Core Insights - I.T Group, a prominent fashion retailer in Asia, faces significant challenges in customer service due to high inquiry volumes, ineffective traditional NLP chatbots, and lengthy response times for complex after-sales scenarios [1][2][3] Group 1: Business Challenges - The customer service team handles nearly 25,000 inquiries monthly, exceeding 35,000 during peak sales periods, with an average handling time of 2 minutes per inquiry, leading to high service pressure and low efficiency [1] - Previous investments in NLP chatbots yielded a low resolution rate of 78%, struggling to understand customer intents accurately, such as misinterpreting cancellation requests [1] - Complex after-sales inquiries require extensive information gathering, resulting in an average handling time of 7 minutes, negatively impacting service efficiency and customer experience [1] Group 2: Solutions Implemented - I.T Group adopted NetEase Cloud's customer service Agent solution, utilizing a hybrid model where 70% of common inquiries are handled by traditional NLP chatbots and 30% by human agents, optimizing both accuracy and cost [3] - The company prioritized three high-frequency, high-value scenarios for pilot testing: pre-sale size recommendations, post-sale order cancellations, and post-sale return assistance [3] Group 3: Achievements - The new solution improved response speed by 60% in pre-sale inquiries, reducing handling time to as little as 17 seconds, significantly alleviating pressure on customer service staff and enhancing conversion rates [4] - For complex after-sales inquiries, the handling time was reduced from 7 minutes to 3 minutes, while also gathering valuable input on cancellation reasons [4] - The customer service Agent demonstrated improved intent recognition and interaction quality, achieving a user satisfaction rate of 97%, particularly in managing customers with negative emotions [4]