Ask any business leader and they will stress why exceptional customer experience (CX) is the highest priority for any business regardless of industry. While it is crucial to attract new customers but maintaining customer loyalty is a more prominent position in any space be it in the world of online retail, software or technology or travel and tourism.

The AI Customer Service tool not only revolutionizes customer service, it also increases brand loyalty and customer loyalty. Companies operating in the B2C sector are now more likely to embrace automated customer support thanks to tools such as AI-powered bots that can help them provide customer service. What is automated customer support and what is the role of AI in enhancing the customer satisfaction? This topic will be explored with industry use cases in the sections that follow.

Obtaining Feedback from customers using AI

As a business How do you get effective client feedback by using AI-powered tools? These are only a few examples of AI-powered applications:

Analysis of sentiment

Customer feedback is a great way to study the mood of customers and offer insight into how customers view your business. Text analytics using AI can gauge and categorize the feedback into positive neutral, negative, or negative. NLP is a tool that can classify words in a comment together and extract the relevant insight.

Furthermore, CX metrics like Net Promoter Score (NPS) or Customer Effort Score (CES) are effective indicators of the general customer sentiment and their perception of the business.

Here's an example of NLP-based analysis of customer preferences:

Text analysis

The analysis of text of customer feedback is a form of qualitative analysis where you can analyze your customers' sentiments and feedback with an elaborate model. AI-powered text analytics tools analyze comments from customers on feedback forms. They determine the sentiment by using some keywords.

Here are some examples of terms that are frequently used in the banking and finance sector.

Text analysis could make use of a set of words to offer business insight. If the customer's comment uses the words of a mixture (costs or expenses, as well as monthly) and monthly, it could be deduced that your monthly expenses are too high for most customers.

Analytics for customer service

Customer service analytics (or CS Analytics) is an effective way to analyze every aspect of CS and determine ways to improve efficiency and cut expenses. An example of CS analytics by using customer service automation. It is a valuable source of customer conversations which could be utilized to evaluate metrics like the rate of retention and satisfaction rate, as well as goal completion rates and customer satisfaction. Other kinds of CS analytics include advanced call analysis and customer review analysis that can improve customer satisfaction and operational efficiency.

Customer feedback is categorizes with machine learning

Among the leading implementation of machine learning for customer feedback, machine learning algorithms can be used to categorize customers' feedback on the basis of common feedback points such as:

Price and quality

Customer service quality

Delivery of goods

Online availability

Companies can utilize categorization in order to understand how customers perceive the products and services you offer. It also helps to identify common issues to be addressed. Tags that are predefined can be used to automate categorization which makes it easier to handle the large amount of feedback from customers.

Customer reviews

Machine learning techniques that are used in customer reviews could be used to analyse product reviews and categorizing them as either positive, negative, or neutral. Review analysis of product reviews with machine learning may be used to determine:

Find out what your customers love and don't love about your product.

Conduct a detailed analysis of your product reviews to the reviews of your competition.

Gain 24/7 real-time insights about your latest products.

Quickly understand the sentiments and general feedback on your latest product. Get a quick overview of the overall feedback about your.

Conclusion

In any competitive business environment being attentive to customers and solving their problems is the only way for businesses to keep customers and increase loyalty. The growth of artificial intelligence customer service has enabled the company to collect and analyze customer feedback for more valuable and actionable information.