Our Project Journey

1

Identifying the Challenge of Overloaded Support Teams

An expanding e-commerce business enterprise fought against excessive patron inquiries, specially during height seasons, that overwhelmed their help teams. This created sluggish responses, longer functioning costs, and dipping consumer pride, emphasizing the need for an automated, scalable solution.

2

Designing an AI-Powered Chatbot with NLP

We created a bespoke chatbot embedded in the client's website and mobile application, leveraging natural language processing (NLP) to learn and respond to questions across various languages. The chatbot was also trained on the client's past support data to cater to frequent questions such as order tracking and returns, to provide precise and context-sensitive responses.

3

Implementing Escalation and Learning Mechanisms

The system was designed to increase complicated issues to human agents, while learning from frequent interactions to improve their reactions. The machine learning algorithm enabled the chatbot to enable the new query pattern and user behavior, increasing its effectiveness over time.

4

Seamless Integration and Multilingual Support

The system was designed to increase complex issues to human agents, while learning from frequent interactions to improve their reactions. The machine learning algorithm enabled the chatbot to enable the new query pattern and user behavior, increasing its effectiveness over time.

5

Measuring Impact and Optimizing Performance

Post-Launch, Chatbot handled 70% inquiries independently, cutting the response time ranging from 10 minutes to 30 seconds to 50%. Customer satisfaction increased by 25% due to immediate 24/7 support, and the customer saved 30% in the support cost, making his team focus on strategic priorities.