Carefully Consider Generative AI Integration for Customer Service Success

Customer service remains paramount in today's swiftly changing business landscape. Thankfully, customer-first organizations can lean on artificial intelligence and automation to enhance customer service and strengthen relationships. Both can reshape customer service by introducing new efficiencies and more personalized experiences.

Traditionally, customer service teams have faced hurdles such as budget limitations, high call volume, and changing customer needs. However, the emergence of AI, particularly generative AI, in customer service applications helps mitigate these obstacles by streamlining more redundant tasks. McKinsey indicates that generative AI can augment individual workers by automating functions that absorb 60 percent to 70 percent of their time<.

Generative AI can also augment customer operations. AI-based intelligent virtual agents (IVAs) are one such use case, generating personalized responses to users, enabling organizations to tailor interactions to meet customers' unique needs. Generative AI also helps organizations streamline repetitive customer service processes, which leads to a decrease in resolution time, drives increased customer satisfaction, and nurtures enduring brand loyalty.

Here are five examples of how companies can use generative AI in customer service:

  1. Self-service knowledge bases: IVAs can use generative AI to create self-service knowledge bases filled with the latest information on products, services, and policies. These knowledge bases enable customers to find answers to their questions quickly and easily without waiting for a human agent.
  2. Product recommendations: Generative AI can aid IVAs in recommending products and services to customers based on their past purchases, interests, and preferences. These personalized recommendations can help customers find the products and services they want more quickly and make them feel valued and understood.
  3. Training materials for service agents: Generative AI is an excellent tool for creating training materials for customer service agents. These materials can help agents learn the skills they need to provide excellent customer service.
  4. Customer sentiment analysis: Generative AI can analyze customer feedback and identify trends in sentiment. Businesses can use this information to develop processes that will improve customer satisfaction and loyalty. They can also adjust IVA-based interactions based on this analysis.
  5. Tailored marketing outreach: Marketing teams can leverage generative AI to create campaigns and proactive outreach tailored to the interests of individual customers. IVAs can personalize outreach regarding promotions, products, and services, which can help businesses increase brand awareness, drive sales, and improve customer loyalty.

Generative AI's ability to boost productivity and strengthen customer experience makes it enticing to business leaders. However, capitalizing on its potential requires a systematic approach to implementation. One way to approach implementation is by starting with internal processes. Businesses can first deploy generative AI to employees, which can create a deeper understanding of the technology and build confidence within the organization.

Below are a few essential steps for business leaders to implement generative AI effectively for internal processes.

  1. Identify needs: Business leaders must understand their objectives and how generative AI can best support specific tasks and everyday applications. These applications include automating frequently asked questions, content generation and summarization, data entry and analysis, or results reporting.
  2. Choose wisely: Select tools that cater to the unique requirements of team members. Give precedence to interfaces and workflows that are intuitive for users and can be personalized by employees to align with their preferences. Partnering with a provider with comprehensive monitoring and reporting functionalities is also important.
  3. Monitor performance: After the generative AI solution is running, oversee its initial operation phases. A helpful tip is tracking metrics such as content accuracy, data entry speeds, error rates, and consistency.
  4. Collect user feedback: The collection of insights from employees engaged with your generative AI solution is essential. Through this practice, you can identify opportunities for improvement, fostering ongoing enhancement and refinement.
  5. Make changes: While you collect feedback from employees, make note of practical applications for customer service tools, should external adoption be a priority. Regular updates based on user feedback ensure the solution is consistent and effective.

By following these steps for internal processes, decision-makers pave the way for generative AI in customer service. Organizations can establish customer service excellence by channeling the capabilities of generative AI with a phased adoption approach.

Successful generative AI integration for customer service requires a clear vision, practical use cases, and continual monitoring. As organizations embrace generative AI, they set themselves up to deliver unparalleled customer service. Businesses can redefine the customer experience and empower their teams to engage with customers in new ways.

Rebecca Jones is general manager of Mosaicx, a provider of customer service artificial intelligence and cloud-based technology. She joined the West Technology Group, owner of Mosaicx, in January 2021 after a 25-year career focused on growing businesses, people, and client success.