Fashion Retailer Automates Customer Support with AI Agents

Challenges

• High Volume of Customer Queries: Sales events and product launches led to query spikes, overwhelming the support team and causing delays.
• Slow Response Times: Manual handling resulted in average first response times exceeding six minutes, leading to customer frustration.
• Scalability Issues: Hiring and training additional agents for peak periods was costly and inefficient.
• Repetitive Inquiries: Most queries were routine (order status, returns, shipping), consuming valuable agent time.
• Maintaining Brand Voice: Ensuring consistent, on-brand communication across automated and human interactions.

Our Approach

• Discovery & Integration Mapping: Worked with client stakeholders to identify high-volume query types and map required integrations with Kentico and internal systems.
• AI Model Training: Used historical chat transcripts and product documentation to fine-tune the AI for brand voice and domain-specific queries.
• API Development: Built secure endpoints for order, refund, and return data retrieval.
• Pilot & Iteration: Launched the chatbot in a controlled environment, iteratively improving based on real user feedback and agent input.
• Full Rollout & Monitoring: Deployed across all digital touchpoints, with ongoing analytics to track performance and identify new automation opportunities.

Project Overview

Facing a surge in digital sales and customer queries—specially during peak —the client want to enhance customer support efficiency, provide 24/7 assistance, and reduce operational costs. The primary objective was to automate repetitive support interactions, improve response times, and enable human agents to focus on complex, high-value conversations.

Solution

We designed and deployed a multi-channel Generative AI Agent, deeply integrated with the client’s Kentico-based e-commerce backend and internal systems. Key features included:

• Natural Language Processing (NLP): For understanding and responding to customer queries conversationally.
• Real-Time API Integrations: The bot fetched order status, refund timelines, and return eligibility directly from internal databases and finance systems.
• Hybrid Retrieval-Augmented Generation: Combined with document embedding to answer FAQs and policy questions accurately.
• Seamless Human Handoff: Complex or sensitive cases were escalated to live agents, with full conversation context passed along.
• Personalized Product Recommendations: Leveraged customer data for upselling and cross-selling opportunities.
• 24/7 Availability: The AI agent operated round-the-clock, ensuring no customer query went unanswered.

Tech Stack

• Kentico Xperience: E-commerce platform and CMS.
• Generative AI (Large Language Models): For conversational intelligence and retrieval-augmented responses.
• Document Embedding Technologies: Powering FAQ and policy answers.
• RESTful APIs: For real-time integration with order management, finance, and returns systems.
• Secure Cloud Hosting: Ensured scalability, reliability, and data security.
• Chat Widget: Embedded on web and mobile channels for direct customer interaction.