Abstract

Modern service enterprises are challenged by a strong competition and dynamically changing business environments. Consequently, the precision of the business requirements identification and rigorous planning regarding investments to information technologies play a key role in the implementation of new capabilities. As the business today is more and more powered by information that is unstructured, social and distributed via various channels, the multi-channel interaction is a reality. It means each customer generates more and more data. On the other hand, a customer is often flooded with a huge amount, mostly not relevant, advertising information. Companies are challenged to collect the data from the customer interaction, analyze it and prepare an intelligent recommendation for an agent or to feed relevant offers to the customer. Modern understanding of the unstructured information requires a fundamentally new approach using the technology to deliver insights, ideas, and an intuition into the rapidly growing and diverse data that customers deal with every day. A hot topic is to decrease the costs and increase the customer satisfaction. One of the sensitive areas is customers’ interaction via company’s contact web forms. This interaction consists mostly of questions or complaints. Accordingly, we describe in our paper a new approach for generating these contact forms using the textual analytics, processing of frequently asked questions and a rule-based system. We also present particular use-cases to illustrate how this approach works in practice.

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