How to use AI-powered Google Ads to boost conversions and sales?
In today's ever-changing digital marketing environment, Google Ads is facing a profound change driven by AI technology. According to the latest data, 15% of Google searches every day are completely new keywords, which poses a severe challenge to traditional search advertising strategies. At the same time, the "Digital Shelf" project of Rakuten Group and Google Advertising has revealed the amazing potential of retail media - through AI-optimized advertising product quantity and budget allocation strategies, it has successfully achieved sustained sales growth. These developments mark that we are entering a new era, and marketers must rethink how to use Google Ads as a powerful tool. This article will explore in depth how AI reshapes the search advertising ecosystem and share practical experience from brands such as Sephora and Hankook Tire to help you maintain a competitive advantage in this new era of AI-driven digital marketing.
I. Overview of Google Ads AI-driven search advertising trends
1.1 Changes in search behavior and the inevitability of AI application
Today's consumer search behavior is undergoing unprecedented changes. The large number of new search terms that emerge every day makes it increasingly difficult for traditional keyword matching strategies to cope with. This phenomenon reflects a fundamental shift in the way consumers acquire information - from a linear, predictable search model to a more fragmented, contextualized exploration process. In such an environment, the application of AI technology is no longer an option, but a necessity. Google Ads AI system can analyze billions of search interactions in real time and identify hidden patterns and intentions, which far exceeds the manual analysis capabilities of human marketers. More importantly, these AI models can continuously learn and adapt, and can make accurate judgments based on context and user history even when faced with new search terms that have never been seen before. This dynamic adaptability is the key to solving the complexity of contemporary search behavior.
1.2 Limitations of traditional search advertising strategies and AI solutions
Traditional search advertising strategies are facing three core limitations: insufficient keyword coverage, inefficient bidding, and overly complex account structures. At the keyword level, manually maintained keyword lists are difficult to keep up with the diversification of search queries; in terms of bidding strategies, static bidding models cannot adapt to the real-time changing market competition environment; and overly segmented advertising groups lead to data fragmentation, hindering overall optimization. Google Ads AI solution provides a systematic response to these pain points: the smart bidding system uses machine learning to adjust each bid in real time; the extended matching technology breaks through the limitations of precise keywords and understands the true intent behind the search; the simplified account structure allows AI to obtain a more comprehensive data view and make more optimized decisions. The combination of these technologies marks the paradigm shift from "manual control" to "AI-driven" in search advertising.
II. Core technologies and strategies of AI-driven search advertising
2.1 The operating principle and practical advantages of the smart bidding system
Google Ads smart bidding system represents a quantum leap in advertising bidding technology. Based on deep learning algorithms, this system can simultaneously analyze dozens of signals - including device type, geographic location, time, audience characteristics, and even the current market competition intensity - to calculate the optimal bid for each search query. Compared with traditional manual bidding, the biggest advantage of smart bidding is its ability to "take the whole picture into account": it not only considers the immediate value of a single click, but also evaluates the user's entire conversion path, so as to make decisions that are more in line with business goals. In practice, brands that adopt smart bidding can usually obtain more high-quality conversions while maintaining the same advertising expenditure. The case of Hankook Tire is particularly striking - after switching to a smart bidding strategy based on GA4 session data, its CPA (cost per acquisition) has not increased but decreased, and some markets have even achieved a 300% KPI growth, proving the amazing potential of AI bidding in improving efficiency.
2.2 The evolution of keyword matching technology: from precise matching to semantic understanding
Keyword matching technology has undergone a revolutionary evolution in recent years. The traditional dichotomy between precise matching and broad matching has been replaced by more delicate semantic understanding. Modern Google Ads systems are able to parse the deep intent of search queries rather than just matching surface words. For example, for users searching for "men's running shoes", the system may automatically display ads for "men's sports shoes" because it understands the similarity between the two in user intent. This evolution has greatly reduced the burden of keyword management for marketers while improving the relevance of advertising. In practical applications, brands can more confidently adopt broad matching strategies to expand coverage without sacrificing precision. Hankook Tire has effectively acquired new customers in overseas markets with low brand awareness through this method - focusing budget on non-brand keywords and using broad matching to capture various related search intents, thereby building brand awareness and driving traffic.
III. Practical effectiveness verification and key insights
3.1 Empirical evidence on the golden ratio of product quantity and advertising budget
The collaborative research between Rakuten and Google Advertising provides empirical insights on the allocation of product quantity and advertising budget, and these findings challenge the traditional cognition of many marketers. The data clearly shows that there is a direct positive correlation between increasing the number of advertised products and sales growth, and this law is not affected by the unit price of the product. More specifically, for every 100 additional advertised products, sales will show a significant increase. The reason behind this phenomenon is the "associated purchase" behavior of consumers in the digital environment - users attracted by advertisements often buy not only the product they clicked on initially, but also related items. Therefore, excessive focus on "star products" may limit overall sales potential. In terms of budget allocation, the study found that when the daily advertising budget reaches 2 times the unit price of the product, it can create the best input-output ratio. Although this "2x rule" is not absolute, it provides a scientific reference point for budget setting, helping brands find a balance between expanding coverage and controlling costs.
3.2 Rakuten Ichiba Case: Cross-platform Data Application of RPP Expansion Function
Sephora's transformation case in the UK market provides a classic example of search advertising strategy in the AI era. Faced with an overly segmented advertising structure (divided by multiple dimensions such as product lines and promotion types), Sephora boldly simplified the account structure and integrated the number of campaigns from complex fragments to a few large groups with clear themes. This simplification brings three benefits: first, it reduces the limitations of AI optimization, allowing the system to find opportunities in a wider range of queries; second, it reduces the complexity of internal management, allowing the team to focus on strategy rather than trivial adjustments; most importantly, it creates amazing business results - a 42% jump in conversion rates, accompanied by a 6% increase in average order value and a 13% increase in ROAS. This case proves that in an AI-driven advertising environment, the role of marketers is changing from "micro-managers" to "strategic guides", and the courage to let AI play often yields unexpected returns.
3.3 Hankook Tire's 300% KPI Growth in Global Integration Strategy
Hankook Tire's global search advertising integration plan demonstrates how AI technology can help brands break through geographical restrictions and achieve scaled growth. Faced with decentralized operations in 28 countries, Hankook Tire adopted a three-pronged strategy: first, upgrading the bidding strategy from a simple "click maximization" to "conversion maximization" based on GA4 session data, greatly improving traffic quality; second, focusing on non-brand keywords in overseas markets and using broad matching to expand brand awareness; finally, optimizing the global advertising structure and introducing performance maximization campaigns as a supplement. These changes have brought impressive results: not only has the overall traffic increased significantly, but some markets have even achieved 300% KPI overfulfillment. It is particularly noteworthy that search advertising contributed more than 50% of the total traffic, becoming the main channel driving business growth. This case proves that global brands can fully achieve the harmonious unity of centralized management and localized effects through the strategic application of AI technology.
IV. Topkee's Google Ads solution
Topkee provides one-stop online advertising professional services based on Google Ads, focusing on helping companies improve the efficiency of potential customer development and sales conversion rate. Our service framework covers the complete advertising life cycle management from pre-evaluation to post-optimization, and can provide corresponding customized solutions regardless of the size of the customer. In the actual service process, we will first conduct a comprehensive website evaluation and analysis, use the latest scoring tools to conduct technical inspections on the customer's website, and produce a detailed report including SEO problem diagnosis and improvement suggestions. This stage of work not only includes basic page structure optimization, but also focuses on in-depth mining of content value to ensure that website information can effectively meet the search intent of the target audience, thereby improving natural search rankings and advertising conversion rates.
In terms of technical integration, Topkee has developed the TTO system as a core management tool. The platform has a multi-account centralized management function, which can complete administrative operations such as account opening application, budget allocation and authority setting in one stop. Its advanced data tracking capabilities support multi-tag ID association, and with the automatic conversion event setting function, it can seamlessly synchronize key behavioral data to the advertising background to achieve a data closed loop for the entire process. Compared with traditional UTM parameters, our exclusive TM tracking technology provides a more flexible URL tagging solution. It can customize tracking rules according to multi-dimensional variables such as advertising source, media type, and event name. Through the accurate data feedback of TMID tags, it helps customers grasp the real conversion results of various channels.
Conclusion
AI technology is completely reshaping the operating logic of Google Ads. From smart bidding, keyword matching to retail media integration, each level contains new opportunities to improve advertising effectiveness. Lotte Group's digital shelf plan, Sephora's account simplification strategy, and Hankook Tire's global integration cases all vividly demonstrate the transformative power of AI-driven marketing. In this rapidly evolving field, success will belong to those brands that can embrace the potential of AI, simplify operational structures, and establish cross-platform data collaboration. However, technology is only a tool, and the ultimate competitive advantage still comes from a deep understanding of consumer needs and innovative satisfaction. We encourage companies to develop an AI advertising transformation roadmap that meets their business goals with the assistance of professional consultants, and turn these insights into actual business growth. In this new era of AI empowerment, opportunities belong to well-prepared pioneers.