USE OF SEMANTICASE FOR CUSTOMER CARE
In the Customer Care area, a lot of information is processed and categorized by the operators to define the complaint management path, the priority and methods of contact and response.
The complaint is characterized by being a written text (if received via digital channels) or vocal (if the phone call is recorded) very rich in information both in terms of content and in terms of the “customer side” perception of the criticality of his exposed situation.
The complaint by its nature comes processed individuallywhile for the monitoring trends of complaint are used classifications generally carried out by operators.
Our semantic analysis project applied to commercial complaints, technical, informative, represents an opportunity from many points of view:
MEANINGS
The meanings underlying the client can be analyzed, without imposing interpretative filters, extracting the meanings directly from the written text.
VOLUMES
Semantic analysis allows you to compare large quantities of complaints.
FEELING
The client's communication style is analyzed with respect to the service offered, and the experience / judgment in relation to the contents of the complaint is monitored.
NATURE OF DATA
The data path of interest to the customer is defined on which to carry out the analysis.
The path can consist of written texts accompanied by other information variables, or be an expression of voice messages or from OCR.
CUSTOMIZATION
It is possible to customize the customer-specific semantic analysis model, which can independently manage the execution of the analyzes and have a dashboard of specific results.
THE COMPLAINTS ANALYSIS PROJECT FOR ENEL
For Enel, with whom we have been working for over a year, we have carried out a customization of the Semanticase tool, and provided the software for the autonomous management of the analysis of complaints (after specific training).
Further each month we prepare a report on the data relating to the last 13 months of the web complaint, carrying out all the semantic analyzes and to return a consistent classification of the content emerged, of critical areas from the point of view of sentiment and gods monthly trend trend found.
The volume of complaints is on average organized into a low number of summary topics, making understanding of the phenomena and critical issues manageable.
From the analysis of the complaint, indications and reflections on the actions functional to the resolution of the critical issues that emerged , complaint risk mitigation.
The continuous investment in the models of understanding and listening to the customer, the desire to experiment and understand new models in data management in synergy with the customer, make the complaints project a approach of customer focused highly innovative.