Coresight Research has published a new framework for AI-powered retail personalization, mapping five capabilities it says will separate leading brands from the rest. The report, sponsored by Cloudinary and AWS, arrives as the global retail marketing technology market is projected to reach $54.7 billion in 2026, growing at a 12.2% compound annual rate through 2030.
The research frames the opportunity around a simple premise: consumers see thousands of brand messages weekly, but only a few earn attention. Those that do deliver relevance, not volume. Generative and agentic AI now make that relevance achievable at scale, across every channel a retailer operates.
The five-pillar model
Coresight identifies five interconnected capabilities that form a modern personalization operating model. The first is unified customer intelligence, where data from CRM, mobile, in-store, and loyalty programs merges into a single consumer profile. That profile feeds sharper segmentation and predictive insights.
The second pillar, next-best action, uses AI to determine the optimal offer, channel, and timing for each customer. The third, hyper-personalized content, applies generative AI to create and optimize creative assets, product recommendations, and dynamic digital experiences at machine speed.
Real-time orchestration, the fourth pillar, puts AI agents to work continuously, responding to behavior, location, inventory, and context in the moment. The fifth, continuous relationship management, adapts communications as customer needs and life stages change, predicting opportunities for upselling, cross-selling, and retention.
What the technology actually does
Cloudinary's platform, running on AWS infrastructure, handles the visual side of this equation. The company's visual content intelligence and delivery tools let brands manage, optimize, and deliver personalized images and video globally. The practical benefit is speed and scale: generating thousands of image variants in minutes, with load times fast enough to keep users engaged.
The report includes case studies that put numbers behind the claims. Zalando saved 5-7 days by generating 1,800 image variants in minutes. Mattel achieved 80% faster load times, which tripled its activation rate. Marks & Spencer also appears among the featured retailers.
For marketing teams working with AI for Marketing Managers, these results point to a shift in how personalization gets done. The tools are moving from batch campaigns to continuous, automated decision-making about what each customer sees next.
The market context
The $54.7 billion MarTech market Coresight sizes for 2026 reflects spending across the tools and platforms that support this kind of work. A 12.2% CAGR through 2030 suggests retailers expect the investment to compound, not plateau. Brands that build these capabilities now are positioning for the period when AI-driven personalization becomes table stakes rather than a differentiator.
Cloudinary and AWS are also sponsoring a Coresight executive forum on visual experiences at scale. The session features Hejar Oncel, CIO at Follett, and Bridget Roman, Sr. Director of Product Marketing at Cloudinary, discussing how Follett is reimagining visual experiences with AI.
Why this matters for marketing professionals
The five-pillar framework gives marketing leaders a concrete checklist for evaluating their own personalization stack. Most teams already have some form of customer data unification or campaign automation. The gap is in the middle: turning that intelligence into visual content that actually reaches the right person at the right time. If your team still produces image variants manually or waits on creative bottlenecks, the Zalando and Mattel numbers show what's already possible. The full report is available from Coresight Research, and the executive forum registration is open for those wanting to hear the Follett case directly.
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