Does Generative AI Have a Role to Play in Enhancing Customer Experience?

Chatbots are the flagship use cases of AI in customer service and support scenarios. Businesses have started using chatbots even before Large Language Models (LLMs) became mainstream.

Most chatbots in those days were rules-based, which was frustrating.

Let me give you an example.

This was a spa website, and I was looking for the offers of the day. When I click on chat, it asks me to input my name, email, and mobile number. After that, I was asked to choose the city from a pull-down menu. Then, it threw up the address of their branches and asked me to choose the one closest to where I live.

Once all this is done, they will tell you the offers they have for the day. Then, I had to choose one of the offers, and they would try to fix an available slot for me. Most often, the slots that I ask for will not be available at the branch closest to me.

The entire conversation thread is a waste of my time, except perhaps the fact that my details are added to their marketing database.

So, the next time when I visited them, I got smarter and typed my name, email, mobile number, the city I was from, and the branch that was closest to my place, and asked them for their offers.

As this was a rule-based engine that I was talking to, it asked me to input my name, email, and mobile number. I had to go through the entire process again.

Then, you also have keyword-based engines that act upon specific keywords that a user inputs. It matches keywords in a user’s question with the text in your knowledge base articles.

Since then, chatbots have come a long way, and with the use of Generative AI, it has become far more intelligent.

I have seen cases where chatbots are used with the goal of deflecting customer inquiries from the agents. The focus is on avoiding support tickets and not providing exceptional customer experiences.

How Are Organizations Using Generative AI Today?

Chatbots are one of the first use cases for Generative AI that every organization is implementing or is in the process of implementing.

We will see chatbots powered by Generative AI deal with routine queries besides providing personalized and instant responses to customer queries.

The routine queries can be:

• Shipment schedule, change of shipment schedule, or requesting priority shipping
• Booking, confirmation, rescheduling, and cancellation of appointments
• Enhancement and cancellation of subscriptions
• Account balance, last five transactions, and stop check payments on your bank accounts
• Seeking invoice details and bill breakups
• Assistance in password change or pin generation

Chatbots powered by Generative AI can intelligently handle many such routine queries. With the assistance of LLMs, chatbots can have conversations that are close to being as dynamic and flexible as those of humans.

What About Knowledge Bases?

The biggest issue with self-service platforms is that the support knowledge base is not kept updated. People don’t make the effort to keep them updated regularly, as they have other KRAs to meet.

Generative AI can help build and maintain support knowledge bases.

They can automatically keep the knowledge bases automated with the good practices and resolutions provided.

This will ensure that human agents will always have access to the most current information and insights.

What About Analytics?

Imagine the amount of data that you generate as a customer service or support function. You would be generating terabytes of data every day – voice and text.

What do you do with them?

Only 2% of the stored information is analyzed for anything meaningful, while the remaining 98% resides on your storage servers for compliance issues.

With Generative AI, you can run analytics on all of this stored information and gain unparalleled insights like understanding sentiments, reading between the lines, misselling, and compliance issues. This will act as an input on agent training.

How About Automated Responses to Support Emails?

You cannot send an automated mechanical response to support emails. It has to be contextual and personalized. With LLMs, you can draft personalized and automated responses that carry a consistent tone while providing relevant resolutions to customers.

How About Proactive Customer Service?

Predictive analytics powered by Generative AI can play a huge role in ensuring exceptional customer experiences.

For instance, if a set of customers are having an issue accessing a particular service in your offering, predictive analytics can pull that information and send a proactive message to all other customers about that service’s unavailability for a specified period.

This would remove surprises completely, and you would have Generative AI to thank for that.

Artificial intelligence, coupled with human intelligence, will play an important role in enhancing customer experiences.

While AI will help automate several routine tasks, the assistive role that it plays for human agents would have the biggest impact on enhancing the customer experience.

AI would open up numerous possibilities for engaging customers.

So, take a pause and stop worrying about AI taking away jobs. It is only going to open up more opportunities and make humans more relevant in the customer experience space.