Case Study: a D2C fashion brand achieves 85% chat resolution and 60% ticket resolution with Robylon AI

For a D2C Fashion brand, Robylon automatically resolved 85% chat queries and 60% tickets

a large d2c ecommerce brand specializing in clothing, footwear, and accessories faced a significant customer support challenge. They were receiving over 100,000 monthly queries, with 70% being repetitive questions about order tracking and returns. Their existing flow bot only automated 50% of chats, while ticketing was entirely manual, so they needed an AI agent from Robylon that could understand natural language and provide fast, personalized responses.

Robylon implemented its AI agent, deploying over 100 pre-built ecommerce workflows. The solution used an intent identification engine trained on historical data to understand user queries, automatically resolve them by triggering relevant APIs, and seamlessly escalate complex issues. As a result, Robylon automatically resolved 85% of chat queries and 60% of tickets, with responses generated in just 3-6 seconds, drastically improving efficiency and customer experience.