French Telecom improved customer experience by converting Chatbot to Conversational AI
Client Overview
Our client is a leading Telecommunication Services Company with operations in 26 countries and 142,000 employees worldwide. The Group has a global customer base of 259 million people, including 214 million mobile customers and 22 million fixed broadband subscribers.
Business Problem
Our client is a leading French Telecom company who had big plans to drive digital transformation. Its aim was to provide a seamless, personalized customer experience to increase customer satisfaction and loyalty. Our client had a chatbot on their Web Application to address end customer queries but had a low confidence score of 20-30% resulting in lower customer experience. The chatbot needed to identify the conversation and respond correctly to the customers with improved confidence score. To accomplish this, the telecom firm required a competent and experienced rollout partner to implement the system.
Our Solution
PureSoftware partnered with the client to analyze the root cause of the problems and decided to implement a machine learning based chat-bot to enhance customer experience to guide customers throughout the process. Our team with extensive experience performed the following:
- Changed the machine learning model from Sklearn to deep learning model embedding TensorFlow.
- Migrated the ML model from pre-trained to Deep learning embedding training in which model is trained based upon the corpus of own dataset.
- Apply Keras policy of Deep Learning for response prediction.
- Fine tune the TensorFlow embedding model according to the dataset so that it can give high confidence score.
Results
After a successful rollout, our client experienced enhanced customer experience as the chatbot had an improved confidence score of 70 to 80%.
Chatbot was able to identify the conversation and respond correctly to the customers.
The Project went live within 6 Weeks and provided with improved UI for a better customer experience.
