Sentiment Analysis

Pratama’s sentiment analysis solutions help businesses understand how customers feel and why.

Using a blend of machine learning, natural language processing (NLP), and on-the-ground human research, we interpret feedback from reviews, social media, and direct engagement.

Core Features

• Human Analysis
  Non-biased, cultural-contextual insight via local experts

• Text Analysis
  NLP tools parse emotion and opinion from unstructured data

• Sentiment Categorization
  Classifies text as positive, neutral, or negative

• Emotion Detection
  Maps feelings like anger, joy, or frustration

• Aspect-Based Sentiment
  Ties reactions to specific product or service attributes

• Multilingual Support
  Captures sentiment in native languages for global reach

Benefits

• Improved Customer Service:
  Sentiment analysis helps your business to identify and address customer complaints, leading to enhanced customer satisfaction and loyalty.

• Competitive Advantage:
  By understanding customer sentiment, your business can differentiate themselves from competitors and make data-driven decisions.

• Informed Product Development:
  Provides valuable insights for product development, enabling businesses to create products and services that meet customer needs and preferences.

• Risk Management:
  Identify potential issues and mitigate risks by addressing customer concerns promptly.

• Data-Driven Decision Making:
  Actionable insights, enabling businesses to make data-driven decisions and optimize their strategies.

Applications

• Customer Feedback Analysis:
  Analyze customer feedback from reviews, surveys, and social media to identify areas for improvement.

• Social Media Monitoring:
  Track customer sentiment on social media platforms to respond promptly to customer concerns and maintain a positive online reputation.

• Product Development:
  Use sentiment analysis to inform product development and ensure that new products meet customer needs and preferences.

• Customer Retention:
  Analyze customer sentiment to identify at-risk customers and develop targeted retention strategies.