6 Our experience so far shows speedy results. We’ve seen some marketers deploy gen AI to personalize content development 50 times faster than a more manual approach (see sidebar “How a European telecom used gen AI to enhance marketing materials”). Technology as a foundational differentiator To better target promotions and gen AI–boosted content, companies can turn to a tech stack that brings everything together. In 2019, McKinsey published “A technology blueprint for personalization at scale,” which described a “4D” strategy (data, decisioning, design, and distribution) for marketing technology. 2 We add one more critical element to this: measurement (exhibit). (It’s not a “D,” but it’s just as relevant.) Marketers can establish a solid foundation for growth through personalization by ensuring these five elements use the latest technological innovations and integrate with each other seamlessly (see sidebar “A tech-enabled evolution from mass discounts to targeted offers”). Data By improving data collection and analysis, marketers can gain deeper insights into customer behaviors and preferences. And while many enterprises have invested in data lakes (storage platforms that hold, process, and analyze structured and unstructured data) and customer data platforms (software that centralizes and unifies customer data from multiple sources to create a single view of each customer), better targeted offers and content requires expanding data architecture in five categories: • a promotions subject area that includes the history of offers and redemptions • a content subject area that includes the history of content delivery and engagement • universal (and potentially gen AI–enabled) metadata and taxonomy, which can improve the flow of automation Exhibit Web <2025> Exhibit <1> of <1> Technology blueprint for personalization at scale Marketers can establish a solid foundation for personalization with an effective technology framework. McKinsey & Company Data Fully automated single source of truth for consumer data to serve real-time needs of activation, analytics, and measurement Decisioning Advanced analytics and machine learning to create customer scoring and real-time triggers Design Central repository to enable dynamic offers and creative optimization Distribution Architecture to deliver messages and experiences across channels Measurement Comprehensive, cross-channel metrics to inform on performance and engagement 2 Sean Flavin and Jason Heller, “A technology blueprint for personalization at scale,” McKinsey, May 20, 2019.