Email Analytics

od: Inference Labs Private Limited

Email Analytics to analyze your incoming and outgoing mails and improve your CSAT scores

In today's fast-paced and hyper-connected world, effective communication is more important than ever. That's why we've developed an innovative solution to help you better understand your customers' needs and improve your communication: Email Sentiment Analytics. Our powerful AI-driven platform uses cutting-edge algorithms to analyze the sentiment of your email communications, providing you with the insights you need to optimize your messaging and improve customer satisfaction.

What is Email Sentiment Analytics?

Email Sentiment Analytics is a data-driven approach to understanding the sentiment of your email communications. By analyzing the language, tone, and other factors in your emails, our platform helps you identify patterns and trends in customer sentiment, so you can adjust your messaging accordingly. This approach enables you to deliver more personalized and effective communications, improving customer satisfaction and driving your business forward.

Key Features: Our email sentiment analytics platform is designed to be intuitive, easy to use, and fully customizable to meet your unique needs. Key features and capabilities include:

  1. Sentiment classification: The ability to classify emails into positive, negative, or neutral sentiment categories based on the language and tone used in the email.
  2. Entity recognition: The ability to identify specific entities mentioned in the email, such as product names, brand names, or locations to help businesses understand what products or services are being talked about in customer emails.
  3. Emotion detection: The ability to detect emotions expressed in the email, such as anger, frustration, happiness, or sadness to help businesses understand the emotional state of customers and respond appropriately.
  4. Topic extraction: The ability to extract the main topics discussed in the email to help businesses understand the specific issues or topics that customers are concerned about.
  5. Trend analysis: The ability to identify trends and patterns in customer sentiment over time to help businesses track changes in customer sentiment and make informed decisions about how to respond.
  6. Data visualization: The ability to present sentiment analysis results in a visual format, such as charts or graphs to help businesses quickly understand the sentiment of customer emails and make decisions based on the insights gained.
  7. Integration with email platforms: The ability to integrate with email platforms, such as Gmail or Outlook, to automatically analyze incoming emails. This can save businesses time and effort by automating the process of sentiment analysis.

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