Bridging the Gap: Leveraging Adaptive AI to optimise Google PMax
In the increasingly intricate world of digital retail, marketers are faced with more channels, data points, and customer expectations than ever before. Traditional manual approaches to managing advertising campaigns are proving insufficient in keeping pace with this complexity. Automation is no longer a luxury but a necessity in today’s marketing landscape.
Retailers must now contend with vast product portfolios, proliferating digital channels, and customer journeys that span multiple touchpoints. The manual intervention once relied upon for tasks such as bidding strategies or budget allocation is no longer viable at scale. This is not just about optimising a single campaign—it’s about managing thousands of SKUs, each with unique demand dynamics, while reacting to real-time shifts in the market. The rise of platforms like Google’s Performance Max (PMax) has been an answer to these growing complexities, but even with PMax, retailers are facing some challenges.
The Human Limit: Why Automation is Essential
The volume of decisions that need to be made in modern retail advertising has outstripped human capability. Every few seconds, there are countless adjustments to be made in bidding, budget allocation, and audience targeting based on rapidly shifting market conditions. No team of marketers, no matter how skilled, can manually manage these intricate layers effectively.
Automation, powered by AI, becomes critical to handling the sheer volume and complexity of modern retail. It’s not about replacing human expertise but augmenting it. Marketers still need to guide the strategy, but Adaptive-AI is essential to execute it at scale.
As famously quoted by the Economist Richard Baldwin at the 2023 World Economic Forum’s Growth Summit, putting it in marketing context:
“It’s not that AI is going to replace marketers, but marketers who use AI will replace those who don’t.”
This underscores the reality that without leveraging the power of automated and adaptive AI systems, brands risk falling behind.
PMax: A Powerful Yet Limited Tool
Google’s Performance Max platform has been designed to streamline advertising campaigns across Google’s vast network. It offers powerful automation by integrating multiple channels such as Search, Display, and YouTube into one cohesive system. For retailers, this sounds like a dream: reduced manual effort, broad reach, and an algorithm that handles much of the heavy lifting.
However, the platform’s reliance on predefined algorithms presents its own set of challenges. PMax functions like a black box, with many decisions made by the system hidden from the retailer’s view. While this is efficient, it also limits marketers’ ability to make nuanced adjustments. For example, PMax tends to allocate spending to “hero” products—the top performers—leaving a long tail of potentially profitable items underutilised. Retailers are left with little visibility into why certain decisions are being made and lack the ability to intervene quickly when market conditions change.
The Rise of Adaptive AI: Augmenting Automation with Intelligence
This is where an Adaptive AI solution like Upp.ai becomes indispensable. It’s constantly evolving in real-time, continuously learning from both internal (retailers’ inventory data, product data) and external data points (competitor pricing) to make smarter, more tailored decisions.
For instance, Upp.ai creates individual demand elasticity models for every SKU in a retailer’s inventory. This allows it to optimise each product’s performance, not just the top sellers. Moreover, it integrates real-time factors like seasonality, weather, and market dynamics to adjust campaigns dynamically.
Our solution empowers retailers with more than just automation—it offers control and insight. Unlike traditional systems that operate in a black box, we provide transparency and the flexibility for marketers to make strategic interventions when needed.
Real-World Success: B&Q and Charles Tyrwhitt
The results are already speaking for themselves. For retailers like B&Q, we drove an increase in return on ad spend (ROAS) from 6 to 8, unlocking significant additional revenue. By spreading budget allocation across the full product inventory, rather than focusing on a narrow set of top performers, B&Q was able to scale its advertising efforts more intelligently.
Similarly, Charles Tyrwhitt used Upp.ai to capitalise on an unexpected demand for overcoats during a summer cold snap. While competitors were pushing typical seasonal products, Upp.ai detected the shift and adjusted Charles Tyrwhitt’s campaigns in real-time, allowing them to seize a unique market opportunity and outpace their competition.
The Future of Retail Advertising
The future of retail advertising lies in the intersection of automation and adaptability. Platforms like Google PMax offer a strong foundation, but to truly thrive in today’s complex environment, retailers need more than just automation—they need the intelligence and flexibility that adaptive AI provides. By combining the strengths of both, marketers can optimise their efforts at scale while maintaining the control and strategic insight necessary to respond to an ever-changing market.
