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.
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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