How AI can benefit CX and customer service

1. Context mining

The evolution of machine learning (ML) and natural language processing has enabled context mining tools to read unstructured data from emails, web forms and surveys, as well as correctly interpret context and urgency. This technology is a game changer for contact centers, where most communication happens over email.

A context mining service can automate how a business routes sales orders to process and forward requests to the appropriate department. Context mining enables customer service representatives to connect with customers who want to speak with a human, which boosts CX and can relieve high-stress situations.

For example, many customer service agents spend the beginning of their work weeks catching up on time-consuming tasks, like adding sales orders received over the weekend. In turn, call abandonment rates skyrocket, and emails go unanswered if data entry tasks consume agents. With a context mining service, agents can better use their time and speak directly with consumers. In turn, CX improves.

2. Intelligent document extraction

Traditional document extraction technologies involve time-consuming and cumbersome practices. They were rooted in hard copies and scanners or required training on thousands of document formats. In turn, organizations spent time training on document types rather than completing tasks, such as entering or fulfilling orders. Now, ML has entered the domain of document extraction and flipped the script, offering a tool that requires less document training and more flexibility.

Advanced ML technology can pre-train models on thousands of sales orders and quickly customize and read documents with high accuracy. If the ML model is below a certain threshold of confidence, it can reroute the data to a human to verify, while getting better at predicting future outcomes.

Intelligent document extraction with tools like robotic process automation can enter sales orders without human intervention, which enables customer service agents to spend more time building relationships with customers.

3. Conversational AI with sentiment analysis

Historically, customers often don't use websites' FAQs, yet they have frequent questions and expect prompt service. Those customers speak with a digital customer service agent 24/7 over a phone call, chat or social media. In a traditional contact center, interactive voice response would act as the front line and often frustrates customers with unhelpful menu selections.

Introducing conversational AI into customer service can make a difference in CX. Conversational AI can speak with customers as a human would, answers common questions, prioritize issues, route their calls and escalate to a human when necessary. After the AI verifies customer information, it can look up billing or tracking details, resend a receipt or provide customer-specific account information. When a customer requires escalation to a human, the tool gives a transcript of the conversation and sentiment data to the agent, leading to seamless CX, more first-call resolutions and better customer engagement.

In the modern business climate, CX and good customer service make a brand standout. Without capitalizing on available technologies to deliver optimal experiences, companies run the risk of losing out on business. Integrating AI with context mining, intelligent document extraction and conversational AI with sentiment analysis can help businesses gain a competitive advantage and improve experiences for employees and customers.

About the author
Christina Kucek is executive director of intelligent automation at CAI.