The white paper highlights the growing inefficiencies in retail customer support, where agents are overwhelmed by repetitive, transactional queries such as order status, product availability, return eligibility, damaged item claims, and invoice requests. Despite investments in CRMs, OMS, and inventory systems, service teams struggle because these systems aren’t seamlessly connected to customer conversations. This manual context-switching leads to slower responses, agent fatigue, and inconsistent customer experiences, revealing a fundamental need for integration rather than just more tools or headcount.

Vassar Digital’s Gen AI-powered solution introduces a context-aware response layer that connects customer queries directly with backend systems. This intelligent layer interprets intent, fetches real-time data, and drafts accurate, on-brand responses for agent review or automated delivery. By automating 60–80% of repetitive workflows, support teams gain relief from cognitive overload, allowing them to focus on complex cases and escalations that truly need human empathy. Case studies, such as a fast-growth fashion retailer, demonstrate tangible results: an 80% boost in support efficiency, 86% automated email responses, and 75% faster resolution times—all achieved without changing the existing tech stack.

The paper emphasizes that scaling smarter, not bigger, is the future of retail support. Transformation doesn’t require overhauling systems but instead embedding Gen AI into existing workflows in a phased, low-risk approach. Retailers can begin with high-volume workflows like order tracking, product availability, or returns, and then expand as confidence builds. Beyond efficiency, the human impact is profound—agents experience reduced burnout, improved job satisfaction, and greater opportunity for skill development, while customers enjoy faster, more reliable, and empathetic service.

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