In today’s fast-paced, up-to-the-minute world, many buying decisions come down to customer service. Here is where technology, most specifically Generative AI, is having a dramatic impact.
With most consumers – an overwhelming 76 percent, per a McKinsey & Company report – getting frustrated when companies don’t deliver personalized interactions, it is not surprising that more than 40 percent of decision-makers have their eyes set on generative AI in 2024 to elevate the customer experience (CX). And by 2028, Gartner reports GenAI will be used by a staggering 80 percent of customer service and support organizations.
Harnessing AI For Superior Experience
These huge forecast numbers cement how AI, and particularly GenAI, is at the forefront of modern customer service. Early adopters have already demonstrated how AI-driven tools have reshaped their delivery of customer service. Among the use cases for GenAI in customer service include:
- Service Responses: With the capability to process voluminous, real-time data sources, GenAI can auto-generate personalized replies that customer service agents can evaluate or edit and then use to respond to issues swiftly. An example of such a tool is Salesforce’s Service GPT.
- Contact Summary Reports: First-contact resolution is a key element in customer service. Be it a query, feedback, or complaint, customer service agents are trained to resolve any issue on the first contact. However, when a contact escalates, there’s a need for a second support rep to take over. GenAI can quickly summarize the contact, eliminating the need for customers or the first agent to repeat the issue and all information provided during the initial interaction. Verint’s Interaction Transfer Bot is an example of such tool.
- Expanded Field Operations: Field service work is one of the most demanding and stressful jobs. Agents often face long work shifts and drive significant distances to respond to customer concerns. It is crucial that they have quick access to tools that can help them address problems efficiently while on the field. AI-embedded tools like Oracle’s Fusion boost field service support, from automating scheduling and routing to digital service assistants offering next-best-action recommendations.
These bright spots of GenAI use are all geared toward enhancing the customer journey. Still, the technology has a lot more to offer in elevating further the customer experience.
Time To Get Hyper-Personal
Moving forward, the customer service strategy should be all about hyper-personalization, propelled by AI-driven tools. For instance, AI-based predictive analytics can use customer data to anticipate needs, behaviors, or potential problems to tailor responses and interactions. Meanwhile, AI-powered recommendation systems can analyze customer preferences and buying history for customized suggestions. Chatbots get personal, too, as advances in natural language processing (NLP) allow these systems to compose relevant and suitable responses. One of the success stories of AI use in customer service is that of beauty retailer Sephora. Its AI-driven customer service strategy has resulted in wider audience reach, an increase in brand loyalty, and a jump in e-commerce net sales.
An AI Firsthand Encounter
However, the benefits of AI integration in customer service are not solely for customers. Service representatives get to experience the technology’s transformative power, too, as access to AI tools increases productivity, optimizes efficiency, and improves employee morale and retention among other things. They are also learning valuable AI skillsets that can help future-proof their jobs, helping allay fears of technology replacing them at work. That the AI-human collaboration is indeed the future of customer service.
Decision-makers now face the challenge of how to use AI best to learn more about their customers. As IBM Institute for Business Value notes, a successful AI deployment in customer service is all about triumphing over high risks and capturing high rewards through listening, testing, and then capitalizing.
