Holiday Readiness: The Absolute Imperatives for Retailer Growth
While professional sports teams vie for championships with millions watching, a quietly intense competition is taking place now and throughout the holidays across retail media.
Commercial potential and consumer intent are high, but captivating attention and driving conversions is more competitive than ever. Indeed, according to Emarketer, global retail media ad spend is projected to hit $168 billion this year.
While nearly two-thirds of retailers now have a retail media network (RMN), many are on legacy tech that doesn’t scale competitively. Unfortunately for them, being slightly less effective doesn’t just mean winning slightly less advertiser budget; it often means winning none at all.
So, what can retailers do? Instead of scrambling or giving up, there are several key opportunities to drive profound revenue growth in Q4 and beyond. While their benefits are multiplicative, even tackling one today can help drive growth tomorrow. Let’s dive in.
AI: The Absolute Imperative
Systems crack under pressure, and digital experiences are no exception. However, holiday readiness requires more than server stability amid massive, spiky traffic. Retailers must seriously consider whether they're equipped to leverage every moment. To that end, those thriving today are neither tiptoeing into automation nor still running pilot tests on artificial intelligence. For them, AI stands for absolute imperative.
Those absolute imperatives are unlocking greater yield, empowering advertisers at scale, elevating the shopper experience, optimizing for long-term value, and treating retail media as core to the overarching business.
Unlocking Yield
Unlocking greater yield begins by better seizing dynamically moving advertiser opportunities. Retailers must assess whether their tech is equipped for the task. Archaic systems reliant on managed-service control over partner waterfalls or simplistic CPM and CPC bidding simply cannot fully leverage the full potential of the holiday season.
Today, AI-driven retail platforms are reaching key revenue-to-GMV thresholds three times faster than the e-commerce powerhouses of the past. Moreover, these retailers are using real-time bidding engines to handle spiky holiday traffic and optimize every ad slot for performance, maximizing yield when it matters most.
Granted, moving away from established systems can be unnerving for some. Unfortunately, while they cling to rowboats, their competitors are jetting away on the winds of AI-powered efficiencies, rich auctions, and diverse demand.
The Advertiser Experience
This brings us to the second absolute imperative: ensuring a seamless and scalable advertiser experience.
Every holiday season, new brands and trends will surprise us. Yet it's grossly self-limiting to manually chase and onboard advertisers. By the time new campaigns are set up, shoppers may have found what they’re craving elsewhere.
Meanwhile, efficient RMNs handle advertiser onboarding through automation and self-service tools, empowering brands at scale while maintaining safety and control. They also break down silos, offering a holistic view of the interplay between paid and organic placements to help advertisers optimize their total impact.
At long last, the ads and internal organic teams aren’t at odds or disconnected. They're working together to create a more cohesive and effective shopper experience.
Both process and total page optimization are here, and everyone in the ecosystem is benefitting. Modern platforms can activate 10,000 advertisers in a single day. A savvy blend of organic and paid content delivers more contextually relevant pages to shoppers, and both satisfaction and conversions are on the rise as a result.
The Shopper Experience
The preceding imperatives are precursors to the main act: the shopper experience. It’s the era of the consumer, and the best RMNs are shifting focus from simply serving the right ads to creating a better shopper journey.
AI is now delivering hyper-relevant content that feels helpful to shoppers, building long-term value and loyalty that outlasts any holiday sale. Where innovation for in-session engagement was once chatbots, now the horizon is agentic AI serving as a personal shopper to refine and drive the shopper’s discovery process.
Optimizing for the Long Term
With a scalable tech stack and a satisfying shopping experience in place, the strongest retailers have their sights further down the road on our next absolute imperative: measuring and optimizing for long-term value.
Yes, immediate return on ad spend is crucial, particularly for any marketer straining to meet stakeholder expectations. However, sophisticated brands are adjusting their focus. Now, holiday campaigns are increasingly viewed as an acquisition or re-engagement event in the journey to build a loyal customer base.
Remembering the Mission
While notable additive lift is possible in the near term by addressing any of the preceding imperatives, the retailers enjoying greater growth at scale are those that are treating media as a central part of their business.
For them, retail media isn’t just about optimizing ad revenue or conversions. It’s not just about seeking total page optimization to improve shopper satisfaction or average cart values. It’s about leveraging the right signals to fundamentally enhance the shopper experience, build brand loyalty, increase lifetime value, and drive real, meaningful growth for the business as a whole.
The real readiness question is this: Is your RMN an efficient and scalable launchpad for the growth of the entire organization, or is it an awkwardly inefficient afterthought?
Pat Copeland is general manager of Moloco Commerce Media (MCM), the only AI-native ads engine that enables retailers and marketplaces to activate high-performing retail media networks.
Related story: Breaking Free: How Retailers Are Reclaiming Control Over Their Advertising Businesses
Pat Copeland, General Manager, Moloco Commerce Media
Pat Copeland is the General Manager of Moloco Commerce Media, where he leads strategic initiatives, product innovation, and customer engagement. By leveraging machine learning, analytics, and scalable cloud infrastructure, his team supports retail partners—ranging from major e-commerce platforms to emerging digital marketplaces—in optimizing their advertising strategies, enhancing customer experiences, and maximizing their monetization potential.
Pat brings 30 years of leadership across top tech companies. At Zendesk, he led global teams building AI-powered customer support tools. At Amazon, he launched and scaled Sponsored Brands into a multi-billion-dollar ad platform. He spent a decade at Google, where he played key roles in Advertising, Research, and Cloud Systems, helping earn the company IEEE’s 2013 Company of the Year and oversaw award-winning products like Google WiFi. Pat began his career at Microsoft, working on operating systems, web services, SQL Server, and Bing.
Pat holds a Master of Science in Computer Science with a specialization in Machine Learning from the University of Southern California and a Bachelor of Science in Computer Science from the University of Arizona.





