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A new report from Coresight Research offers a glimpse into how extensive data gathering has become for brands and retailers.
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From identifying major life changes like a shopper’s marriage or a recent pay bump, artificial intelligence is enabling marketers to learn more about consumers in a way that is almost too intimate.
A new report from Coresight Research offers a glimpse into how extensive data gathering has become for brands and retailers, and how the latest advancements in AI can further expand insights.
“The modern customer profile consists of more than just a name, address and purchase history,” the report said. Multitudes of data points are harvested, from browsing activity and product views to purchase history and email engagement. This data collection is not limited to instances when a shopper makes a purchase. It covers lifecycles.
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“With AI’s ability to continuously collect data and update and analyze customer profiles, marketers can manage engagement throughout the entire customer lifecycle,” the report read. “The assembled data also identifies key milestones for the customer, including first purchase, marriage and increased spending power.”
What may be alarming to proponents of data privacy is exciting for marketers. In 2026, Coresight estimated that the global market for marketing technology will see a compound annual growth rate (CAGR) of 12.2 percent for the rest of the decade, from $54.7 billion in 2026 to $97.5 billion in 2030.
Coresight Research said AI is making it possible for marketers to cut through the noise of nonstop messaging and content that consumers have grown to ignore—even though AI is also partly responsible for the chaos.
The research, which Cloudinary and Amazon Web Services sponsored, identified five pillars of AI-powered marketing personalization: customer intelligence, decisioning, personalization, real-time orchestration, and continuous relationships—all of which use some form of AI, whether it be machine learning (ML), generative AI or agentic AI.
A high level of personalization in marketing requires a strong data foundation for the AI to work. This means having a unified platform that has the ability to access real-time data across various databases and systems, or as Coresight called it: a unified customer intelligence layer.
Coresight cited The Home Depot, for example. With 170 million customer profiles, it could take the company up to 10 days to create new customer experiences based on buying and search activity. AI narrowed this down to a day, thanks to Adobe’s real-time customer data platform, which brought together various data points such as in-store sales, return volume and website activity.
“The ability of AI/ML to find previously unknown relationships among data, fueled by large amounts of computing power, enables marketers to analyze data from large numbers of customers and derive previously unknown customer segments,” Coresight said.
With unified customer data, AI can then determine the next best course of action by determining the best time, place, and channel to reach the customer. For example, Coresight said Coca-Cola is using AI to send email reminders to customers who have not yet checked out within an hour, which has led to increases of 35 percent in open rates, 21 percent in click-through rates, and 8.5 percent in conversion rates.
Since AI agents can operate autonomously, Coresight said marketers can adjust their message based on real-time information such as the customer’s location, the weather that day, and the availability of inventory. This makes it possible to provide personalized product recommendations, as opposed to recommendations based on what is best-selling or what was recently purchased.
“AI accesses consumer profiles and data to make more intelligent recommendations, even incorporating projections of the consumer’s future needs,” Coresight said. “Personalized experiences can provide substantial differentiation and improve conversion and loyalty among consumers who are constantly bombarded with text- based offers and promotions.”
Using AI in marketing can have huge implications for brands. Those that use it have the benefit of understanding and serving their customers better, Coresight said. On the other hand, those that don’t will “miss the opportunity to extract the maximum value” from customer data.
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