AI in SMB Contact Centers

AI integration in contact centers is revolutionizing customer care for small businesses, enhancing efficiency and customer satisfaction. As small businesses increasingly rely on AI tools, they are better equipped to manage call volumes and address customer concerns effectively.

John Klein, a solutions architect at CDW and an industry expert in communication and collaboration platforms, highlights the significance of AI in modern contact centers. With extensive experience in voice, video, and audiovisual technologies, Klein has played a pivotal role in designing and deploying phone systems and video solutions across various manufacturers.

Customers often prefer different communication methods based on the complexity of their concerns. For quick questions, email or text is sufficient. However, for more complex issues, customers tend to pick up the phone. This dual challenge for small businesses—ensuring quick response times and connecting callers to the right staff—can be effectively addressed through AI integration in contact centers.

A survey reveals that 94% of Baby Boomers and 71% of Gen Z consider calls the quickest way to reach customer care. This preference underscores the importance of maintaining efficient call centers, even as alternative communication methods like text, email, and social messaging become more popular. Small businesses, despite their size, must create a substantial online presence, which necessitates a reliable and responsive call center.

Key Advantages of AI in Contact Centers

AI tools, such as large language models (LLMs), chatbots, and natural language processing (NLP), offer significant benefits for contact centers. Tier-one agents, who are the first point of contact for callers, can leverage AI to answer simple questions and route callers to higher-level support as needed. This dual functionality makes AI an ideal entry point for improving contact center operations.

Chatbots and Simple Queries

Chatbots can be trained to handle simple queries by accessing connected databases. They can also escalate calls based on the content and context of customer interactions. For instance, if a caller inquires about delivery updates, AI tools can request tracking numbers and retrieve relevant data. If a customer reports an issue with a product, AI can escalate the call to human agents for further assistance.

Understanding Customer Sentiment

Advanced LLM and NLP frameworks enable AI agents to better understand customer sentiment. For example, two customers calling an SMB and saying, "I need to speak with an agent," may have different underlying emotions. Customer #1 might be calm and responsive to a chatbot's help, while Customer #2, who has been struggling with an issue for hours, might be agitated. AI can differentiate between these sentiments and respond appropriately.

Integrating AI with customer relationship management (CRM), enterprise resource planning (ERP) systems, and e-commerce platforms can enhance the ability of human agents to handle customer concerns. Once callers are on the line, AI tools can provide relevant data, including past conversations, purchase histories, and previous complaints, giving agents a head start in resolving issues.

While generative AI-enabled chatbots have significantly improved, AI integration in contact centers is not a one-time task. Small businesses must approach it as a long-term investment requiring continual monitoring and consistent management. By doing so, AI can help reduce costs and improve customer satisfaction, making it a valuable asset for small businesses.

This article is part of BizTech's AgilITy blog series, featuring insights from AI experts and IT leaders. New research from CDW highlights the growing importance of AI in contact centers for small businesses.