Marketing today depends heavily on digital advertising to reach consumers and many digital businesses rely upon revenue from personalized ads. In the last few years, advertising agencies have targeted ads using third-party cookies to track users’ preferences.
However, many companies, such as Apple and Google, recognize how third-party cookies pose several privacy concerns. In response, digital marketers have begun developing cookieless solutions powered by AI.
AI has become an incredibly powerful tool for innovation with companies implementing it for use in management, robotics, and, now, marketing. One method of AI-based marketing known as contextual advertising has already shown incredible results, leading experts to predict the market for contextual advertising to reach $376 billion by 2027.
In this article, we will discuss the issues with current cookie-based marketing methods, and explore the AI-powered innovations to digital marketing that Google, Meta, and IBM have begun developing.
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The Problems with Cookies
Digital marketing agencies often use a controversial technique called fingerprinting to personalize ads for users. Fingerprinting relies on third-party cookies that generate user-specific browser ID tags.
Every time a user accesses a website with a cookie-based ad, an embedded script, called a tracking pixel, collects the user’s browser tag and sends it to the advertiser’s server.
The ad agencies develop user profiles associated with the browser tags and track browser history, purchases, and other user information. With their detailed user profiles, ad agencies can suggest highly personalized ads.
Users, however, often know little about what personal information ad agencies collect and have little power to prevent unwanted data collection unless they manually disable cookies on their browser.
Apple and Mozilla have recognized these privacy concerns, disabling third-party cookies on Safari and Firefox. Additionally, Google has announced Chrome will disable third-party cookies within two years as the company currently relies on revenue produced from cookie-based ads.
How AI is Replacing Cookies
AI integration in advertising is the key to cookie replacement. AI can process several different kinds of data in many formats. Collecting real-time user data such as search history, custom preferences, demographics, and weather information, AI can analyze users’ behavior, find patterns, and personalize ad recommendations to target users’ current product interests.
AI solutions can also provide effective ads without collecting personally identifiable information (PII) and avoid privacy issues resulting from identity-based advertising. Instead of tracking individual users and their personal, private data, AI advertising algorithms analyze user behavior to group people into different audiences based on their preferences.
AI advertising leverages data more effectively than cookie-tracking methods and provides more insightful preference information to advertisers. So, customers benefit from better ads, and the digital marketing industry benefits from higher conversion rates.
Google, Meta, and IBM have all begun developing AI-based advertising algorithms to replace cookie-based methods. Below, we will describe each company's solution in more detail.
Google’s Privacy Sandox and Topics API
To develop tools that help digital businesses thrive and resolve privacy concerns, Google launched the Privacy Sandbox initiative to reduce covert tracking and improve internet privacy standards.
The initiative plans to phase out the Chrome browser’s use of third-party cookies altogether within two years. As a replacement for cookie-based ad recommendation methods, Google has introduced a new AI-based algorithm, the Topics API.
The Topics API works by analyzing browser history to determine a topic that represents a user’s interests for that particular week. The algorithm processes all user information locally without communicating potentially sensitive or private information with external servers.
When a user views a Topics-affiliated site, the API shares three of the user’s topics, one from each of the last three weeks, with ad companies to help them personalize their digital advertising.
The browser deletes topics and user data after three weeks, keeping preference information relevant without storing user information long-term. The API also excludes sensitive categories such as race and gender.
The Privacy Sandbox plans to launch developer trials of the Topics API soon to gather feedback before implementing their solutions into the Chrome browser.
Meta’s Conversions API
Meta has taken a different approach to cookieless marketing with their new Conversions API. Previously, Meta’s advertising service, the Facebook Pixel, measured conversions on a browser level, requiring cookies.
Now, their new API bypasses browser-based data collection techniques and shares data directly from an advertiser’s server to Meta’s databases. Meta claims its algorithm will help reduce cost per action for brands while honoring users’ privacy preferences.
IBM Watson Advertising
Another effective, cookieless strategy for digital marketing, contextual advertising, focuses on showing ads based on context (website content, location, weather, etc.) in certain parts of a webpage to catch a user’s attention. In the cookieless future, contextual advertising provides valuable insights into which products and services users are interested in.
IBM’s advertising tool, the IBM Watson Advertising Accelerator, uses an AI-based contextual advertising algorithm and predictive analytics to cluster users into audience groups and provide relevant, timely, and interesting ads accordingly.
With their powerful Watson AI, IBM’s tools improve ad recommendations without the use of invasive tracking techniques.
How Will Cookieless Advertising Affect Digital Marketing
Despite their controversies, cookie-based marketing strategies have allowed many ad agencies to provide relevant, preference-based ads for years, and, with their eventual removal, companies will need to adjust to the cookieless future.
Fortunately, AI-based solutions offer powerful alternatives to cookie-based advertising by clustering users into audiences based on contextual information and browser history.
With AI solutions, digital marketers can also improve their relationships with internet users by respecting their privacy. If users know their sensitive data remains safe, they may be more open to engaging with ads and trust brands.
Already companies including Toyota, Mastercard, Chevrolet, and CVS have begun benefitting from AI-powered advertising solutions, reaching millions of consumers and increasing brand preference.
Conclusion
As more and more companies continue recognize the power of AI, technology will continue to evolve to harness its data-processing capabilities.
AI-powered marketing offers marketers and brands an opportunity to phase out older, privacy-breaching advertising methods and use new, highly-accurate and trustworthy ad personalization algorithms.
In addition to helping brands grow, AI solutions will allow consumers to regain trust in digital marketing and explore the products they want to see.
