Suppose you are running a business and receiving 20 emails daily from customers sharing their experience with your product or service. In that case, it might be a good idea to read those emails by yourself to make the necessary amendments and corrections and enhance the quality of offerings. However, if we increase that number of emails to some thousands, the idea might not seem feasible. So, you need a tool that can read those thousands of emails on your behalf, assess the negative and positive feedback of the customers, and give you an overall insight into their experience. That’s where AI sentiment analysis walks in with its new capability of understanding the emotions of texts based on certain algorithms. Let’s understand this concept and how AI sentiment analysis benefits your business with different use cases. 

What is AI Sentiment Analysis?

AI Sentiment Analysis

AI-based Sentiment Analysis, more popular as opinion mining and sentiment analysis, is the new concept in artificial intelligence that uses natural language processing and machine learning to understand the tone and emotions of any text or vocal speech. This technology understands and assesses the group of words and helps it understand whether the comment is positive or negative. Natural language processing and machine learning carry the extensive dataset for the training and labeled datasets. 

At the same time, AI sentiment analysis even allows identifying the patterns and associations between words, sentiments, and phrases to provide a clear insight into what the user wants to say or convey. In this new concept, the system first processes the text data to eliminate unnecessary information and focus on more meaningful texts. It then processes relevant features into a numerical representation called extraction. Based on the trained dataset and algorithm, the system uses this data to understand emotions.

AI-based Sentiment Analysis- Relevant Statistics

Here is a glance over the use of sentiment analysis technology worldwide to benefit their business and enhance product and customer satisfaction.

  • According to Bain&Company, 54% of the companies around the world have adopted the AI-based Sentiment Analysis technology as of 2020, which is expected to exceed 80% by the end of 2023.  
  • This new technology has been identified to have 85% accuracy in assessing speech emotions, which is higher than any other method available in the market to analyze speech tone.
  • According to Forbes, 86% of customers are willing to pay more for a good customer experience and personalized treatment. 

So, the use cases of AI sentiment analysis among businesses worldwide have only increased, allowing them to provide a better customer experience and service to their customers. 

Types of AI Sentiment Analysis

There are four types of AI-based sentiment analysis- 

  • Intent-based Sentiment Analysis 

While the other types of sentiment analysis applications identify the tone of texts, this NL task goes well beyond it. This type of sentiment analysis focuses on the degree of extent to which the emotion of the speech is expressed in the text. For example, it entails gauging if the text presents a complaint, command, query, desire, and other speech factors. Industries like healthcare, legal, human resources, marketing, and advertising mainly use this type of sentiment analysis.

  • Aspect-based sentiment analysis 

Users employ aspect-based sentiment analysis when conveying a specific message that can be positive, negative, or neutral through a particular part of the text. This more detailed version of traditional sentiment analysis helps extract the users’ opinions. For example, this type of sentiment analysis are to understand the likes and dislikes of customers regarding the quality, price, or design of the product. 

  • Emotion detection 

As the name suggests, this is the natural language processing application used to identify the information about emotions expressed in the form of text. This NLP concept focuses on understanding the more emotional aspect of the writer, easily detecting various emotions like anger, fear, happiness, and surprise. Studying customer feedback with this technology makes knowing about their emotions associated with your product or service even more effective. Businesses can easily know how their target audience feels about their products. 

  • Fine-grained sentiment analysis 

Fine-grained sentiment analysis focuses more on using the lexicon approach and delving into the sentiments expressed in the text. Based on intensity, targets, and emotions, it focuses on identifying customers’ sentiments. AI-based sentiment analysis utilizes this type of analysis for political analysis, product reviews, customer feedback analysis, and news and media analysis.

Top benefits of AI sentiment analysis

Having gone through different types of AI sentiment analysis and their use in different industries. Let’s know about some benefits businesses can leverage using these innovative technologies. Here are the core benefits that you can enjoy with AI sentiment analysis tools- 

AI Sentiment Analysis Benefits
  • Product analysis 

The sentiment analysis tools significantly help understand the products by getting valuable insights. One can use the technology to actively listen to people’s viewpoints regarding the different aspects of the product, including performance, unique features, user behavior, functioning, and much more. Companies receiving daily customer feedback on quantity regarding the product or service can greatly benefit. This technology will read all the feedback and summarize what customers are experiencing and what to improve. 

  • Reputation management 

Every business has its reputation in the market associated with how the customer base perceives and sees its brand. Businesses like hospitality, tech companies, and clothing brands can greatly benefit by analyzing how customers think and then offering services in the market accordingly. Tasks like brand feeling surveillance, noticing specific feelings, and finding patterns and trends can be easily carried out with AI-based sentiment analysis tools. Additionally, these tools are adept at paying attention to influence individuals, enhancing their effectiveness.

  • Customer voice analysis

For any business, it is important to listen to their customers and take measures to enhance their experience with the brand. So, Voice AI sentiment analytics listens to what your customers say about your brand and product over different platforms and gives an overall report for the conclusion. Companies like TripAdvisor use AI-based sentiment analysis to entertain different feedback coming from customers over different platforms. 

Also Read – Top Artificial Intelligence Development Company

  • Reduces employee retention 

This is one of the significant benefits of AI sentiment analysis. Employees are the most important resources for the business, and sentiment analysis can be a great solution to enhance employee retention. By imparting this technology in the different communication mediums used by the employees, the organization can know if any employee is dissatisfied regarding any particular thing in the workplace, and thus, the necessary actions can be taken. 

  • Predictive analysis 

Predictive analysis is one of the biggest benefits businesses can leverage using AI sentiment analysis. By assessing the previous data and studying consumer behavior, businesses can predict future trends and make informed decisions. For example, predictive analysis can easily tell the demand for a particular product or service at a particular period in the market. Thus, making that particular product’s stock can bring a good profit for the business. At the same time, this benefit enhances the use cases of AI sentiment analysis to a great extent. 

  • Making the marketing strategy more efficient 

By assessing the customer response to a particular marketing campaign, you can remove the unnecessary practices from your marketing campaign and put more effort into the ones that affect the customers. This way, the sentiment analysis technology can also help you enhance your marketing strategy. 

  • Smart Targeting 

Using sentiment analysis, you can easily find out the happy customers of your brand and thus target them to increase your conversion rate. Similarly, you can find customers with good spending habits and thus increase the chances of purchase by targeting them more efficiently. 

  • Multiple customer handling 

While traditional chatbots can only support the FAQ format, the more advanced chatbot with AI sentiment analysis can understand customers’ emotions to provide a better solution. This will increase customer satisfaction and, thus, ultimately strengthen your customer base. 

Use cases of AI sentiment analysis across industries

Artificial intelligence has helped businesses of all industries to leverage different types of benefits and increase their productivity. Similarly, NLP and ML-based sentiment analysis technology is also important in different niches to enhance the customer experience and deliver competitive advantages to businesses. Here are the use cases of sentiment analysis across the industries- 

  • Retail industry

Deloitte, one of the biggest brands in the retail industry, has been using sentiment analysis technology to know how customers feel about their brand. By turning toward social media channels, review platforms and other digital means of customer communication, they focused on knowing how customers feel about their support services. Similarly, businesses in the clothing industry can also do wonders with sentiment analysis by knowing about the trends that are being encouraged by the customers in the market and thus providing the stock accordingly. 

  • Tourism and hospitality

Tourism and hospitality is the industry that can best leverage the advantages of sentiment analysis. When talking about transportation, restaurants, and hotels, there are a range of things that can disappoint customers at some time. Sentiment analysis makes it easier for businesses to know about the factors that have spoiled the customer experience and thus make the necessary corrections to enhance the customer experience in the future. 

  • Telecommunication 

Telecommunication is an industry that entirely depends on how well they handle their customers. Telecommunication businesses are the ones that have to handle the complaints, feedback, and demands of the users to the maximum extent. By implementing the sentiment analysis in the calling and messages portal, the system can easily identify the areas where the customers are mostly satisfied and dissatisfied. This will make it much easier for telecommunication businesses to know about their customers and make the decisions. 

Also Read – How Much Does It Cost To Develop AI Chatbot

  • Healthcare 

During training, sentiment analysis can help health professionals know where the trainees face the most problems. Similarly, the medical language is more complex than others, and thus, it can be of great use to know about the different types of health issues of the patients by training the machine learning and natural language processing model in sentiment analysis accordingly. 

  • Banking and Finance 

Financial institutions like banks and insurance companies can enhance their customer acquisition and retention strategies. By assessing the reviews and feedback on social media from the campaigns run by either themselves or their competitors, they can know customers’ pain points in leveraging financial services. So, financial institutions can streamline the process by learning from that feedback and making significant improvements. 

Best AI Sentiment Analysis Tools

There are different names in the market that represent the best sentiment analysis tools providing services to businesses around the world. By identifying the keywords based on predefined data sets and training data, these tools have claimed to have the highest accuracy to give the best results to the users. Here are the top 5 sentiment analysis tools being used by most of the audience- 



This is the AI sentiment analysis tool by Clarabridge that contains CX Analytics and CX Social. When scoring the content or information, this tool considers all the factors like grammar, context, industry, tone, sources, and much more. At the same time, it uses the 11-point scale that helps to index the sentiment of collected data. This is one of the best AI sentiment analysis tools that you can use to gather positive, negative, and neutral feedback.  



This sentiment analysis tool is part of the OpenText Content Analytics platform, which is specially designed to identify and evaluate the expressions of sentiments and subjective patterns of any speech or text. OpenText sentiment analysis takes the test on three levels: topic, sentence, and document. The tool can easily tell if the text is subjective or factual. At the same time, one can also use this tool to identify the customers’ positive, negative, and neutral tone in their mail, feedback, and requests. 



ParallelDots is the AI research group that provides the sentiment analysis tool. Besides this analysis tool, they have a range of other offerings, including products, plugins, and APIs. ParallelDots sentiment analysis API uses the Long Short-Term Memory algorithm that classifies the text as positive or negative. The tool is trained from the social media dataset and can handle formal and casual language. 



Lexalytics is one of the best choices when playing with big data and is concerned about information security. First, this tool uses natural language processing to break the sentence and evaluate semantics, syntax, etc. The second step comes with entity recognition, intention detection, and data categorization, which takes the sentiment analysis process to the next phase. In the third and final stage, the structured data and conclusions are transferred to the data visualization suite to make it easier for the users to understand the results.

Meaning Cloud

Meaning Cloud

AI sentiment analysis tool Meaning Cloud comes with a range of features like global sentiment (to study the general opinion given in the text), sentiment at attribute level (for sentiment analysis of each sentence), facts identification, irony detection, graduate polarity (to study the differences in sentiments), and agreement & disagreement detection. These features, when combined, make Meaning Cloud one of the best AI sentiment analysis tools. 

Final Opinion

Artificial Intelligence has always amazed the world with its innovative capabilities and use cases in different scenarios. Similarly, AI-based sentiment analysis tools help businesses know how their customers and stakeholders feel about the brand by assessing their texts, feedback, suggestions, and communication over different mediums. Businesses using this technology to understand their customer’s needs and preferences have experienced significant growth in their profit by taking the right steps. If you want to leverage the benefits of AI sentiment analysis tools in your business, Octal IT Solution is keen to be your partner in this new journey.

Managing Director

Arun Goyal is a passionate technology enthusiast and a seasoned writer with a deep understanding of the ever-evolving world of tech. With years of experience in the tech industry, Arun has established himself as a prominent figure in the field, sharing his expertise and insights through his engaging and informative blog posts.

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