Are you leveraging AI to maximize your Google Ads performance?
In today's digital marketing field, marketers are facing unprecedented challenges: from massive data analysis to creative content marketing output, to cross-platform advertising optimization, the workload and complexity are constantly rising. According to the latest market observations in May 2025, consumer behavior has become more fragmented, brand loyalty has decreased, and cross-channel shopping has become the norm. In such an environment, how to accurately reach the target audience and improve advertising effectiveness has become an urgent problem for companies to solve. The AI agent function recently launched by Google Ads is providing marketers with a breakthrough solution. By integrating generative AI (such as Gemini) and automation tools, advertisers can significantly reduce manual operation time while improving advertising accuracy and creative diversity. This article will explore in depth how AI reshapes the Google Ads ecosystem, and share successful cases such as retailers Duca di Morrone and sports brand Scicon Sports, revealing the practical application and future development direction of AI-driven advertising strategies.
I. Trends in the integration of Google Ads and AI tools
1.1 Challenges and AI solutions currently faced by marketers
Modern marketing teams need to handle multiple tasks such as data analysis, audience insights, creative thinking and cross-channel optimization at the same time. Traditional manual operations can no longer cope with the ever-changing market demands. Google Ads' AI agent function was born for this purpose. Its core value lies in automating repetitive tasks and allowing marketers to focus on strategic decision-making. For example, agent tools can automatically analyze real-time performance data analysis and landing page content marketing, and adjust keyword bids and ad copy in real time to solve the problem of traditional optimization lag.
More importantly, these AI tools have the ability to continuously learn. Taking Google Analytics' agent interface as an example, it can actively identify abnormal fluctuations in traffic and point out possible reasons through visual reports, such as competitor activities or technical errors during specific periods. This early warning mechanism allows marketing teams to respond quickly and avoid ineffective advertising expenditures. According to actual measurements, companies that use AI agent functions have increased troubleshooting efficiency by 40% and shortened campaign launch time by two-thirds.
1.2 Launch and application scenarios of Google Ads proxy function
Google Ads' AI proxy function has evolved from simple keyword suggestions to a full-scale marketing consultant role. The latest "Marketing Consultant" can be directly integrated into the Chrome browser sidebar. When marketers browse competitor websites or industry reports, AI will provide real-time strategic suggestions. For example, when it detects that a product page lacks price promotion information, it automatically recommends adding a limited-time discount slogan to the search ad and adjusting the material combination of the Performance Max campaign at the same time.
In practical application, the proxy function is particularly suitable for three scenarios: when there is a lack of historical Google Ads in the early stage of new product launch, AI can refer to industry benchmarks to quickly establish an advertising framework; seasonal activities such as Black Friday can automatically allocate budgets to high-conversion channels; during the stage of cross-border market expansion, it can dynamically generate multilingual copy based on local search trends. The American outdoor brand Patagonia used this function to increase the efficiency of advertising localization by 50% when entering the Asian market, while maintaining the consistency of global brand tone.
II. Application of AI tools in creative generation and optimization of advertising
2.1 Using AI to generate high-quality search advertising content marketing
Creative output is the key to advertising effectiveness, but it is also a labor-intensive link. Google Ads' conversational AI can now automatically generate advertising copy that meets business goals based on brand guidelines and product databases. For example, if you enter "high-end coffee machine Mother's Day gift", AI will generate multiple sets of titles and descriptions that emphasize selling points such as "30-second rapid extraction" and "professional milk foam system", and automatically filter out words that do not match the brand tone (such as "cheap" and "discount").
In advanced applications, AI can also perform "creative layering testing" - automatically combining different value propositions of the same product (such as "time saving" vs. "professional sense") into dozens of advertising variants, and dynamically eliminating combinations with poor results based on initial performance. French cosmetics brand L'Oréal used this technology to test in the European market and found that the "ingredient safety" claim had a 22% higher click-through rate than the "celebrity endorsement" claim, and then adjusted the advertising strategy for its entire product line. This data analysis-driven creative optimization allows human teams to focus on core concept generation rather than mechanical modification.
2.2 Application of multimodal AI (such as Gemini) in strategic planning and creative generation
The new generation of multimodal AI such as Gemini is bringing advertising creativity into a new dimension. Its breakthrough lies in the ability to simultaneously process text, image and even video data analysis, playing the role of "digital creative director". In the strategy stage, Gemini can analyze hot topics in the community and the tone of competitor advertisements, and suggest differentiated positioning directions; in the generation stage, by inputting abstract concepts such as "adventurous outdoor equipment", AI can produce visual proposals including mountain silhouettes and corresponding slogans (such as "Conquer unknown altitudes"), greatly shortening the distance from strategy to execution.
In a practical case, the Media.Monks team used Gemini to analyze discussions among car owners in the community for a certain car brand and found that the demand for "family safety" was not fully met. AI then generated a series of advertising concepts, including a dynamic display video script for the rear seat child monitoring system, and emotional appeal copywriting such as "Dad's invisible protection". This ability to integrate Google Ads insights and creative output allows advertising strategies to no longer rely on intuitive guesswork, but to be based on real-time market signals.
2.3 Dynamic creative generation and cross-platform advertising optimization (taking Performance Max as an example)
The Performance Max (PMax) campaign represents the pinnacle of AI-driven cross-channel optimization. Its core lies in the "dynamic creative optimization" (DCO) technology - the system automatically combines the most relevant creative elements based on the user's real-time behavior (such as browsing hiking shoes but not clicking on them). For example, street-style model images and "limited color matching" slogans are displayed to young people, while functional close-ups and "arch support technology" copy are displayed to middle-aged users, and all adjustments are completed in milliseconds.
Empirical evidence from sports brand Scicon Sports shows that PMax's dynamic creative combination has increased its advertising exposure in the French market by 300%, while reducing the cost per conversion by 35%. The key is that the brand provides a wealth of basic materials (such as multi-angle product videos, usage scenario photos, and technical specification charts), allowing AI to freely mix and match according to the preferences of various countries' markets. For example, German users prefer technical content marketing, so AI automatically increases the exposure frequency of specification charts; the British market responds better to lifestyle images, and the system adjusts the material weight accordingly. This "global strategy, local execution" model is the core advantage of AI advertising.
III. Advanced AI marketing cases and effectiveness analysis
3.1 Evidence of ROI improvement for retailer Duca di Morrone
Italian men's shoe brand Duca di Morrone faces a typical peak season challenge: how to maximize sales under a limited budget. It uses the Performance Max campaign, and after setting the ROI target, AI fully decides on budget allocation and material combination. The key is to provide sufficient creative fuel - including 360-degree product videos, close-up photos of materials, and seasonal copy with the theme of "returning to the office".
The results are amazing: compared with the same period of the previous year, a 30% increase in advertising spending brought a 192% sales growth, and ROI doubled directly. AI's breakthrough was that it discovered that the conversion rate of the keyword "maintenance-free leather" was unusually high in the German market, so it automatically prioritized the relevant materials to the business community in the region; at the same time, it detected that the search volume for "casual shoes" increased on weekends, and immediately adjusted the ad title to emphasize the weekend wear scene. This kind of micro-optimization is difficult for human teams to follow up in real time.
3.2 Dynamic Creative Strategy for Scicon Sports' Cross-border Market Expansion
Sports eyewear brand Scicon Sports wants to expand into the Nordic market, but faces the dilemma of limited resources. Its solution is to upload materials for the same product in different usage scenarios (such as road racing, mountain off-road, and urban commuting) through the PMax advertising series, allowing AI to automatically adjust the exposure ratio according to the preferences of each country.
Data analysis shows that Danish consumers respond best to the demands of "minimalist design" and "lightweight", so AI increases the weight of related materials to 78%; while the German market pays more attention to technical specifications such as "UV400 protection", and the system strengthens such information accordingly. As a result, the Danish market revenue increased by 167% year-on-year, and AI automatically discovered that there was an unexpected demand for bicycle bags in Sweden, opening up new product line opportunities. This ability to "discover unknown markets with data analysis" is the strategic value of AI.
3.3 Delivery Hero's Customer Lifetime Value Prediction Model
Delivery Hero, a delivery platform, is facing the dilemma of rising customer acquisition costs. It cooperated with Google to develop a three-stage AI model: first, GA4 was used to analyze the characteristics of high-value users (such as the repurchase rate of those with a first order amount of more than US$30 reached 42%), then AI was trained to predict the potential lifetime value (LTV) of new customers, and finally this data analysis was integrated into the smart bidding system of Google Ads.
Actual measurements in the Latin American market show that compared with the traditional CPA (cost per acquisition) model, the AI-driven LTV bidding strategy brings double customer value and increases the proportion of high-value users by 13%. The key is that AI can identify subtle behavioral patterns - for example, the LTV of users who pay with Apple Pay is 25% higher than the average, and the system automatically increases the bid ceiling for this group. This "quality over quantity" customer acquisition mentality redefines the measurement standard for marketing efficiency.
IV. Topkee's Google Ads solution
Topkee provides one-stop online advertising professional services based on Google Ads, helping enterprises to effectively improve the development of potential customers and sales conversion results through systematic solutions. Our service framework covers the complete advertising life cycle management from pre-evaluation to post-optimization, and is suitable for corporate customers of all sizes. In terms of practical operations, we will first conduct a comprehensive website evaluation and data analysis, use the latest scoring tools to conduct technical diagnosis of customer websites, and produce a detailed report containing a list of SEO problems and improvement suggestions. This stage also includes the optimization of website content marketing structure to ensure that all pages meet the search engine optimization specifications and provide information content marketing with substantive value to the target audience, fundamentally improving the conversion efficiency of natural search rankings and advertising landing pages.
In terms of technical tool application, the TTO system developed by Topkee is a core management platform with multi-account centralized control functions, which can realize advanced management needs such as media budget allocation and advertising account authorization. The system supports multi-tag ID association settings, can establish a refined tracking mechanism, and synchronize conversion events to the advertising background through automated processes, greatly improving processing efficiency. In response to the demand for advertising traffic tracking, we use the self-developed TM parameter system, which has higher flexibility than traditional UTM. It can customize tracking rules according to dimensions such as advertising source, media type, and event theme, and generate exclusive tracking links with TMID identification codes, providing an accurate basis for subsequent effect analysis.
In the strategic planning stage, our professional team will collect market intelligence from multiple dimensions and produce customized theme proposals based on the characteristics of the customer's industry and business goals. After feasibility verification, these proposals will become the planning blueprint for subsequent advertising activities. In terms of keyword strategy, we screen out highly relevant core keywords through competitor and industry research, and combine intelligent bidding technology with matching mode optimization to dynamically expand keyword combinations to ensure that advertising can accurately reach potential customers. The creative production stage integrates AI-assisted tools and professional design resources to generate high-conversion advertising copy and visual materials based on product characteristics and market trends.
Conclusion
The integration of AI and Google Ads is opening a new era of digital marketing. From Duca di Morrone’s doubling of ROI to Delivery Hero’s customer value prediction, evidence shows that AI not only improves efficiency, but also creates micro-optimizations that are difficult for humans to achieve. However, the key to success lies in “human-machine collaboration”—humans focus on strategy and creative direction, while AI is responsible for execution and data analysis-driven iteration. If you are considering introducing an AI advertising solution, it is recommended to start with a small test (such as a PMax campaign for a single product line) and then expand the scale after accumulating experience. Our consulting team has global real-world cases to help you develop an AI marketing blueprint that meets your business goals. Contact us now to explore how to accelerate the AI potential of Google Ads for your brand.
