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The European retail media market exceeded €10 billion in 2025 and is projected to reach €25 billion in 2026. In this era of rapidly evolving consumer behavior, the case of Pandora Jewelry stands out. By leveraging a strategy that combines Google Ads with first-party data, the company achieved a remarkable 3.2-fold year-over-year increase in offline revenue and a 77% increase in total revenue in 2023. This not only demonstrates the power of data-driven marketing but also highlights the critical transformation facing the retail industry: a shift from traditional channel-based marketing to an omnichannel, AI-powered, intelligent marketing model. This article will delve into how leading companies are leveraging the Google Ads platform to create value at every touchpoint in the consumer journey.
I. Trends and Challenges in Digital Transformation in the Retail Industry
1.1 The Impact of Changing Consumer Behavior on the Retail Industry
Contemporary consumers have developed a "search-to-buy" behavior. According to research by Google and the European Retail Federation, younger generations use an average of 4.7 channels to make a single purchase. Pandora's operational data shows that 75% of holiday shoppers continue to search for deals throughout the holiday shopping season. This fragmented consumer behavior is forcing retailers to redesign their marketing funnels. For example, home furnishings brand Home24, with its 500,000-item inventory, is increasingly relying on precise product data to make decisions. This led them to implement generative AI to optimize product titles and attributes in , ultimately increasing click-through rates by 29%. This shift requires marketing teams to have access to real-time data and provide relevant information at the moment of consumer decision-making.
1.2 Omnichannel Shopping Experience Becomes the Market Standard
Annie McAndrews, Pandora's North American Media Director, emphasized, "Companies that ignore the omnichannel experience often mis-focus their budgets on e-commerce." Using Google Ads' in-store conversion tracking technology, the brand discovered that consumers might first watch a product video on YouTube, then search for local inventory on their mobile phone, and finally complete their purchase in-store. This multi-touch journey led them to develop a dynamic budget allocation system that adjusts ad spending bi-weekly based on incremental online and offline sales. European retail media pioneers such as MediaMarktSaturn have demonstrated that omnichannel advertising strategies that integrate offline data can achieve ROAS 2.5 times higher than online-only strategies. This demonstrates that Google Ads' value has evolved from simply capturing clicks to becoming a tool for experience design throughout the entire consumer journey.
II. Core Strategies for Integrating First-Party Data with Google Ads
2.1 Establishing a Year-Round Testing Framework and Applying It During Key Consumer Periods
Raul Duque Ruiz, Vice President of Global Marketing at Pandora, revealed the secret to their success: "We conduct innovative testing from January to October and focus on execution from November to December." This "test-learn-scale" framework enabled them to accumulate sufficient data insights before the Christmas shopping season. For example, using Google Ads' Experiments feature, they discovered that combining brand storytelling videos with local inventory ads increased store visits by 23%. This approach requires the marketing team to establish a rigorous testing culture, boldly experimenting with new ad formats (such as video action campaigns), audience targeting methods, and bidding strategies during off-season, and then scaling successful models during key consumer periods.
2.2 Omnichannel Budget Allocation and Real-Time Performance Optimization
Pandora's "open budget" mechanism is a core strategy for responding to market fluctuations. They set dynamic ROAS thresholds, and when Google Ads' intelligent bidding system detects opportunities exceeding the threshold, it automatically increases the budget. This approach was particularly effective during Black Friday. When the system detected a sudden increase in "click-and-collect" conversion rates in a certain region, it immediately increased the Shopping Ads budget for that area by 40%. Home24 has developed a more granular budget allocation logic, setting differentiated ROAS targets in Google Ads based on profit margin differences between product categories (e.g., sofas vs. lamps). This data-driven budget fluidity requires retailers to integrate data from ERP, CRM, and advertising platforms to establish a unified performance measurement framework.
III. Key Lessons from Successful Case Studies
3.1 Pandora's Festive Sales Growth
Pandora's case study provides a complete blueprint: Through a year-round testing framework, they confirmed by October that the combination of "video mobile ads + local inventory" was the most effective. Omnichannel budget allocation enabled them to immediately shift resources to high-return channels. And offline conversion tracking revealed the true impact of advertising on brick-and-mortar performance. The combined effect of these strategies was astonishing—not only did Google Ads revenue grow by 77%, but it also drove a 34% increase in overall holiday sales. The key was their approach to treating first-party data as a strategic asset, not just a marketing tool. Raul Duque Ruiz, Vice President of Global Marketing, emphasized, "Accumulating sufficient data insights before the critical consumer period is the non-technical key to holiday success."
3.2 Home24's AI Data Optimization Results
Home24's FeedGen project demonstrates how AI can solve retail pain points: Faced with the impossible task of manually optimizing 500,000 products, they partnered with Google to develop a LLM-driven tool to automatically generate high-quality product titles and attributes. A French market test showed that AI-optimized product data increased shopping ad clicks by 29% while reducing operating costs by 62% (due to reduced manual review). Even more noteworthy was the subsequent impact: structured product data improved Google's product knowledge graph, leading to a 17% increase in organic search traffic. Chief Marketing Officer Dr. Sascha Vitzthum noted, "Generative AI not only improves advertising effectiveness but also reshapes the entire product data management process." This case study demonstrates that the future of retail advertising lies in the integrated application of "AI + first-party data."
3.3 Benchmarking Practices in European Retail Media
These European cases collectively demonstrate a mature model for retail media. These companies go beyond simply selling ad space and transform first-party data into actionable business insights. Google's German research shows that leading retailers view media as an independent profit center, contributing an average of 3-5% to total revenue. More crucial is their strategic thinking—for example, Rewe supermarkets integrate advertising inventory with their membership program, enabling precise measurement of advertising effectiveness down to the individual level. These approaches require initial investment but establish a competitive advantage that is difficult to replicate. As Claudia Denzel, Google's Retail Director for Germany, puts it, "Retail media isn't a short-term trend; it's a paradigm shift that redefines how retailers and brands work together."
IV. Topkee's Google Ads Solutions
Topkee provides one-stop online advertising services based on Google Ads, using systematic solutions to help businesses effectively increase lead generation and sales. Our service framework encompasses the entire advertising lifecycle, from initial evaluation to post-optimization, offering customized solutions for clients of all sizes.
In the initial phase of our service, we conduct a comprehensive diagnostic using professional website scoring tools, providing a detailed analysis of website structure, content quality, and SEO techniques. This assessment not only pinpoints the key factors currently impacting search engine rankings but also provides specific optimization recommendations to ensure that website content meets search engine standards and provides tangible value to target audiences. Through systematic SEO enhancements, brand visibility in search results pages can be significantly improved, thereby driving increased conversion rates. Our TTO system is the core advertising management platform, offering multi-account integrated management capabilities. Clients can complete ad account creation, budget allocation, and permission settings through a single interface, significantly improving operational efficiency. The system supports multiple tracking tag configurations, accurately capturing user behavior data across various channels. Notably, its intelligent conversion settings automatically create conversion events based on different marketing objectives and instantly synchronize them to the advertising backend, automating data processing throughout the entire process.
In terms of tracking technology, our TM system offers greater flexibility than traditional UTM parameters. Clients can customize tracking rules based on multiple dimensions, such as marketing themes, media sources, and ad levels. The system automatically generates tracking links with unique TMIDs. This technology allows advertisers to clearly understand the actual performance of each channel, providing data support for subsequent adjustments to advertising strategies. For advertising planning, our professional team conducts in-depth analysis of the client's business characteristics, examining market trends, competitive landscape, and target audience from multiple perspectives to produce creative and feasible thematic proposals. Through a rigorous requirements verification process, we ensure that each proposal precisely aligns with the client's business goals, while also saving clients time and costs during the marketing planning phase.
Conclusion
From Pandora's successful holiday season to Home24's AI transformation, these cases demonstrate that in the age of privacy, the combination of first-party data and Google Ads is becoming the most powerful engine of retail growth. However, technology is only a tool; true transformation requires a shift in organizational mindset—viewing data as an asset, testing as a culture, and omnichannel as standard. We have entered the era of "intelligent retail media," and those companies that can integrate AI insights with human creativity will win consumer mindshare and wallet share. If you need professional assistance planning your Google Ads strategy, please contact our team of retail marketing consultants to collaborate on your data-driven growth plan.
