What is AI for Customer Service
Among commonly used AI technologies are Natural Language Processing, ML, Case-Based Reasoning, and Conversational Generative AI, among others. Businesses need a trusted AI knowledge hub for AI and knowledge orchestration so that the right AI is used and the right knowledge delivered for the right situation through the right channel in the right tone.
AI for customer service: Overview of technologies
- Machine Learning (ML) and Natural Language Understanding (NLU): Machine learning is a subfield of artificial intelligence that gives computers the ability to learn without explicitly being programmed (Source: MIT). NLU is the ability to understand natural language input, infer user intent, and respond accordingly.
- Generative AI or gen AI: Generative artificial intelligence (AI) describes algorithms (such as ChatGPT) that can be used to create new content, including audio, code, images, text, simulations, and videos. Recent breakthroughs in the field have the potential to drastically change the way we approach content creation (Source: McKinsey).
- Conversational AI: Conversational AI leverages AI technologies such as Case-Based Reasoning to guide frontline staff in their customer interactions as to the next best question to ask and the next best thing to do in their effort to resolve problems or provide advice. Conversational generative AI can also be used to drive conversations where regulatory compliance is not critical. Conversational AI can also be used to drive customer self-service conversations.
- Case-based Reasoning: Looks at past cases to resolve new cases just like a doctor would go about diagnosing a disease or a sales expert would go about recommending a new product to a customer.
- And much more.
AI for customer service: Use-cases
- Understand query intent: Not just hearing what the customer says (the “utterance”) but inferring intent and diagnosing the real problem.
- Customer self-service: Upon understanding customer intent, AI can drive self-service so customers can help themselves.
- Route the query: If self-service fails, AI can help route the customer’s query to the right queue or agent in an intelligent manner so that it is resolved effectively and efficiently.
- Leverage context: Context goes beyond the customer utterance and the current customer conversation. It includes checking the customer’s previous interactions, purchase history, and other account details as well as their current sentiment for a 360-degree view of the context to recommend the next best step.
- Resolve the query: AI technologies such as Conversational Generative AI and Case-Based Reasoning can provide real-time guidance to frontline staff to help them resolve customer issues while ensuring compliance. This can help make all your frontline agents as good as the best ones!
- Analyze and improve: Continuous improvement is key to customer service excellence. Analyzing customer interactions and knowledge-base adoption and effectiveness can provide insights into how service performance can be improved.
AI for customer service: The benefits
1. Reduced service costs
AI can help reduce service costs while elevating the quality of service at the same time. Our clients have seen up to a 90% deflection of customer service requests to digital self-service, 35% improvement in First-Contact Resolution (FCR), 15% reduction in Average Handle Time (AHT), and 50% reduction in agent time-to-competency. Proactive customer service can help preempt customer service calls. In addition, knowledge automation with AI accelerates speed to value. For example, our clients have been able to speed up knowledge creation and curation tasks by 5X with the GenAI capabilities in eGain AssistGPT.
2. Improved Customer and Agent Experience
AI-driven personalization enables businesses to deliver tailored experiences that wow individual customers. Moreover, the eGain AI Knowledge Hub enables service organizations to personalize conversational guidance. For example, a novice agent can be required to go through a step-by-step process while an experienced agent may be allowed to take short cuts.
3. 24/7 Availability
In today’s global marketplace, customers expect round-the-clock support, regardless of their location or time zone. AI-powered chatbots and virtual assistants ensure that businesses can provide round-the-clock support and assistance to customers anytime, anywhere.
AI for customer service: Addressing common concerns
Trust: A big barrier to AI adoption is a lack of trust in the answers it delivers. GenAI may hallucinate in some instances or give different answers to the same question. There is also the garbage-in-garbage-out problem. If AI is not trained on trusted data and content, it will generate and deliver garbage at the other end. This can increase financial and legal exposure for the business, especially in regulated industries such as financial services and healthcare. The solution here is to layer AI on a trusted knowledge foundation and orchestrate knowledge and AI centrally in a hub. This is exactly what the eGain AI Knowledge Hub does. Trust, in turn, increases user adoption and business value.
Change management: Key stakeholders such as contact center agents, knowledge authors, and subject matter experts may be skeptical when deploying AI and knowledge for customer service. They might worry that the new system may limit their career growth. These concerns can be overcome by positioning the initiative properly, focusing on what’s in it for them and how it can expand their career opportunities rather than limit them—for instance, they can support a broader portfolio of products, ascend to Level-2, or get into value-added activities such as sales with AI augmentation.
AI for customer service: Success stories
Multinational Financial Services Provider improved First Contact Resolution (FCR) by 36% and slashed training time by 40% with the eGain AI knowledge hub.
Hypergrowth SaaS company improved contact center agent confidence by 60% and self-service adoption by 30%, while improving their gross margin three years in a row, thanks in part to customer service automation, powered by the eGain AI Knowledge Hub.
Large federal government agency experienced “phenomenal success” with the eGain AI Knowledge Hub. The hub empowers 25 million users and 128,000 contact center agents and other customer service personnel with consistent and accurate information and AI-guided customer service processes, compliant with regulations. Thanks in part to eGain, their position in the Forrester CX Index improved by 33% in 2021 over 2020!
After implementing the eGain AI Knowledge Hub, a mammoth federal government agency deflected up to 70% of incoming calls to AI-powered virtual assistance, reduced case handling time by 25%, and improved form-filling with granular knowledge assistance within forms. No wonder these powerful capabilities elevated their agent engagement to 92% versus their industry benchmark of 67%.
Premier health insurance firm reduced agent training time for handling complex health insurance queries by 33% even as its agents—over 2,000 of them—had to go remote overnight due to COVID lockdowns. In fact, eGain’s AI-backed knowledge capability helped them meet all 30 of their goals, including slashing Average Handle Time and increasing First Contact Resolution, while vaulting them to a top 5 rank in Forrester’s CX Index benchmark evaluation.
AI for customer service: How to adopt risk-free
Related links
- Generative AI and KM for Customer Service: BFFs that Assure Mutual Success
- eGain AssistGPT™, eGain’s Generative AI Assistant for Knowledge Automation
- The Best Use Cases for Generative AI in Digital Customer Service
- Harnessing generative AI for customer service: KMWorld webinar
- Generative AI For Customer Service: Best Practices For Success
- Blog: 10 Use-Cases for Leveraging Generative AI for Better CX and AX (Agent Experience)
- eGain Knowledge Hub
- Try generative AI for customer service
- Artificial Intelligence in the Contact Center
- Blog: Artificial Intelligence (AI) Knowledge: The Platinum Bullet for Customer Service Transformation
- What is Generative AI for Customer Service?
- Knowledge Management for Dummies: 2nd Edition, John Wiley & Sons
- Download Gartner Market Guide for Customer Service Knowledge Management Systems