This paper discusses harnessing omnichannel customer feedback data using deep learning, and integrated with NPS survey data to deliver superior customer experience (CX). While there is lot of work done and tool availability in this field for English, there is a lack of algorithms and research done for local languages, such as Bahasa Indonesian. We describe our Quasi Recurrent Neural Network (QRNN) based approach that we used on customer omnichannel feedback for topic modelling, priority prediction and sentiment classification. We further demonstrate the use of our work for multiple clients in Indonesia, in order to set up an advanced CX monitoring and improvement programme (CXM). We showcase our holistic approach to customer experience, integrating omnichannel customer feedback data with NLP-based predictions. We also showcase two cases where we deployed our intelligent CXM tool and set up intelligent conversation monitoring systems to predict customers at the verge of churn-out, beforehand.