### Retail's Data ImperativeRetail stands at a pivotal moment where trusted customer data emerges as the defining competitive advantage. A Stibo Systems study of 500 U.S. business leaders reveals that 91% view customer-data management as critical, yet only 31% fully trust their data, leading to lost revenue for over half and reputational damage for nearly one in three. This gap hampers personalization, slows AI adoption, and fragments operations amid rising shopper expectations and multichannel complexity.Data fragmentation persists as a core barrier, with experts forecasting it will degrade AI performance in 2026 even as the technology scales. Retail AI could unlock $240–$390 billion in value, with 91% of leaders investing and early adopters achieving returns six times faster, potentially capturing three-quarters of the $164 billion market by 2030. Those connecting data across stores, customer interactions, inventory, and orders gain the clearest operational visibility.### Impact on Product Feeds and Catalog StandardsPoor data quality directly undermines product feeds, the backbone of e-commerce discovery and sales. Fragmented customer and inventory data results in inconsistent feeds, where stock levels appear available post-sale, causing overselling and customer frustration. Real-time data processing addresses this by enabling instant updates, preventing missed sales and supporting dynamic pricing based on demand and trends.Catalog standards suffer without governance: 57% of organizations lack policies, creating system inconsistencies that weaken multichannel visibility. Trusted data enforces uniform quality standards, ensuring feeds integrate seamlessly with merchandising and commerce systems. By 2026, retail media evolves into a unified operating system, collapsing fragmentation so media, pricing, and sales data align for precise product discovery and promotion. The challenges of managing **product feeds** are further addressed in our blog post.### Elevating Card Quality and Assortment VelocityCard quality—product detail completeness and relevance—hinges on clean data integration. Fragmented sources yield incomplete profiles, spawning irrelevant recommendations that erode trust. Customer Data Platforms (CDPs) unify data from POS, online platforms, and social channels into 360-degree views, incorporating identity resolution, AI-driven segmentation, and profile enrichment for fuller, accurate cards. Understanding the importance of quality product descriptions can greatly improve **card quality**, which is discussed in further detail in our blog.This unification accelerates assortment velocity, the speed of onboarding and updating products. No-code tools and AI thrive on trusted data, automating cataloging to push real-time personalization and self-healing displays. Without it, AI initiatives falter—28% of leaders report struggles implementing them due to unready data—limiting dynamic content and engagement.### No-Code, AI, and the Path to ScaleNo-code platforms amplify data's power by democratizing access, allowing rapid feed adjustments and catalog builds without deep coding. AI elevates this: connected data enables predictive forecasting, tailored recommendations, and operational decisions, shifting AI from support to primary driver in commerce and experience. If you want to understand how you can utilise artificial intelligence, we have written an article about **Artificial Intelligence for Business - NotPIM**. Edge computing further boosts speed, handling large streams for agile scalability over rigid cloud reliance.Retailers prioritizing governance—defining ownership and standards—turn data into resilience. Real-time activation via CDPs triggers precise offers, notifications, and pricing, fostering engagement. As regulations tighten and transparency demands rise, this foundation ensures AI precision, preventing confusion from mismatched insights and positioning data-ready operations ahead. For any e-commerce business, proper implementation of a **product feed** is essential.*Retail Customer Experience* *Retail Dive****As the findings highlight, the future of e-commerce hinges on the ability to manage and leverage product data effectively. This shift towards data-driven operations underscores the importance of solutions like NotPIM. Our platform directly addresses the challenges of data fragmentation and poor quality through automated product feed transformation, enrichment, and catalog management, giving retailers the tools they need to capitalize on the opportunities presented by AI and personalization.