Core Insights - The article emphasizes that effective after-sales service relies heavily on human interaction, especially in technical fields where customer inquiries are often complex and situation-specific [1] - Traditional chatbots struggle to meet customer needs in after-sales scenarios due to their reliance on keyword searches, leading to inefficient and frustrating customer experiences [1] Group 1: Challenges in After-Sales Service - Companies face increasing service costs and pressure as business grows, often relying on human customer service representatives to handle inquiries [2] - A leading motorcycle brand experienced bottlenecks in its service system due to reliance on human agents, leading to three main issues: response efficiency, rising labor costs, and inconsistent service quality [3][4] - The company aimed to alleviate these issues by introducing an AI solution, with a conservative target of a 30% call interception rate [4] Group 2: Implementation of ZENAVA - The introduction of ZENAVA resulted in an average effective conversation interception rate of 65% and an overall call interception rate of 50%, significantly reducing the burden on human agents and lowering after-sales costs [6] - The implementation process prioritized specific scenarios, starting with the company's app, which centralized frequent inquiries and allowed for quick validation of the AI's effectiveness [7] - Clear boundaries were established for the AI's service capabilities, ensuring that complex technical issues were directed to human agents while standard inquiries were handled by the AI [8] Group 3: Collaboration and Knowledge Management - The client company provided in-depth knowledge of its after-sales processes, which helped define the AI's service scope and response logic [10] - The technology provider, Tianrun Rongtong, was responsible for transforming the company's knowledge into usable AI capabilities, ensuring a structured knowledge base for the AI to draw from [11][12] - The successful deployment of ZENAVA in a high-stakes environment demonstrated the necessity of integrating AI into after-sales services to overcome the limitations of human-only support [13][14]
为什么传统Chatbot搞不定售后，天润云（02167.HK）ZENAVA却能接走一半咨询？