Analyze patients feedback
to improve organization performance

Understand and improve patient experiences by gleaning insights from B2C communication

channels & customer feedback

How it works?

The Sentiment & Entity Analysis solution enables organizations in healthcare to analyze patient feedback — be it reviews, support requests, or phone calls.

 

Powered by NLP, it analyzes texts and converted audio-to-text data to assess message sentiment as positive, neutral, or negative and assign it to a given entity. While scanning through the text, the solution detects such keywords as brand titles, types of services, contact data, etc.

 

The data processed is stored in a database for further use in ML applications, or it can be displayed in a Business Intelligence dashboard for analysis and review by customer support teams.

Download as PDF

Key Features

  • Sentiment and entity classification

  • Object-oriented sentiment analysis

  • Emotion detection and recognition

  • Support of various data sources (chatbot messages, social network messages, support requests, emails, etc.)

  • Batch (schedule) or real-time forecasting

  • Secure, scalable, and customizable

  • Easy integration through RESTful API

Key Benefits

How to deploy our software products?

Need more information?