AI in CX, Quality Management and Contact Center Solutions: Why the Contact Center is Here to Stay

By Chrissy Calabrese, Vice President of Product Marketing at Playvox

AI in CX, Quality Management and Contact Center Solutions: Why the Contact Center is Here to Stay

To say that artificial intelligence (AI) has been written about frequently over the past year would be an understatement. There is probably one area where there are more expectations for AI than in customer experience. For many organizations, particularly in the telecom arena, contact centers are seen as cost centers, so those operating contact centers or holding support centers under their P&L are always seeking new ways to streamline costs in their business.

While recent studies show the expected growth and impact of AI over the next decade, there’s also potential for job creation. Most experts agree that customer service jobs will be augmented and automated, not replaced. Many believe that by automating mundane tasks, we’ll be more productive, efficient, and AI will enable businesses to provide better customer experiences with more self-service options and help fix employee burnout.

No matter what side you are on, the promise of AI is significant. In this article, we’ll discuss the history of AI being used in a contact center, how AI tools are utilized today, and the future of AI in improving CX.

AI in the Contact Centers: Looking Back to Look Ahead

Before we jump in and look at AI in customer experience today, it’s key to reflect and understand how AI has been previously used.

Workforce Management Solutions

Anyone who has worked in a service center for a long time is familiar with the teams of people, number of spreadsheets, and the hundreds of hours that have traditionally gone into creating schedules. There’s the initial analysis of determining when customer interactions come in (the hours when it’s the busiest), another analysis of which team members are available or not (noting special circumstances, when agents need to leave or any other schedule limitations), and then matching all this together to optimize schedules to deliver the agreed-upon service level agreements (SLAs) for response and wait times, and first contact resolution (FCR).

One of the early ways that AI was leveraged was to optimize all the previous steps via a modern workforce management solution (WFM). WFM solutions automate the entire process outlined above and consider the most accurate real-time data to produce a schedule for your agents that accounts for hours and number of people needed, and the differences in agent availability — to create customer experiences in accordance with agreed-upon SLAs. This process is all done using AI.

Chatbots

Another tool that’s been in use for a few years is chatbots. These AI-powered virtual assistants can provide immediate responses to customer queries, offer product recommendations, and even help troubleshoot. As chatbots continue to evolve, they can handle multiple customer conversations simultaneously, help reduce wait times, improve overall customer satisfaction, and transform CX at the contact center.

 Personalized Customer Experiences

Personalized customer experiences aren’t new, nor is the ability of AI to create these kinds of experiences. A few examples include:

Using AI to provide relevant article recommendations on a website that relates to an article the visitor has already downloaded. In this case, a database saves information about a customer’s online identity and what they might have searched for or previously downloaded.
Matching the caller ID with a record in Salesforce: Through robust integrations with Salesforce, this type of AI lets a contact center agent greet a customer by name as their phone number “pops” in the agent’s CRM when the contact calls. This type of AI has been in use for many years, and although it might seem basic, it’s still in action in the typical contact center.

Whisper Technology

Whisper technology is when an AI-type assistant “listens” to an agent’s in...