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Call centers have long been environments where innovation thrives. From high-tech audio hardware to custom software solutions, savvy call centers leverage tech to make operations run smoother and make the customer experience friendlier.

It makes sense, then, that in the present day, cutting-edge technologies like Artificial Intelligence (AI) stand poised to revolutionize these environments and transform how customers and call center agents interact.

Machine learning, natural language processing, and other forms of Voice Intelligence can provide your call center with tremendous advantages — provided you understand how the technology can streamline workflows and boost efficiency. Here are the most exciting ways in which AI and customer service call centers intersect for the better.

📚 Check out Dialpad's State of AI in Customer Service Report 2022 for the latest insights about AI's impact on businesses and contact centers, based on a survey of over 1,000 CX professionals.

Intelligent Call Routing

It wasn't that long ago that skills-based routing systems were a fresh concept — using customer profiles to pair callers with an agent whose skills were up to the task of assisting them. Increasingly, AI and computer analytics will make the human element unnecessary when determining which agent to assign to a call.

Intelligent call routing uses self-learning algorithms to analyze customer personality models, previous call histories, and behavioral data. It then uses that info to determine the best manner in which to handle calls — sending simple, routine requests to bots if possible and routing calls to live agents only when the nature of the request is of sufficient complexity to require a human touch.

In those cases, AI can use the information at its disposal to route calls to the best-equipped agents to deal with specific types of customers and queries, ensuring that tickets are closed quickly and effectively and free up time across the board.

Over time, this technology becomes more effective at making successful matches, which allows you to better respond to customers and improve their overall experience consistently.

Improved Call Analytics

There's a wealth of information in every customer interaction, and call center AI is the key to capturing it all.

Simple sentiment analysis can provide hints on how people feel about your brand, service, or products based on the words they use. Advanced sentiment analysis can consider the tone of voice and speaking volume, giving a complete picture of the "how" and "why" of what a customer says.

With features like Natural Language Processing (NLP) and voice recognition, you can record customer service interactions and have them transcribed in an easy-to-read format. Transcriptions make it easy for supervisors to review conversations at a glance, pick up necessary details, and spot areas where agents need more coaching.

AI can assist with analytics, which provides the opportunity to spot trends across large sets of customer data while providing insights on whether or not your customers are angry, happy, or dissatisfied. You'll then adjust your strategies for interfacing with customers to improve your services to deliver a better experience for your customers.

A Better Grasp of Customer Behavior

Building off of call analytics, AI can make customer interactions more effective in several ways. For starters, the trends in customer behavior that AI can identify will provide the early insight that call centers require to predict emerging customer needs and quickly develop best practices around them.

What's more, AI can make detailed customer information and behavioral profiles available to all your agents. This information helps your customer service team anticipate customer needs and quickly adjust their approach to customer retention, upsell and cross-sell, or other specific actions in every customer interaction.

Response Suggestions and Management

What's the best way to respond to large volumes of customers? While AI might not formulate complete, perfect responses for every scenario, it's more than capable of assisting agents in responding more appropriately in a wide range of situations.

Real-time speech analytics (RTSA) can provide live feedback about the flow of a conversation, augmenting agents' and customer service representatives' listening capabilities. It can also offer recommendations on opening lines, closing lines, responding to queries, and other best approaches.

Additionally, you can use this technology to ensure that conversations adhere to your internal standards and alert managers when conversations veer from the appropriate course and may require either intervention or follow-up action. This will improve customer call quality over time, help you further refine best practices, and reduce instances of churn and dissatisfaction among callers and customers.

Facilitating Self-Service

AI can't replace everything that a human agent can do, but it is often sufficient to reach a satisfactory resolution for simple requests. You can leave routine, day-to-day questions, and other fundamental interactions that might fall under the banner of "self-service" to AI. Help your callers complete simple tasks like placing an order, checking a balance, or paying a bill on their own, so your human agents are free to respond to more complex calls.

There is also a potential for AI to take on more significant self-service tasks. This depends on having accurate data so that AI can correctly automate its responses to customers. Incomplete information limits the ability of AI to manage more complicated interactions. Prioritizing data and analytics will be essential if you want AI to play a larger role in responding to customers and providing more significant degrees of self-service.

Use Cases for Call Center AI

Though the specifics vary, the primary use cases for AI in call centers fall into three main areas:

  • Automating data collection and routine processes to free up human agents
  • Analyzing call center data to provide insights on customers and refine strategies
  • Supporting service agents by improving response times and quality

Though the development of many call center AI features is still relatively recent — within the last several years — you can observe their impacts based on the continued adoption and refinement of such technologies by large entities in both the foodservice and banking industries.

While AI technologies will never replace humans in customer service and call center roles entirely, they are set to take on more of the monotonous work and support humans in carrying out their functions more effectively.

Dialpad's AI technology can help route calls intelligently, monitor customer sentiment, provide better self-service options, and more. To learn how AI can help streamline operations and boost your call center's efficiency, contact Dialpad today.