AI in SMB Contact Centers

John Klein is a solutions architect at CDW and an industry expert in communication and collaboration platforms. He has experience in training and education in voice, video, audio visual, and headset technologies and has helped design and deploy hundreds of phone systems and video solutions across manufacturers. John Klein is a solutions architect at CDW and an industry expert in communication and collaboration platforms. He has experience in training and education in voice, video, audio visual, and headset technologies and has helped design and deploy hundreds of phone systems and video solutions across manufacturers.

When customers have a quick question, they may reach out via email or text. For more complex concerns, they’re picking up the phone. For small businesses, this creates a dual challenge: Ensuring that calls are answered quickly and connecting callers to staff who can effectively address their needs. Integrating artificial intelligence into the contact center can help keep wait times down and customers satisfied.

According to one survey, 94% of Baby Boomers say calls are the quickest way to reach customer care. Surprisingly, 71% of Gen Z say the same, despite their familiarity with alternative options such as text, email and direct social messaging. No wonder, then, that 57% of customer care leaders expect call volumes to increase over the next two years despite available alternatives. And small businesses are no exception. Their small size is no bar to creating a substantial online presence, which in turn necessitates a reliable and responsive call center. Integrating AI systems such as large language models (LLMs), chatbots and natural language processing (NLP) offers a path to improved call center operations that don’t break the bank.

Key Advantages of AI in Contact Centers

Tier-one agents are the first stop for callers. They’re also the ideal entry point for AI. This is because tier-one calls serve two common purposes: Answering simple questions and routing callers to higher-level support as needed. AI tools excel at both tasks.

Chatbots and Simple Queries

Chatbots can be trained to answer simple questions using connected databases and can flag calls for escalation based on the content and context of customer calls. For example, if a caller is looking for delivery updates, AI tools can ask for tracking numbers and fetch relevant data. If, however, a customer states that their item has arrived but isn’t working as intended, AI can escalate the call to human agents.

Understanding Customer Sentiment

Improved LLM and NLP frameworks help AI agents better understand customer sentiment. Consider two customers who call an SMB, reach a chatbot and say, “I need to speak with an agent.” What the business (and the chatbot) don’t know is that customer #1 ran into a challenge with his new product and immediately picked up the phone. Customer #2, meanwhile, is dealing with the same problem but has spent the last few hours trying to solve it himself, getting increasingly agitated in the process. While both customers say the same thing, their tone changes the meaning. Customer #1 might be responsive to a chatbot offering to help. Customer #2 will not be.

By integrating AI with customer relationship management, enterprise resource planning systems and e-commerce systems, small businesses can augment the ability of human agents to handle customer concerns. Once callers are on the line, AI tools can pull up relevant data including past conversations, purchase histories and previous complaints, giving agents a head start.

While today’s generative AI-enabled chatbots are a significant improvement over their predecessors, AI is not a fire-and-forget function. Instead, small businesses need to approach AI integration as a long-term investment that requires continual monitoring and consistent management.

AI in contact centers can help small businesses reduce costs and keep customers coming back. This article is part of BizTech's AgilITy blog series. New research from CDW reveals insights from AI experts and IT leaders.