5 Ways To Use AI For Sentiment Analysis

Implementing AI sentiment analysis is a unique opportunity to automate the work of your customer support team. It allows you to increase loyalty and customer satisfaction, know your customers better, and predict future market trends more accurately. According to IBM, about 25% of large businesses in the United States already use artificial intelligence and see significant productivity increases. Do you want to join them? We will tell you how to conduct sentiment analysis using AI and choose the best tools. 

What is AI Sentiment Analysis

AI sentiment analysis is the use of machine learning and natural language recognition technologies to identify, highlight, study and quantify elements with a specific emotional coloration. It differs from manual information processing by a high degree of automation, as artificial intelligence groups and classifies such text elements and generates reports for making appropriate management decisions. 

Most often, sentiment analysis involves identifying a person's general mood: positive, negative or neutral. This will help you choose the most appropriate communication tactics and take the necessary actions to retain the client. Modern technologies also allow you to get more detailed information:

• identify specific emotions, such as anger, joy, disappointment, approval, sadness, etc;
• identify the aims of specific messages, such as a desire to buy a product, get additional information or unsubscribe;
• Identify specific features or components of products the message relates to;
• identify positive or negative features of the products mentioned by a customer, such as design, functionality, usability, etc. 

For customer sentiment analysis, AI technology is used. Artificial intelligence independently creates classification rules when processing a large amount of information. Its efficiency increases with each new text fragment. Studies show that AI has an average accuracy of 85%, while the accuracy of manual data processing does not exceed 70%. 

How is AI Used For Sentiment Analysis: 5 Ways

Artificial intelligence is a rather flexible technology that can be easily adapted to the needs and specifics of particular companies. This makes AI for sentiment analysis useful in the following ways. 

1. To identify the emotional coloring of reviews

To assess the emotional coloring of reviews, you need to take the following steps.

• Collect feedback. Include a request for feedback in your post-sales emails or collect feedback via messengers, social media or Claspo widgets. The latter can independently collect reviews of site visitors or redirect them to unique pages and third-party platforms. 

• Process. At this stage, you can connect an AI tool to assess customer sentiment and analyze and parse texts into small details, just like a teacher checking the dictations of schoolchildren. The tool will generate detailed spreadsheets with structured data and summarized reports that will be useful for direct employees and management. Examples of suitable platforms include OpenText, RepuState, Lexalytics and others. 
• React. Having information about the emotional coloring of responses on specific product characteristics, company specialists can write responses themselves or entrust this task to chatbots.

2. Identify the best and worst features of products

This analysis will be useful for developers or UX specialists. This information will help improve the quality of the product for the user. It can be done using the following algorithm:

• Conduct a survey. This can be done using newsletters, polls on social networks or popups. To create a survey using a popup, create pop-ups with information collection forms.
• Perform an in-depth analysis. Entrust artificial intelligence with a more detailed analysis. It will help you identify specific phrases and sentences associated with certain emotions. Parsing them into parts, AI selects keywords and calculates their frequency in a particular message or the entire data set. This allows you to find out what exactly your customers are talking about, such as whether they don't like the design or are not satisfied with the functionality of the latest mobile app update.
• Make a decision. With such insights, you can determine all the factors that should be considered when updating or improving a product or service. Artificial intelligence can also determine problem-solving priorities for developers and provide management with customer expectations data — lists of functions and design features that your products lack. 

3. Identifying market trends

AI can also work on a more global scale. You can use it in the following scenarios:

• Do your research. Artificial intelligence can help you identify products that can earn you significant amounts. Usually, an increase in sales is preceded by a surge of interest in certain products on social networks and online media. It is very difficult to track it on your own — you will have to spend all your working time monitoring popular posts. But AI can easily handle this task by processing hundreds of pages in a few minutes. It will identify current trends and make recommendations for you: which products you should pay special attention to, which to consider if possible and which to avoid at all costs. 
• Simulate. To be the first, you have to be the best. By choosing a specific business, you can track all mentions of certain products and identify their characteristics associated with the strongest emotions. This will help you not just go through trial and error but bring products that perfectly meet consumers’ expectations to the market. 
• Get insights during the sale. Artificial intelligence will also help you at this stage, analyzing feedback and enabling you to adjust your marketing campaigns on the go. An example of successful product promotion following the trend is Adidas and Kanye West's joint campaign, which earned more than $1.2 billion (!) on Yeezy sneakers in 2022. 

4. Monitoring brand reputation

To find out exactly how your target audience perceives your company, follow these instructions:

• Start searching for information. According to Help Scout, one complaint equates to 25 dissatisfied customers who simply keep silent about their negative experience with a business. Most of this audience will never contact the company directly to avoid conflicts. However, they are willing to share their opinions on other platforms: social media, review aggregators, blog comments, etc. Artificial intelligence will help you find out where your company is being discussed. 
• Analyze the data. AI tools for customer sentiment analysis can sort reviews by tone and emotional coloring. They will associate certain emotions with the company name, brands, specific products, or even product characteristics. 
• Launch PR campaigns. Using the proportion of positive to negative in consumer sentiment data, you can develop your own communication tactics. The world-famous Hilton hotel chain uses this strategy to contact dissatisfied customers within 13 minutes after a negative review is posted online. 

5. Track employee sentiment

AI can collect data not only from outside but also from within the company. You can use it in the following ways:

• Change the platform. To use artificial intelligence to optimize your HR policy, you just need to shift its focus from customer feedback to work chat messages. There are no confidentiality violations — we're talking about analyzing business communications.
• Identify problems. Analyzing the tone of correspondence allows you to receive timely information about internal conflicts between specific employees, dissatisfaction with salary, working conditions, or work complexity, and corporate ethics violations.
• Take the necessary measures. You can transfer employees to other departments or projects, make them individual offers, issue warnings, or limit their authority. 

Best AI Sentiment Analysis Tools

There are lots of web services with this kind of functionality. We strongly recommend the following platforms: 

1. Clarabridge

This AI sentiment analysis service is capable of working with 11 factors of review grouping. It takes into account emotional coloration, references to specific products or their characteristics, industry, and even customer demographics. 

One of the service's advantages is its ability to analyze the context. When it comes to a laptop, it will mark the word "lightweight" as a positive characteristic, and when the review is about winter shoes, it will mark it as a negative one. The subscription price is individual for each client. You can request a free demo or test social media monitoring tools for 14 days. 

Clarabridge's sentiment analysis gives you fertile ground for building marketing hypotheses. For example, if Clarabridge finds that most positive reviews are related to a specific product feature, perhaps focusing on that feature in your advertising campaigns will help you increase sales. You can validate such hypotheses with the help of Claspo.

With Claspo, you can easily conduct widget A/B testing, which means checking which offer, message, design, and even the color of the call-to-action button brings you the best results. The main thing is to think through the hypotheses carefully and consistently approach each experiment. Since we at Claspo regularly check our own assumptions, we have prepared a universal template with the critical stages of conducting A/B testing. It will help you competently put any theories into practice and get meaningful results for your business. And yes, it is suitable for any experiments, not only those related to widgets.

2. Repustate

The platform is attractive because it can work with 17 different languages. For each of them, the program chooses its own approach, taking into account the peculiarities of vocabulary, grammar and punctuation. This significantly improves the accuracy of AI sentiment analysis. Meanwhile, Claspo widgets can dynamically change languages depending on the user's browser language or the language selected on your website. So, if you conduct surveys with Claspo, you can collect more feedback from visitors from different countries, transfer more material to Repustate for further analysis, and get more valuable insights.

Another of Repustate’s advantages is the ability to determine the strength of emotional coloration. Thanks to this, artificial intelligence highlights sentences and phrases that require special attention from the person in charge. 

Subscriptions start from $99 per month. A 14-day trial period is available.

3. OpenText

This AI sentiment analysis service is available in a package offer that includes marketing tools and cloud-based digital asset management tools. The platform allows you to switch between analyzing specific sentences, documents (reviews), and topics in general. The service automatically groups the collected information and draws conclusions about customer sentiment — in general or individual cases. 

The subscription cost is determined individually. If you sign a contract for one year, new users get three months of access to the tools free of charge. 

4. ParallelDots

This web service uses proprietary algorithms to determine the tone of customer appeals based on Long Short-Term Memory (LSTM) technology. It offers different approaches to analyzing texts in reviews, social media and mainstream media, which significantly increases its accuracy. Another advantage of the platform is its very simple design. It is easy to work with, even for people who have never worked with AI tools before.

Subscriptions start at $79 per month. There is a free version with a limited number of queries and no access to the API. 

5. Lexalytics

This comprehensive marketing analytics platform not only determines the tone of appeals but also uses it to forecast product demand and changes in retention and churn rates, making it a huge help in planning advertising campaigns. With this knowledge, you can modify your strategy promptly. For example, launch a widget to promote a particular product when demand is predicted or announce special offers for customers and users when the risk of churn is high.

The main advantage of the Lexalytics service is its full vertical integration. By uploading raw data, you get both reporting and ready-made templates for making management decisions. 

The cost of the subscription is discussed during the demonstration. Most customers can expect a short trial period of up to 14 days.