How Visionary Companies are Using Artificial Intelligence

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Visionary companies around the world are exploring different technological strategies to meet the growing consumers’ demands for improved CX with reduced costs. Moreover, outbound sales call centers are trying to incorporate AI into their business strategies to alleviate pressure on their agents and create a more productive work environment for everyone.

Call center affiliate programs are known for turning to AI-powered contact solutions to streamline their workflow. After all, AI has immensely impacted the customer services sector and has proven to be an effective means of improving performance.

AI has given BPO companies the ability to reduce their operational costs without any comprise on the quality of customer service provided. It allows them to personalize customer experience for improved performance while also increasing customer agent efficiency and developing actionable analytics to further achieve their long-term business goals.

Today, let’s learn more about how outbound call center companies are making the most of artificial intelligence to scale and grow their businesses.

How is AI Used in USA Call Centers?

1. For Predictive Call Routing

Most people think of predictive call routing as a means of routing a call to a particular department. In reality, this AI-based technology is significantly more complex and sophisticated.

Predictive call routing uses AI to match call center customers to particular agents who are best able to handle their specific issues. This can be based on the agent’s particular set of expertise or even a personality model specific to the organization.

This AI-based technology relies on the customers” behavior profiles to develop a comprehensive understanding of their journey, preferences, and personas. The software looks at communication habits and other features to match each query with the best-equipped agent at that particular moment based on their communication style, personality, and call history. This allows the organization’s customer service and overall experience to be hyper-personalized for each customer. 

2. For Interactive Voice Response Protocols

Interactive Voice Response is one of the most common AI-based protocols used in outbound call center outsourcing. Most of us have interacted with this form of AI during our customer service experiences. 

This was when the customer answered pre-recorded questions about themselves, including what language they speak, their name, account details, etc. This might come across as tedious and frustrating, but this AI technology can save companies a significant amount of time by routing calls appropriately.

This type of Interactive Voice Response is best suited for companies with a high volume of incoming calls. Most of these calls are about operational hours, eligibility, bank statement information, and other routinely, specific information that is required prior to services. They mostly don’t need to be handled by a service agent and can be done directly through AI.

3. For Conversational and Emotional Intelligence AI

Conversational AI is commonly known as chatbots nowadays, and it is when AI is used by a call center to power up an online chat option. This has become a necessary form of customer service for most organizations globally, as consumers now prefer messaging with brands directly instead of calling them up on the phone.

As you probably know, chatbots are now one of the most in-demand channels for customer service queries. They allow customers to quickly get their questions answered using a form of self-service. They receive customer support in a live environment without having to interact with a service rep and ensure long wait times.

Chatbots are also a huge asset to businesses as they significantly reduce call volumes. Agents no longer need to answer redundant questions and can focus their time on resolving complex issues instead. 

On the other hand, emotional intelligence AI allows you to track customer sentiment live on the call. This is mostly done by detecting changes in the customer’s voice. For example, an angry customer would start to speak louder, while a frustrated customer might take long pauses or deep breaths.

Emotional AI is trained in different languages and cultural cues to maximize its efficiency. It analyzes the tone and cadence of the customer’s voice to detect their mood. It also measures the number of times an agent interrupts a customer and the tone of voice in which they reply.

All of this data is collected and presented in the form of live feedback via popup messages to offer the agent insight into how the customer is feeling during the call. The agent can then make any necessary changes to the way the call is handled to ensure the best results. This form of AI can do wonders for conflict resolution and allows outbound ecommerce customer service agents a way to pick out cues that they might have missed on call.

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