Next-Generation Retail Catalog Management: AI, Microservices, and Cloud-Native Technologies
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V6I1P106Keywords:
Retail Catalog Management, Microservices Architecture, Machine Learning, Artificial Intelligence, Cloud-NativeAbstract
Digital commerce brings new product management needs to retailers who maintain different catalogs on various channels. The traditional management systems for catalogs cannot handle quick updates or individual recommendations anymore. This research explains how AI-powered automation boosts retail catalog management through separate services and cloud-based technologies. Catalog management gains power from AI to sort products effectively while enriching content automatically and reacting to market changes through price adjustments and user targeting. Machine learning helps maintain accurate data while decreasing human work costs and boosting search results. The microservices system design enables retailers to grow their business while adopting new features easily to match market changes. Cloud-native deployments deliver uninterrupted system access across multiple computers, plus they link effortlessly with third-party services. By adopting modern technology, retailers get better product performance through speedier acceptance and better quality data delivery, plus enhanced customer satisfaction. This work examines present-day challenges of catalog management, such as data security issues plus API integration and management problems, which it explains how to address. We show examples of present-day retailers who successfully deployed next-generation catalog management in their retail stores. This research offers strategic recommendations to retailers and IT leaders who want to use cloud-based AI solution microservices for superior catalog management in today's dynamic retail business
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