Leveraging AI to Super-charge Customer Engagement: Why Chatbots Must Chat Less and Answer Questions More

0
154

Share on LinkedIn

Chatbots have become increasingly common in recent years, with businesses using them to handle customer inquiries, assist with online transactions, and even provide emotional support.

They are designed to ask a series of questions and mimic a person to make humans more comfortable when interacting with the system, all while reducing the “information space” of possible answers. While this back and forth between machine and human may make it more likely for the question to eventually be answered, the experience often becomes time-consuming and frustrating, especially when the machine veers off track, makes nonsensical comments, or worse, ends up still not being able to find the right answers after a long chat.

It is fairly obvious that most people don’t want to spend time chatting when they have questions. When looking for information or assistance, they want to get to the correct answers as quickly as possible and avoid wasting time engaging in idle conversation or exchanging pleasantries with a chatbot. Put simply, they want to ask the question, get a clear and concise answer, and move on with the task at hand. In order to optimize this experience, there should be less emphasis on “chatting” with users and more focus on ways to provide them with specific answers to their questions on the first click.

How NLP Can Turn Search Engines into Answer Engines

To combat the above challenges, many organizations are looking to evolve the search process using sophisticated AI-based solutions. As Natural Language Processing (NLP)-powered “answer engine” technology has advanced, it has become possible to design chatbots that are able to answer questions without the need to carry out a lengthy and unproductive conversation. These advanced chatbots will have an NLP-powered answer engine at the foundation, allowing them to understand sophisticated human language intuitively and find the most accurate, comprehensive, and trustworthy answers instantly. This makes the experience much more efficient and satisfying. End users don’t have to spend time trying to clarify their questions, decipher a chatbot’s responses, or engage in small talk to get the information they need.

While chatbots are very good at executing the tasks they were designed to do, such as closing an account or processing a payment, they often struggle with answering questions, particularly if those questions are phrased differently from what the chatbot expected. Unfortunately, errors are common as most chatbots are trained to recognize specific keywords and phrases and respond with pre-programmed answers. As a result, if a user asks a question in a way that the chatbot doesn’t recognize, it may not be able to provide an accurate or useful response.

An NLP-powered answer engine is intelligent in that regard. It not only allows users to ask their questions however they like, but also understands that the same question phrased differently is asking for the identical information. Therefore, it returns precise results without getting stuck. This advanced chatbot capability results in a more personalized and positive user experience, enabling improved customer engagement and overall satisfaction.

A key advantage to chatbots powered by answer engines is finding not just one, but all the accurate answers so the user won’t miss out on important information. For example, a compliance officer can leverage a chatbot to find all the regulatory requirements from a long list of compliance documents. This means that the company won’t overlook any important rules and standards related to the specific regulation so they can meet any compliance mandate successfully.

What about ChatGPT?

Although it has made great strides and could be suitable for many consumer applications, ChatGPT alone cannot provide accurate answers to most questions related to a specific business. This is because it often returns unacceptable levels of inaccurate information and does not provide any explainability as to how it generates a response. Chatbot providers and organizations in complex and regulated industries such as healthcare, legal, financial services, and government, who must provide both trusted answers and transparency, cannot afford to rely on ChatGPT today. However, some of the underlying ChatGPT technologies can potentially be coupled with answer engine technologies to reliably address customers’ needs.

In order to be effective, it often comes down to the chatbot’s ability to deliver answers effectively. While chatbots have been designed to mimic human conversation and sometimes engage in idle chit-chat, the future of chatbots lies in their ability to quickly and efficiently answer questions with precise and comprehensive answers in addition to performing simple tasks. As businesses recognize the value of chatbots that excel at answering multiple types of questions, we can expect to see a shift away from conversational chatbots and towards more efficient and effective tools that help users get accurate and trusted information quickly and easily.

This is great news for both businesses and consumers, as it will reduce customer frustration and confusion caused by chatbots that are unable to answer questions beyond what they are trained on, allowing for more streamlined and effective customer service experiences.

John Reuter
John Reuter is the Chief Strategy Officer at Kyndi, a global provider of the Kyndi Platform for the Natural-Language-Enabled Enterprise, an AI-powered platform that empowers people to do their most meaningful work. To learn more visit https://kyndi.com/ or follow them on LinkedIn: https://www.linkedin.com/company/kyndi/ and Twitter: https://twitter.com/kynditech.

ADD YOUR COMMENT

Please use comments to add value to the discussion. Maximum one link to an educational blog post or article. We will NOT PUBLISH brief comments like "good post," comments that mainly promote links, or comments with links to companies, products, or services.

Please enter your comment!
Please enter your name here