Atomic Omnichannel: Reinventing Retail Personalization with Generative-AI Content Factories

Abstract

With hyper-personalization, retailers, need to provide a steady one-to-one customer experience across various channels that include eCommerce websites, email, push notifications, and SMS. The presented paper suggests the concept of the Atomic Omnichannel framework, a scalable individualization system that runs on Generative-AI contentious. Basing on real-time customer cues, these factories are dynamic assembly of modular content blocks with a combination of text and image data via multimodal learning. The delivery of asynchronous content overheads to Kafka-driven event mesh, and automatic QA agents based on NLP or computer-vision grant quality and compliance with little human interference. The system has been tested on 12 retail brands and shown impressive improvements: up to 108 percent of click-through rate increments, 90 percent decrease in the time it takes to create campaigns, and the improved personalization accuracy of up to 75 percent. Real-time scalability of millions of users with latency rates below a second was validated with performance benchmarks operated on peak load. The researchers point out the revolutionary effect of Gen-AI personalization on work efficiency and contact with clients. Through this, retailers are capable of leaving manual, departmentalized campaigns aside and shifting into large scale dynamic customer-cantered experiences. The final passage of the paper informs about some aspects of moral choices, further growth in AI/VR customization, federated artificially intelligent agents, and independent creative pipelines. Atomic Omnichannel is therefore an example of a blueprint of next-generation and AI-native retail engagement.