5 Ways to Leverage Artificial Intelligence in Call Centers

As generative AI advances, it is quickly becoming less expensive and more efficient than work done by hand, and in some cases, surpassing what humans create. Every profession that requires creativity — such as social media management, games development, graphic design, coding, or product design, to name a few — will soon be revolutionized by this technology. Advertising strategies and sales processes are already being changed thanks to the power of generative AI.

Speech Analytics converts spoken words into text, making it easier to search and analyze customer conversations. This transcription process enables contact centers to track keywords and phrases that are important to their business, such as product names, competitor mentions, or compliance-related terms. While AI-powered systems may be able to handle a large volume of calls, they still require a significant investment in terms of technology and infrastructure. This investment may not be feasible for smaller businesses or those with limited budgets, meaning that human agents will still be necessary for these companies.

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Predictive call routing factors information regarding the customer’s problem and analyzes the customer’s voice to estimate their mood and personality. This way, customers can connect with an agent that matches their temperament and needs. Here are a few AI applications that can create better customer experiences and impact the way your company thinks about call centers. Customers expect their interactions with the contact center to be fast, personalized, and effortless. It would help if agents had insight into past behaviors, trends, and unspoken needs. At the same time, siloed data and functions make it hard to get visibility into the customer journey.

• While the use of Generative AI in call centers is still in its early stages, it is worthwhile to explore some of the potential use cases for Generative AI chatbots in this context.
• By efficiently addressing the customer’s concern, the chatbot eliminates the need for the customer to wait on hold or be transferred to a human agent, saving time for both the customer and the call center.
• Before deploying Invoca’s AI-driven platform, MoneySolver tracked only a small percentage of calls into its call center where over 100 agents handle customer inquiries.

Through this, AI suggests articles, manuals, or solutions based on the ongoing conversation. This streamlines issue resolution and allows agents to provide accurate and up-to-date information to customers. Speech analytics can automatically assess calls as they happen, enabling real-time monitoring. This ensures agents get the required coaching to help them handle customer inquiries better and promptly resolve issues. AI integrates with data sources, such as CRM systems, to access relevant customer information, then uses skills-based routing, predictive routing, and customer priority to match callers with the most suitable agents. Additionally, contact centers use AI in handling multichannel routing, such as chat and email.

Unpacking Customer Demand: The Next Frontier for Customer Experience Transformation

The development of quality assurance tools, generative AI systems (like ChatGPT), low-code platforms for building bots, and more have driven rising interest in AI solutions. Over the years, platform providers have introduced endless tools designed to boost productivity and enhance customer satisfaction. But, the intelligent solutions available to customer service leaders today are becoming more advanced.

AI-powered Call Routing can also provide agents with insights into customer behavior and needs, so that agents can personalize calls and effectively address the customers’ issues. This helps agents respond to customers confidently and quickly and provide customers with helpful resources. Meanwhile, NLP is a branch of AI that helps machines understand text and speech similar to how a person would. Popular NLP-based applications include Speech-To-Text (STT) transcription, Sentiment Analysis, and chatbots. Omnichannel Routing – routing and interaction empowers agents to positively and productively interact with customers in digital and voice channels.

Deep learning unlocks even more surprising innovations, first of all in the field of speech recognition and interactive voice response. With the tools covered in this article, you’ll have a solid foundation to get started with AI as part of your customer service strategy. Ultimately, real-time translation is an essential AI tool, enabling businesses to engage a wider audience, improve accessibility, and eliminate language barriers. Sentiment analysis is an application of contact center AI that can be used to identify and monitor customer emotions/attitudes. They can even route customer service requests to the most appropriate agent/department by gathering the initial details of the customer’s query before escalating. Here, we’ll cover five applications of contact center AI and how each one can be used to supercharge customer service.

VOICE & AI attendees will run the gamut from developers and conversation designers to product leaders and marketers, Erickson said. They are all trying to figure out what the best approach for utilizing the new generative AI technologies to upgrade their aging tech stacks. So much has changed technologically in such a short period of time that it’s causing a ripple effect in the larger enterprises that are trying to figure out to adjust their roadmaps to account for the new tech.

The pandemic accelerated an ongoing trend in which AI was used to enhance the current de facto call center response tool — IVR. By using AI-driven chat tools, smaller problems can be immediately addressed, while large, more complex issues can be directed to call center agents. Conversational AI continued to help evolve the call center, while predictive behavioral routing took it to the next level, enabling brands to deliver exceptional customer experiences during the pandemic and beyond. With so many businesses closing their doors while others were forced to transition to an entirely remote workforce, call centers struggled to quickly move from in-office call centers to home offices. Magnus Geverts, VP of product marketing at Calabrio, a customer experience intelligence company, told CMSWire that 2020 was the year of reinvention for contact centers, and that AI allowed businesses to remain operational.

Read more about How To Use AI For Call Centers here.