AI in Customer Service: How it Works and Why You Need it

For many companies, artificial intelligence (AI) technology has completely changed the game for providing increased efficiency, especially when it comes to customer service. For instance, thanks to AI, Xfinity customer service has been able to make itself available to its customers around the clock. Another example can be online e-commerce where users receive relevant suggestions based on their current and previous purchases, and that is all made possible with the help of AI.

Customer support that is powered by AI provides a better user experience to your customers. On the other hand, for a company implementing AI in customer support means improved online customer experience, bringing about better retention rates, sending out an excellent brand image, providing efficient preventive help, and bringing an increased generation of revenue. And this is how AI in customer support will benefit the company.

How AI Works

Artificial intelligence is a classification of a variety of technologies. When it comes to customer service, the two AI technologies we usually refer to are natural language processing (NLP) and machine learning (ML).

Machine Learning

ML is an AI segment that processes a large amount of data and extracts insights from that. It specifically uses an algorithm to perform a specific action by recognizing patterns from previous data and making predictions on new data.

For instance, the interaction between a customer and support staff creates an enormous volume of organized data that ML can process and analyze to provide a response to the customers. This is where NLP comes in.

Natural Language Processing

NLP helps the machines to be able to understand spoken and written texts.

Chatbots like Siri and Alexa use NLP to understand and interpret what the user is saying and then provide them a response accordingly.

Why You Need It for Customer Service

Now that you understand what approaches are used by AI in customer support, you now need to start implementing it in a variety of ways;

For Categorizing Support Tickets

That’s possible with automatic tagging tools. It means that you can add labels to the data so that you can structure and then process it easily. You can tag the tickets according to various niches.

For instance, you can tag the tickets according to the features they have i.e. urgent queries, routine queries, need more info, can’t provide, and need an external specialist. That way the ticket is then analyzed and categorized according to their specific features and it also helps your team understand what’s bothering your customers.

For Performing Analysis on Customer Feedback

AI can analyze open-ended responses in customer surveys; it can either categorize them as positive or negative.

But with the help of AI-powered sentiment analysis, you can learn which of the customer experience has the biggest emotional effect on your products or services. For instance, AI can help you uncover that users are not happy with one of the core features offered in one of your products. That way you can prioritize and work on the feature based on the feedback you have received.

For Analyzing Texts

You can also use AI’s help to analyze texts such as customer support queries or reviews of your competitors. Again you need to set up tags here as well.

These tags can be categorized as complaints, questions about the products, competitors, content performance, requests, etc.

Regardless of the name, AI is powerful enough to recognize underlying moods, purpose, and urgency of the customers’ request, or any texts there may be. AI examines the content and then provides them the tags you have assigned for each particular content.

For Chatting with Customers

This is where you can implement chatbots to answer the basic questions and requests put forward by your customers. It can include product/service information, delivery time, order status, balance inquiry, etc.

With the help of chatbots, your customers receive answers quickly and simply. AI-powered chatbots also enable your human support agents to focus on more complex issues, and overall reduce operating expenses.

For Providing Multilingual Support

Now you don’t need to hire support that is familiar with multiple languages. Instead, you can use automation tools to detect the languages of your customers and then provide a response accordingly.

Selling to international clients increases your prospects of attracting and retaining a wide variety of customers. They can be transformed into brand supporters just because they have been enjoying your products or services in the language of their preference.

Wrapping Up

There you have it; using AI for customer support can literally save expenses for your company and improve customer service. AI makes providing customer service seem easy and provides a more efficient and smarter insight into what your customers want from your brand.

Hence, when customers are happy with the experience they are getting from your brand, they become brand advocates and help to boost the reputation of your company.