Analyze customer service interactions to assess drivers of dissatisfaction. Identification of top drivers for customer calls and customer dissatisfaction by semantically analyzing the unstructured customer service text and attachments (emails/pdfs). Automated framework to analyze this data continuously across 7 countries in 7 languages
- What are the top reasons why customers are calling us? Where do customers think we are difficult do business with?
- Are the reason codes in CRM system and the actual reason (from the description text) why customer is calling aligned?
- Which processes can we transform or automate so that it is easier for customers to business with us?
- Intelligent Machine to monitor customer service data continuously across seven countries in seven different languages.
Extract and interpret customer service data from company’s CRM; email threads; customer service-driven PDF attachments; and service response and fulfillment data from the internal ERP.
- Identified top reasons why customer is call by semantically analyzing the unstructured customer service text and attachments (emails/pdfs). Created a automated framework to analyze this data continuously across 7 countries in 7 languages.
- Identified significant customer facing process complexities and automation opportunities by analyzing customer interaction data, such as email exchange analysis, elapse time, hand offs, internal activities.
- Automated customer service request handling which will significantly reduce the cost of handling and increase the customer response quality