In the fast-moving, ever-evolving story of digital marketing, the impending demise of third-party cookies has sparked a significant shift in how marketers are approaching data-driven strategies for targeting users. Beginning around the middle of 2024, Google will begin sunsetting their third-party cookies capabilities.

What’s Next After Third-Party Cookies?

This seems like a problem because 71% of consumers prefer personalized ads, which are usually generated by tapping third-party cookies. However, with privacy concerns and regulatory changes shaping the future of online advertising, forward-thinking marketing professionals are exploring alternative solutions to maintain targeted advertising effectiveness. One such solution gaining traction is leveraging AI-powered data as a strategic alternative to third-party cookies.

For many reasons, AI is up to the task. To continue serving personalized ads, AI can harness two types of rich data for its targeting: zero-party and first-party. Zero-party is information that a user purposely provides to a website or business for just their use, and first-party data is gleaned from the user's website activity, and kept just on that website; it is not shared across sites like third-party data is currently shared.

With third-party cookies disappearing, let's examine how AI-powered data can empower marketers to maintain the personalization that both consumers and brands have come to count on.

How to Use AI as a Predictive Analytics Tool

As we are all seeing firsthand, AI does not replace the human touch. While it can be an extremely useful tool that makes our work more efficient, it is still critical to fact-check the work of AI and infuse it with humanity to create AI strategies with careful human oversight.

Here are some smart ways to integrate AI into your predictive analytics tools:

1. Using Zero-Party Data: For AI to replace third-party cookies, it requires good input, and copious amounts. Just as large language models (LLMs) can craft entire books using the data sets they’re provided, marketers can feed their AI tools information about the people coming to their website, and this zero-party data can be used to inform future marketing. For instance, a gated page can capture a site visitor’s demographic and psychographic information. The AI software can then use this to craft content that resonates with this particular user and serve it up to them. Whether it’s a new ad or a retargeted one, the content will reflect some of the users’ tastes and behaviors. As with all LLMs, the more information it is fed, the better it gets to know each user, resulting in a cycle of personalization.

2. Using First-Party Data: Working with first-party research that’s generated by a users’ behavior on the site, AI can deduce preferences, past purchases, and time spent on certain pages, as well as geographic location and certain demographics. This predictive analytics tool can then use valuable information to tailor personalized messages for each user, resulting in higher conversions and stronger brand loyalty. AI-powered algorithms can analyze content context, sentiment, and keywords to serve ads that align closely with the user's interests and intent. Marketers can leverage AI algorithms to dynamically adjust content elements such as headlines, images, offers, and CTAs based on user behavior and engagement metrics. They can also use AI to power their chatbots, which collect first-party information and then use that to interact with the consumer, building rapport and a positive customer experience.

3. Meshing Zero- and First-Party: One of AI's superpowers is its ability to instantly integrate vast amounts of information to derive important insights. By mashing up zero-party feedback with first party-data, an AI tool can also help optimize large and complex online campaigns. It can handle the sheer volume and complexity of hundreds of users accessing a site and transform that into a smart strategy - with the help of a human of course!

4. Using Predictive Analytics Tools: AI can take this information one step further by modeling it for the future. With vast amounts of data, it can perform predictive analytics that help marketers model user behavior, anticipating what products to put in front of consumers, or how to design content. It can optimize ad placement in real time, identify potential churn risks, and even predict future trends, keeping online campaigns optimized and efficient.

Put AI to Work for You

A cookie-less future is a welcome one as people demand better privacy protection online. Now, with the help of AI, marketers can also breathe a sigh of relief as they realize that they can still effectively serve up online advertising to consumers without the benefit of the cookie trail.

As we’ve seen, AI can leverage zero-party information, first-party data, an integration of both, and predictive analytics tools for targeting and personalization that resonates with prospects. While we will all still feel the shift to a cookie-less future, AI is helping to ease the transition. We can help too. If you’d like to learn more about how to deploy AI to target and personalize your advertising, reach out today. We’re looking forward to a better balance of online privacy and efficacy—in a cookie-free world.


Written by Sean Johnson

Chief Strategy Officer Sean Johnson is poised to bring his expertise in data analytics and predictive analysis to a broader platform at Ironmark. His journey is an inspiring testament to the power of vision, dedication, and strategic innovation.

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