The company is a financial services firm that provides a broad range of solutions and services to a global customer base. The company has a comprehensive network of facilities around the world, with over 5000 associates assisting their customers. Customers lodge service requests by telephone, email, or through an online chat interface. As a B2C service provider, the company strives to maintain high standards for effective communication between their associates and customers, and tries to monitor customer interactions at every opportunity. The broad objective of this service performance monitoring is to maintain satisfactory quality of service over time and across the organization. To this end, the company has devised a set of standards for service excellence, to which all customer interactions are expected to adhere. These standards comprise different qualitative measures of service levels (e.g., associates should use clear and understandable language, associates should always maintain a professional and friendly demeanor, etc.) Associates’ performances are measured based on compliance with these quality standards. Organizational units at different levels, like teams, departments, and the company as a whole, also receive scores based on associate performances. The evaluations and remunerations of not only the associates but also of management are influenced by these service performance scores.

Questions for Discussion

1. How did the financial services firm use text mining and text analytics to improve its customer service performance?

2. What were the challenges, the proposed solution, and the obtained results?