Sentiment Analysis

The application performs voice and text analysis to identify user sentiment about a product, service or an event. The Neural Network is pre-trained with a large amount of text and audio from Social Media and other public repositories. The analysis can be performed in real time or offline.

 

Problem

Organizations spend huge amounts of money on marketing/advertising to gain users, but a lot of them also struggle to retain consumers whether due to inferior product or customer service. In most cases, customers make their dissatisfaction known on Social Media, E-mails to the company or on phone calls to their call center. If Companies can harness this resource to identify dissatisfaction and offer discounts or other retention strategies to their consumers the attrition rates can be drastically reduced.

Solution

By leveraging Sentiment analysis tool, Organizations can quickly identify dissatisfied consumers (voice/text) and take remedial steps almost near real time. An automated bot can be built to post on their social media channels how the company plans to address the situation, for example. Patterns can be identified by age and gender to build targeted solutions.


 

Use cases

Customer Service

Customer Loyalty

Brand Equity

Industry

Applies to most industries