How AI Can Improve Call Center and the Customer Experience

Artificial intelligence (AI) is becoming increasingly prevalent in the business world, with ChatGPT-4 generating a lot of buzz due to its ability to generate true-to-voice content and images in an instant. While most people are focused on how this technology will impact branded writing or copyright materials, marketing isn’t the only department that can benefit from AI. In fact, AI can be used to improve  the customer experience, particularly in contact centers.

In this article, we’ll take a look at how contact centers can use generative AI and other AI-based analytics programs to improve the customer experience.

What is Generative AI?

Generative AI refers to programs that use digital neural networks and deep learning algorithms to create new content, such as website copy, books, or scripts for customer support teams.

Generative AI isn’t the only tool that can benefit call centers; there are also AI-based analytics programs, for example, that can offer invaluable date insights. AI tools have a number of valuable features and use cases, including within call centers.

Benefits of AI in the Call Center

The benefits of using AI in contact centers are numerous and varied ⎼ and are evolving nearly daily. As different types of AI tools have a large array of unique features that can benefit businesses. Here are some examples:

• Call sentiment tracking: This involves assessing a customer’s attitude, emotions, opinions, and objections around the brand, product line, marketing campaigns, and overall customer experience.
• Keyword tracking during conversations: This involves monitoring for keyword patterns to see what users are discussing most frequently and what they’re saying regarding certain key phrases.
• Accelerated script writing: This can be used to create scripts for different scenarios, ensuring contact center staff are never caught unprepared.
• Quick responses to simple questions: This can be used by contact support teams and chatbots to address customer needs quickly.
• Transcribing audio calls into transcripts: This can be used to analyze call center performance, opportunities for training, and customer sentiment.
• Machine learning: This provides relevant suggestions to customers and employees, helping them find the solution, product, or service that they need faster.
• Natural language processing: This trains these systems to understand language as humans do and can be vital for creating translations across different languages to better service more customers.

Here, are some real use cases that demonstrate how call centers are using these AI features to improve the customer experience:

Use Cases

Tracking calls to provide feedback and growth opportunities:

AI can transcribe audio files into text quickly and affordably, allowing managers to assess their team’s performance and address common customer concerns.

This enhances team functions and can help better support customers’ needs, leading to a better customer experience with every call.

Assessing customer sentiment:

AI tools that analyze call sentiment can track a customer’s attitude, emotional response, stated concerns, and their opinion about the brand, call, product, and solution.

Tracking this information is invaluable. Ongoing customer frustration— both regarding your experience with the brand or even their phone support experience— will result in high churn rates and lost customers.

Using call sentiment tools to review “problem” calls with unhappy customers can help you flag potential problems and obstacles throughout the customer journey so you can rectify them before they drive away more clients, meaning more happy clients long-term.

Looking for patterns using keyword tracking:

Keyword tracking can help identify potential issues that may be driving customers away or preventing them from making a purchase.

It’s extremely common for customer support staff to hear the same problem popping up over and over. Having quick access to this information means the problems can be resolved right away. The customer who called will be happy to have a solution, and it will also improve the overall customer experience by preventing the issues from impacting additional customers.

Providing preemptive support to reduce calls:

Providing customers with multiple options to reduce the need for them to reach the call center can improve the customer experience significantly.

1. Setting up advanced chatbots that can answer basic questions about your brand, product, service, or the customer’s orders; AI makes chatbot programming (and the chatbot potential) easier than ever.
2. Writing an extensive volume of help or support articles, with help from the product team, to address commonly asked questions.
3. Sending AI-generated emails to customers after a purchase with a link to the support knowledgebase.

The customer is then likely to have shorter wait times, which is significant since nearly two-thirds of customers do not wait longer than two minutes on hold; long wait times directly impacts their experience.

Creating diverse scripts for team members:

AI can be used to create a large number of diverse scripts for contact center team members, enabling them to respond in a more personalized way to customer queries.

Customers are not all the same, and when you’re working in a call center, it’s likely that you’ll hear something new every day. It’s common for customer support workers to regularly hear scenarios they’ve never heard before, and knowing how to respond and solve the customer’s problem in a more personalized way can be a game-changer for improving the customer experience in a big way.

Pros and Cons of AI for CX

The five use cases discussed above may have you ready to sign up for AI tools right away. Before you do though, it’s important to weigh the positives and the negatives of this technology— and understand its limitations.

Pros

It’s fasterthan doing the work manually.

It’s relatively easy, as long as you know how to use the tool and how to ask it for what you need (though there is a fairly significant learning curve here).

It can be cost-effective, compared to hiring full-time or freelance experts.

It can save time, which in turn can save money.

Cons

While the pros are highly appealing (and why generative AI is being discussed so much), there are real cons to using it, too:

It still requires major oversight.Multiple users have caught ChatGPT creating low quality content, and others have found that it’s prone to inaccuracies, not understanding nuance, or even making up statistics. This could be a disaster.

You need to know how to use it. You need to learn how to ask the tool what you want and hope it creates the desired end result. Sometimes it can, sometimes it can’t.

There are privacy and security concerns.There are a number of different potential security issues relating to generative AI, and some can directly impact businesses— including the fear that the information you give the tool may not stay confidential. There are also concerns around the fact that it may not be fully compliant with privacy practices.

It can’t truly create anything original. This may or may not be an issue when using AI for customer service, at least not to the degree that it would be with content writing or copywriting, but AI only recreates what’s already out there.

Final Thoughts

While AI can certainly help to improve the customer experience, it’s not an all-encompassing solution by itself. The human element of customer service will always be critical and cannot be replaced.

That said, using AI strategically alongside a strong telecommunications partnership offers massive scalability potential. Testing it out to see how it works for your business and your workflow won’t hurt!

Looking for help from a telecommunications partner? Learn more how TelWare can help with your business communications.