What Is AI Engine and Do I Need It?

Although it doesn’t feel like all that long ago, way back in the 90s one of the most important factors to a call center’s success was the ability to route a customer to the right support agent with the IVR (Interactive Voice Response). Countless hours were spent identifying the most efficient call routing patterns and expert agent capabilities to ensure that your request reached the right person quickly. This technology is still widely used today and there are still teams in the largest companies programming IVR systems to accomplish pretty much the same goal.

As the standard for customer support evolved there have been many attempts to improve the function and the customer experience associated with IVRs to reduce hold times and provide more relevant support faster. Even today some companies will use their IVR system as a way to keep a customer on hold, rather than provide a solution, when agents are inundated with calls.

For those of us who’ve worked in the voice industry for some time, we’ve seen first-hand the attempts to accomplish a customer’s need before reaching an agent. First there was expert agent routing that delivered your call to the agent most qualified to help you. Then came advances in voice recognition, which today has evolved to be a very effective tool to increase containment rates and deflect calls from reaching a live agent. My two favorite examples of the power of voice recognition are Cox Communications and Capital One, two examples of great voice recognition and routing.

Our memory, however, is short. It wasn’t so long ago that we were all pulling our hair out punching digits into the phone or constantly repeating “agent”, “Agent”, “AGENT”, AGENT!!!!!”.

Whether it was a limit of computational power or the sheer cost of developing and implementing advanced call center technology, it took decades for phone systems to be able to front end the customer support process as efficiently as they do today. Thankfully we all survived to see it without boiling over from the hypertension usually associated with calling with a customer service department.

Bad customer experience is definitely not the case with Chat Artificial Intelligence (Chat AI). While we seem to hear about the shortcomings of Chat AI like the disconnected conversations and the robotic like responses, these experiences are usually the product of Chatbots with limited AI functionality or early stage deployments. The increases in both computational power and the massive advancements in machine learning are driving excellent customer experiences that improve over time.

When was the last time you heard of technology actually performing better, on its own, without a ton of additional development work or continuous updates? Well, that’s the case with Artificial Intelligence. Like a person, the more experience it has interacting with customers and information, the better it performs with little need to be manually improved or fine-tuned.

Today, AI Chat can be used to answer a large majority of customer requests and because Artificial Intelligence learns as it is used, customers prefer to interact through AI chat to avoid all of the frustrations commonly associated with calling a contact center agent. 

We’ve all seen the numbers and they tell us that customers are more likely to make a purchase if they’re able to speak to a representative at the time of purchase. Study after study shows that if you can prevent even the smallest percentage of customer defection revenues and profitability can literally skyrocket as much as 80%. Just as important, the faster is your service the better is customer experience.

The same can be said for customer support. More than 70% of customers say that responsive customer support providing fast, courteous, relevant and contextual answers to their inquiries are the most important factors in determining the quality of customer service and the likelihood of that customer doing business with the company in the future.

As our world becomes even more “on-demand” and global, providing around the clock sales and customer support is quickly becoming a key differentiator. Customer’s desire to do business with companies on their own schedule and terms are driving financial growth and customer loyalty across all sectors and industries. Companies that neglect this “always on” requirement not only lose out, but need to find ways to be competitive.

Unfortunately, only the largest companies have the financial resources to deliver 24x7 customer support and sales operations. Still many of the largest companies can’t justify the expense of building out and staffing a 24 hour contact center. While outsourcing to a BPO is always an option, statistics show a diminishing return for outsource customer and sales support operations.

As customers continue to drive up the use of chat and social communications for customer support and sales, along with the incredible growth in Artificial Intelligence technology, smart companies on the forefront of customer service now have the ability to offer around the clock service for a large portion of their customers.

Think about this: While the average phone support call has previously been measured at almost 6 minutes, the average chat session lasts just 42 seconds, indicating that the vast majority of customer support issues are simple and only require limited information in order to leave a customer informed and satisfied with the interaction.

Today Artificial Intelligence can deliver a personalized, informed, and contextually relevant response to just about any question related to most customer inquiries. Add on the fact that AI actually “learns” as it interacts with people and information and the value to the customer and the vendor actually increases over time.  Wouldn’t we all like to have immediate service with zero wait times and fast, courteous response that immediately addresses our needs? I know I would.

Implementing Artificial Intelligence for customer service comes down to an application cost that, when amortized over the number of chat or social sessions it can handle, reduces customer support costs to as little as 10% of traditional contact center and agent expenses.

The one objection to relying on Artificial Intelligence in the contact center is the customer experience. There’s enough bad press out there about Chatbots and broken, robotic responses that are sometimes irrelevant that some customer support professionals are wary of any form or automation. My response to that is, while those were valid concerns; just take a look at Siri today vs. 2 years ago. The quality of responses has dramatically improved, as has the customer perception and usefulness.

What are your thoughts about Artificial Intelligence in the contact center? We’d love to hear from you.