Problem Description

Introduction Lacoste, a globally renowned fashion and sportswear brand, is dedicated to delivering exceptional customer experiences across its digital platforms. In pursuit of this goal, Lacoste has implemented a chatbot solution to manage customer interactions on its website . However, the current solution has demonstrated limitations in meeting Lacoste's specific business needs and maximizing customer engagement and sales opportunities. As part of its ongoing commitment to innovation and excellence in customer service, Lacoste is seeking a more advanced chatbot solution to enhance its digital customer experience further. Context Lacoste is seeking a solution that offers greater personalization, advanced analytics capabilities, and seamless integrations with other key systems. This RFI represents Lacoste's initiative to explore cutting-edge chatbot solutions that can address these challenges and elevate its customer support and sales capabilities. Lacoste aims to identify a third- partycapable of delivering a comprehensive chatbot solution tailored to its unique requirements, ultimately enabling Lacoste to provide a superior digital experience for its customers. Functional Requirements Integration with Instant Messaging Platforms: The chatbot solution must have the capability to seamlessly connect with various instant messaging platforms such as Messenger, WhatsApp, Kakaotalk, etc., to ensure broad accessibility for customers. Customers are able to continue their conversation on any other plateform. Chat-to-Call or Video Transformation: Ability to seamlessly transition from a chat session to a voice or video call, allowing for enhanced customer support options when needed. Personnalize Customer Relation : Provide agents with the functionality to track customer navigation and access to their datas (orders history, fidelity points, promotion available etc...) enabling them to better understand customer journeys and provide more contextual support. Have access to all customer datas. Real-Time Supervision and Monitoring: Real-time monitoring features must be in place to allow supervisors to track individual and team performance based on agent activity, website traffic, and engagement rates, facilitating continuous improvement and optimization of customer support operations. Customer Voice Analysis: Classify, filter, and export conversations to analyze customer feedback and identify trends for product quality, conversion optimization, and customer satisfaction improvement. Advisors Support : Advisors Support to suggest appropriate processes and personalized responses. Additionally, the system must provide a summary or transcription of calls, including next steps or key points. Product Quality Monitoring: Implement features to monitor and address product quality issues such as exchanges, returns, and customer service contacts, ensuring prompt resolution and customer satisfaction. Conversion Optimization: Enable the chatbot to track and analyze customer actions such as adding items to cart and wishlist, leveraging this data to optimize conversion rates and drive sales. Identify trends and patterns in customer behavior, allowing for the creation of personalized product recommendations and targeted promotional offers. Guided Search and Product Recommendations: Develop capabilities for guided search and natural language text prompts to recommend products based on customer preferences and desirability, enhancing the overall shopping experience. Notification Alerts: Provide notifications to customers when a response is ready or when an action is required, enhancing communication efficiency. Appointment Scheduling: Capability to schedule appointments with customers directly through the chatbot, streamlining the process for both customers and agents. Enable Advanced Analytics and Reporting: analytics and reporting capabilities, allowing the organization to gain valuable insights into customer interactions, agent performance, and trends, thereby enabling data-driven decision-making to continuously improve customer engagement strategies. Nice-to-Have: Implement natural language querying for AI-driven reporting and communication purposes, allowing for more intuitive interactions and insights retrieval.