies.
Marketers and brands must approach this development with a strategic mindset, ensuring that they remain in control of their data and campaign goals. By balancing automation with oversight, companies can harness the power of GPO without compromising their competitive edge or falling into regulatory traps.
Ultimately, while GPO could reshape the digital advertising landscape, it also places greater responsibility on marketers to safeguard their business interests. As the industry continues to evolve, businesses will need to remain agile and vigilant, ready to adapt to both the opportunities and challenges presented by this new feature. If you have any questions or need further assistance, reach out to Raj, Fiona or Rahul at hello@sml.digital.