Everyone Should Know AI Advertising Strategies
With the rapid development of AI technology, the advertising industry is undergoing unprecedented changes. However, tightening privacy regulations and adjustments to platform policies (such as Chrome’s restrictions on third-party cookies) have also created new challenges for brands. How to effectively use Google ads to increase brand exposure and conversion rates while protecting user privacy has become a key issue in current digital marketing. This article will provide a comprehensive strategy to help brands achieve efficient advertising in the AI era.
I. Advertising Changes and Challenges in the AI Era
1. Background: AI Technology Reshapes the Advertising Industry
AI technology is reshaping how the advertising industry works. From precise delivery to data analysis, the application of AI makes advertising more intelligent. However, as awareness of privacy protection increases, governments around the world have introduced relevant regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). These regulations require brands to obtain explicit consent from users when collecting and using user data and ensure data security. In addition, the Chrome browser’s restrictions on third-party cookies further make data collection more difficult. Traditional advertising methods rely on third-party cookies to track user behavior, but with the trend of privacy protection, this method is no longer feasible. Therefore, brands need to find new ways to collect and analyze data to achieve precise delivery.
2. Core Issue: Balance Between Privacy Protection and Advertising Effectiveness
How to use Google display ads to increase brand exposure and conversion rates while protecting privacy has become a core issue facing brands. Traditional data collection methods are limited, and brands need to turn to high-quality first-party data and combine it with privacy protection technology to achieve precise delivery.
II. Basic Strategy: Establishing a High-Quality First-Party Database
1. Collect High-Quality Data with User Consent
With the trend of privacy protection, first-party data has become a brand’s most valuable asset. First-party data refers to data that brands collect directly from users, such as emails, phone numbers, purchase history, etc. First-party data has higher accuracy and reliability than third-party data. In order to collect high-quality first-party data, brands need to obtain explicit consent from users. This means that when collecting data, brands should provide a clear privacy policy and let users understand how the data is used. In addition, brands should also offer value exchanges such as coupons, exclusive content, etc. to increase user engagement and trust.
2. Use Google Analytics and Enhanced Conversions to Enhance Data Collection and Analysis
Google Analytics is an important tool for brands to collect and analyze first-party data. With Google Analytics, brands can track user behavior on their website, such as page views, time spent, conversion rates, and more. This data can help brands understand user needs and preferences to optimize advertising strategies. Enhanced Conversions is a feature provided by Google that helps brands improve the accuracy of their conversion data. With Enhanced Conversions, brands can match users’ conversion data (such as purchase amount, product category, etc.) with conversion data from Google display ads to get more accurate conversion reporting.
3. Establish Long-Term Value Exchange and Improve User Trust and Data Quality
In order to enhance user trust and data quality, brands should establish a long-term value exchange mechanism. This means that brands should continue to provide users with valuable content and services, such as personalized recommendations, exclusive offers, etc. In this way, brands can not only increase user engagement, but also collect more high-quality first-party data.
Case: Kia activates first-party data through Google Analytics and Customer Match
Kia, a globally recognized automotive brand, uses Google Analytics and Customer Match to activate its first-party data to improve advertising effectiveness. Through Google Analytics, Kia tracks user behavior on the website and matches this data with conversion data from Google display ads . In addition, Kia uses Customer Match to retarget its existing customers to increase conversion rates for its ads. In this way, Kia successfully improved its advertising performance and achieved a higher return on investment.
III. Technological Innovation: The Combination of Privacy Protection Technology and AI
1. Privacy Sandbox: Chrome’s Privacy Protection Solution
Privacy Sandbox is a privacy protection solution provided by Chrome browser that is designed to replace third-party cookies. With Privacy Sandbox, brands can continue to collect and analyze user data while protecting user privacy. Privacy Sandbox provides a series of APIs, such as FLoC (Federated Learning of Cohorts) and TURTLEDOVE, which can help brands achieve precise delivery without tracking individual users.
2. Differential Privacy and Confidential Computing: Technical Means to Ensure Data Security
Differential privacy and confidential computing are two important privacy protection technologies. Differential privacy protects the privacy of individual users by adding noise to the data. Confidential computing uses encryption technology to ensure the security of data during processing. These technologies can help brands continue to use data to optimize advertising while protecting user privacy.
3. AI-Driven Advertising Optimization
AI technology plays an increasingly important role in advertising optimization. With AI, brands can automate the ad serving process and make adjustments based on real-time data. For example,Google ads Smart Bidding feature can automatically adjust ad bids based on user behavior and conversion data to maximize ad effectiveness.
IV. Practical Strategy: Applying SKAdNetwork and Transformation Modeling
1. Set Up the SKAN Conversion Value Structure to Track Installation and Subsequent Events
SKAdNetwork (SKAN) is a privacy solution provided by Apple that tracks the installation and subsequent events of iOS apps. SKAN allows brands to capture app install and conversion data without tracking individual users. To get the most out of SKAN, brands should set up a conversion value schema to track different events such as app installs, signups, purchases, etc.
2. Combine with Google ads API to Achieve More Precise Advertising Optimization
The Google ads API helps brands automate their ad serving process and make adjustments based on real-time data. By combining SKAN and the Google ads API, brands can achieve more precise ad optimization. For example, brands can automatically adjust ad bids based on conversion data provided by SKAN to maximize ad performance.
Advantages of Transformation Modeling: Provides Immediate Data to Fill SKAN’s Time Delay Shortcomings
A major drawback of SKAN is the time delay in data reporting. Because SKAN requires a certain amount of time (e.g. 24 hours) to report data, brands cannot make adjustments based on real-time data. Conversion modeling can fill this gap. Through AI technology, brands can predict current conversion rates based on historical data, thereby enabling faster advertising optimization.
Case: LINE Manga integrated with Google ads through SKAN, reducing CPA by 28%
LINE Manga is an online comics platform. In order to improve advertising effectiveness, LINE Manga integrates SKAN with Google Ads. In this way, LINE Manga managed to reduce CPA (cost per action) by 28% and achieve a higher ROI.
V. Topkee’s Google ads Service
Topkee provides one-stop online advertising services based on Google ads to help brands increase potential customers and sales. Whether it's a small business or a large corporation, Topkee has a solution for it. Topkee uses the latest website scoring tools to conduct a comprehensive website assessment and provides detailed SEO issue reports and solution recommendations to help brands improve their ranking in search results.TM is a flexible customer tracking tool that can be customized and configured based on advertising sources, media, accounts and other factors to achieve more precise advertising. Topkee combines the brand's product information and market trends, and uses AI technology to generate creative text and images to improve the efficiency of online marketing activities.
Conclusion:
In the AI era, brands need to combine first-party data, privacy protection technology and AI-driven advertising optimization methods to achieve efficient advertising. By building a high-quality first-party database, applying privacy protection technology, and combining SKAdNetwork and conversion modeling, brands can increase brand exposure and conversion rates while protecting user privacy. If you need further assistance, please contact Topkee's professional consultants and we will provide you with customized advertising solutions.
