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AI self-service benefits and best practices
Customer service is now the top area for AI adoption across the enterprise. Follow these best practices to implement AI-driven self-service in your organization.
Customer self-service portals can be convenient and improve CX when they help consumers get what they need more quickly and easily than speaking to or chatting with a live agent. But when customers can't get what they need from self-service tools or businesses have an upsell opportunity that requires human intervention, that benefit ends.
Determining whether to route customers toward or away from self-service portals is now less challenging with the arrival of generative AI agents powered by large language models (LLMs). No longer must customers browse categories, run keyword searches that spit out links to follow, or have stilted conversations with rule-based chatbots. Instead, they can engage in casual conversation with AI agents that understand their intent, tap into the company knowledge base, and deliver contextually relevant information that can resolve even the thorniest of problems.
Now, 52% of companies use AI text agents and 42% use AI voice agents for customers, according to a global Metrigy study of 759 companies that researched the role of AI in CX. AI is fundamentally changing the customer interaction model, to the point where more businesses now say technology matters more than people in delivering successful customer interactions.
In fact, most companies (79.5%) say AI will have a positive effect on their customer service in the next two years. In the coming years, they anticipate the percentage of customer interactions that AI fully resolves will double, from 29.2% today to 60% by 2030.
Customer-facing AI agents already are proving generally better at handling most customer issues than human agents, including confirming or changing deliveries, appointments and reservations, getting product information, and reaching out proactively. Human agents are better for refunds, complaints and selling products or services, according to the Metrigy study.
As companies develop and refine their customer self-service strategy, they must consider how and when AI will play a role.
AI self-service best practices
Never finish building a knowledge base
The self-service knowledge base is always a work in progress that changes with the company. The more a business can automate those updates, the better. As customers ask chatbots, AI agents or human agents questions, AI will note the addition of new inquiries, compile appropriate answers to each and automatically add new questions to the knowledge base. What's more, as content in the knowledge base itself changes, AI can automate those updates. For example, if the warranty terms have changed and are updated in the company warranty file, AI can see that update and automatically update the knowledge base.
Optimize unstructured content for AI agent use
To maximize the value of AI in self-service, organizations must ensure their unstructured data is properly formatted for AI consumption and indexed for use by retrieval-augmented generation (RAG) systems. RAG systems elevate self-service deliverables by retrieving specific knowledge base and document sets for relevant data based on the customer's conversational prompt. The retrieved data gets added to the LLM prompt for context, and the LLM generates a response using that newly provided data, improving accuracy and contextual relevance.
Incorporate triage agents into self-service journey
Currently, two-thirds of companies begin at least some of their customer interactions with an AI triage agent. These AI triage agents, which typically replace interactive voice response systems, effectively ask customers what they need using natural language instead of having customers select from a menu. Today, 36.3% of all customer interactions start with an AI-powered triage agent. However, human agents are still most effective for handling complaints, processing refunds and selling products or services.
Use transactional self-service
Self-service becomes more complex, but also incredibly useful, when it's transactional. Think of tasks such as transferring money, rescheduling an appointment and retrieving medical records. To support self-service transactions today, 64.3% of companies are using AI agents to automate the integration between front-office CX applications and back-office systems. These tasks reduce the business's operational costs because, in the past, a human had to be involved in each of them.
Make proactive suggestions
Use AI to make suggestions for either solving a problem or selling something that aligns with the customer's characteristics or activities. Reach out proactively, using AI guidance for customer segmentation, message generation and best time to contact.
Personalize interactions
Personalization and customization matter. Rather than just providing knowledge bases that customers can search, use AI to deliver personalized responses based on a customer's past purchases or interactions. Proactive outreach should be highly personalized, as well.
Give customers options
If self-service fails, always provide an option to chat with a human agent or schedule a call or chat if the business does not operate 24/7.
Take advantage of mobile devices
When designing an effective self-service strategy, consider other enabling technologies that can increase the use of self-service portals. For example, businesses with mobile-enabled self-service portals see substantial increase in use. Customers who use mobile devices typically want a quick answer to a pressing question.
Use interaction analytics
To further refine a self-service strategy, businesses need to make the most of interaction analytics. Customer interaction data is an invaluable source of information for the business in general as well as for gaining an understanding of how AI agents and human agents can better serve customers.
The bottom line: Customers want intelligent self-service that provides them with answers quickly and guides them to new products and services, opportunities to join loyalty programs or proactive notification systems, and personalization based on their past interactions.
Beth Schultz is vice president of research and principal analyst at Metrigy. She focuses her research on unified communications, collaboration and digital customer experience.
