Analyze Customer Feedback in the Banking industry

Tasks

• Analyze open-ended responses and free-form comments from customer surveys, contact center interactions and social media.
• Enrich internal systems with industry-oriented customer feedback analysis.
• Obtain full analysis of the Voice of the Customer categorization in Banking.

Companies can no longer afford to ignore customer feedback coming via unstructured channels and comments: interviews, open-ended survey responses, contact center interactions (email, phone, chat), social conversations. These comments possess a level of spontaneity and often include references to the root causes of the problems that make them particularly valuable.

However, in order to embed this information automatically into the company's processes and enable them to effectively take this feedback into account, it is necessary to perform an analysis that is highly adapted to this domain.

This Bot uses MeaningCloud's semantic analysis APIs and the predefined models of its Vertical Pack for the analysis of the Voice of the Customer in Banking to implement customer feedback analysis adapted to this industry.

The Bot receives the text from an unstructured comment and returns a multilevel categorization based on typical categories of the banking industry: companies, products, operations, customer service activities, interaction channels, quality parameters. In addition, the Bot can return a positive/negative/neutral polarity analysis related to these categories and a specific customer satisfaction dimension. The Bot will also output the JSON with the complete analysis returned by the API.

The Bot enables the immediate analysis of customer feedback in the banking industry with high relevance and accuracy without the need to develop specific domain configurations. In this way, that feedback can be embedded into the company's processes and enrich its internal systems (CRM, marketing automation) with very valuable information about the needs, perceptions and preferences of customers.