If you integrate offline data with Google Ads, you can boost conversions 3.2x
At the beginning of 2025, the director of product management of Google Ads announced a series of functional upgrades for maximizing advertising campaigns, marking the entry of omni-channel marketing into a new era driven by AI. In a market environment where digital transformation is accelerating, Spanish insurance giant Santalucía successfully increased online channel sales by 3.2 times through offline data activation strategies; while German retail brand Baur used the GA4 forecasting model to create a 56% sales growth during the economic downturn. These success stories reveal a key trend has evolved from a simple advertising platform to an intelligent marketing hub that integrates online and offline data. This article will deeply analyze how the latest technological innovations of Google Ads enable cross-industry omni-channel marketing, and through empirical cases in the insurance and retail industries, deconstruct the implementation path and key success factors of data-driven strategies.
I. The rise of omni-channel marketing and the strategic positioning of Google Ads
1.1 Market demand for omni-channel integration under digital transformation
Today's consumer behavior has completely changed, and a single-channel marketing strategy is difficult to meet user expectations. The transformation of the Spanish insurance market is a testament to this - consumers demand that insurance companies respond to their needs in real time, forcing the century-old company Santalucía to integrate AI and data analysis technologies. This market demand has given rise to the rise of omni-channel marketing, and Google Ads has become a core tool for companies to achieve digital transformation with its cross-channel integration capabilities. The launch of the Maximize Performance campaign is Google's direct response to market demand. It allows advertisers to use multiple advertising formats such as search, display, and shopping in a single advertising campaign, and automatically allocate budgets to the best performing channels through AI. This integration not only improves marketing efficiency, but more importantly, breaks down data silos and lays the foundation for a true omni-channel experience.
1.2 The core value of Google Ads as a data hub
The core value of Google Ads has shifted from traffic acquisition to data integration. Taking Santalucía as an example, the key to its success is to feed offline interaction data from the call center back to the system in real time. This data closed loop enables AI to dynamically adjust bidding strategies and prioritize high-value potential customers. Google Ads plays a role in more than just advertising, but also a data hub that connects online and offline behaviors. The campaign-level negative keyword feature added in 2025 further strengthens this hub value, allowing brands to more accurately control the advertising display context and avoid invalid exposure. This data integration capability makes a natural extension of the enterprise customer data platform (CDP), providing a solid data foundation for omni-channel marketing.
II. Insurance industry evidence: Santalucía's offline data activation strategy
2.1 Construction of potential customer value grading system
Santalucía's transformation began with the establishment of a potential customer value grading system, which subverted the traditional marketing thinking of winning by quantity. By analyzing historical data, they found that there were significant differences in conversion rates for different interaction methods (form submission, telephone consultation, etc.), and the lifetime value of different insurance products was also very different. For example, potential customers who entered through a specific landing page CTA were 2.3 times more likely to purchase high-end medical insurance than those from other channels. Based on these insights, Santalucía developed a multi-dimensional scoring model that not only considers the possibility of conversion, but also incorporates long-term value indicators such as product profit margin and customer retention rate. This system enables bidding strategies to truly align with business goals, rather than just optimizing surface conversion indicators.
2.2 Real-time feedback mechanism for CRM and call center data
The core of Santalucía's success lies in the construction of a real-time feedback loop for CRM and call center data. Through the digital CRM API, the entire journey of each potential customer from the first contact to the final transaction is tracked and sent back to the Google Ads system. This includes key details such as whether the customer received a quote, the amount of the quote, and the type of product purchased in the end. This real-time data stream enables the AI model to dynamically adjust the bidding strategy-when the system detects that the actual conversion rate of a certain type of potential customer is higher than expected, it will immediately increase the bid for users with similar characteristics. This mechanism is particularly suitable for industries with long conversion cycles such as insurance, because it can continuously optimize marketing efficiency in a long sales funnel.
III. Retail case: Baur's predictive audience application
3.1 GA4 prediction model and first-party data integration
Faced with the challenges of the economic downturn, German mail-order retailer Baur pioneered the integration of GA4 prediction model with existing first-party data. Although their original BI system can classify customers based on historical purchase data, it cannot capture website behavior signals in real time. GA4's "seven-day purchase probability" prediction model perfectly fills this gap. It can analyze users' real-time browsing depth, product page dwell time and other micro-behaviors, and discover new high-intention signals outside the traditional RFM model. It is worth noting that Baur did not completely replace the original system, but let GA4 and the BI system complement each other - GA4 is responsible for capturing short-term purchase intentions, while the BI system continues to track long-term customer value. This dual-track data strategy enables them to take into account both immediate conversion and long-term customer relationships during key promotional periods such as Black Friday.
3.2 Practical results of seven-day purchase intention prediction
Baur's test results confirmed the amazing accuracy of GA4's prediction model. During the six-week test, 70% of the "likely to purchase within seven days" audiences identified by the system were new potential customers that the original BI system failed to cover. The conversion rate of this audience is 3.2 times higher than that of the general audience, and the average order value is also higher. In-depth analysis found that these "hidden high-intent users" often show specific behavior patterns, such as repeatedly viewing the same product category and browsing the delivery policy page. GA4's AI model can automatically identify these subtle signals, which are easily overlooked by traditional rule-based systems. This predictive ability enables Baur to create a 56% sales growth with the same budget and maintain profitability under inflationary pressure.
IV. Topkee's Google Ads solution
Topkee provides a one-stop online advertising service based on Google Ads, aiming to help companies effectively increase the number of potential customers and sales performance. Regardless of the size of the customer, Topkee can provide customized solutions based on the needs of different companies, and ensure that advertising campaigns achieve the best results through systematic service processes and professional tools.
Topkee's service begins with comprehensive website evaluation and analysis, using the latest scoring tools to deeply detect customer websites, produce detailed SEO problem reports and provide specific improvement suggestions. This stage not only includes technical SEO optimization, but also structural adjustments to page content to ensure that the content meets search engine specifications and has market value, thereby improving search rankings and conversion rates. In terms of technical integration, the TTO tool developed by Topkee can centrally manage multiple advertising accounts and realize the automated process of account application, budget allocation and permission setting. The system supports multi-tag ID concatenation. Through the precise data tracking mechanism, event tracking can be set according to the conversion goal with one click, and the data can be synchronized to the advertising background, greatly improving the efficiency of delivery.
In response to the needs of advertising tracking, Topkee adopts TM setting technology, which is more flexible than traditional UTM parameters. Customers can customize tracking rules based on dimensions such as advertising source, media type, and event name. The system automatically generates an exclusive link with TMID, allowing the marketing team to monitor the effectiveness of each channel in real time and optimize the allocation of advertising resources. In the strategic planning stage, Topkee will collect data from multiple dimensions and produce theme proposals based on the characteristics of the customer's industry and market dynamics. After feasibility evaluation, these proposals will be transformed into high-quality marketing activities to help customers save pre-preparation time. Keyword research combines competitor analysis and AI tools to screen out core keywords with high conversion potential, and integrates smart bidding strategies and broad matching technology to expand advertising coverage while maintaining delivery accuracy.
Conclusion:
From Santalucía's offline data activation to Baur's predictive audience application, the practices of these leading companies have proved that Google Ads has evolved into an AI-driven omni-channel marketing hub. The key to success is to establish a cross-departmental data collaboration culture, invest in seamless integration of technology platforms, and develop a diversified evaluation indicator system. As the function of maximizing advertising campaigns continues to strengthen, companies can now reach high-value audiences with unprecedented accuracy while maintaining the necessary control over marketing strategies. If your brand is planning an omni-channel transformation, now is the best time to embrace technological innovation. To learn more about how to apply these strategies to your business, it is recommended to consult a professional certified partner to tailor data-driven marketing solutions.
