AI Sentiment Analysis

AI sentiment analysis system can provide valuable insights for businesses and organizations looking to improve customer understanding, increase efficiency, gain a competitive advantage, manage risk, and save costs.

  • 7% Improvement in Accuracy.
  • 16% Improvement in Marketing Effectiveness.
  • 14% Improvement in Customer Satisfaction

Business Implementation

One study published in the Journal of Artificial Intelligence Research found that an AI-based sentiment analysis system could accurately determine the sentiment of tweets with an accuracy of around 85%.

Another study published in the Journal of Business Research found that an AI-based sentiment analysis system could accurately determine the sentiment of customer reviews with an accuracy of around 90%.

A study published in the Journal of Computer Science found that AI-based sentiment analysis systems performed similarly or better than human annotators in determining the sentiment behind a text.

AI-based sentiment analysis uses natural language processing (NLP) and machine learning algorithms to determine the sentiment or emotion behind a piece of text. This can include analyzing social media posts, news articles, customer reviews, and other forms of written communication. Sentiment analysis can be used for various applications, such as gauging public opinion about a particular topic or product, identifying potential issues with a company's customer service, and tracking brand sentiment over time. The effectiveness of sentiment analysis can vary depending on the quality of the data and the specific algorithm used. Still, it can be a valuable tool for businesses and organizations looking to gain insights from large amounts of unstructured text data.

An AI sentiment analysis system can provide several benefits for businesses and organizations looking to gain insights from large amounts of unstructured text data.

  • Improved customer understanding: AI sentiment analysis can be used to analyze customer feedback and reviews, providing valuable insights into customer needs, preferences, and pain points, which can improve products and services.
  • Increased efficiency: Automating the sentiment analysis process can save time and resources compared to manual analysis, allowing organizations to process large amounts of data quickly and efficiently.
  • Competitive advantage: By using AI sentiment analysis, businesses can gain a competitive advantage over others who do not have access to such advanced tools.
  • Risk management: AI-based sentiment analysis can also help organizations identify and mitigate risks related to public perception of their products or services.
  • Cost-effective: AI-based sentiment analysis can be less expensive than traditional methods, making it a cost-effective solution for small and medium businesses.

Overall, an AI sentiment analysis system can provide valuable insights for businesses and organizations looking to improve customer understanding, increase efficiency, gain a competitive advantage, manage risk, and save costs.

Tech Implementation

Case Study

AI Sentiment Analysis for retail

A retail company wanted to gain insights into customer sentiment regarding its products and services. Attri’s Blueprint for Sentiment Analysis analyzed customer feedback from various sources, including social media, review sites, and email, and classified feedback automatically into positive, negative, and neutral sentiment categories.

The company used our model and experienced

  • 94% Accuracy in Sentiment Detection.
  • 10% Reduction in Resource Expenditure.
  • 21% Improvement in Customer Satisfaction.

AI Sentiment Analysis for retail

A retail company wanted to gain insights into customer sentiment regarding its products and services. Attri’s Blueprint for Sentiment Analysis analyzed customer feedback from various sources, including social media, review sites, and email, and classified feedback automatically into positive, negative, and neutral sentiment categories.

The company used our model and experienced

  • 94% Accuracy in Sentiment Detection.
  • 10% Reduction in Resource Expenditure.
  • 21% Improvement in Customer Satisfaction.

AI Sentiment Analysis for retail

A retail company wanted to gain insights into customer sentiment regarding its products and services. Attri’s Blueprint for Sentiment Analysis analyzed customer feedback from various sources, including social media, review sites, and email, and classified feedback automatically into positive, negative, and neutral sentiment categories.

The company used our model and experienced

  • 94% Accuracy in Sentiment Detection.
  • 10% Reduction in Resource Expenditure.
  • 21% Improvement in Customer Satisfaction.

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