The Rythmos Blog

Do Chatbots Provide Real Business Value or Increased Customer Frustration?

Posted by Rythmos on Jul 19, 2019 11:00:00 AM

Chatbots are polarizing. On the one hand, are the skeptics, afraid of anything not human. They become genuinely upset when visiting a website they are interrupted by a single message - “Hi, How can we help you today?”

On the other hand, you have fervent supporters who want to skip the theatrics and ask pointed questions directly to the source. Chatbots earn the ire or the adoring love of everyone - and it’s rarely an in-between opinion.

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So what is the problem? What is the place of the chatbot today? Are they just a necessary though frustrating stepping stone to something much better or are they a pivotal part of adding real business value? 

What is a Chatbot?

It is essential to define what a chatbot is - and isn’t. These Artificial Intelligence (AI) messages simulate a conversation through a website, mobile app, telephone call, or any other kind of software. It is an active question answering system designed to simplify and streamline the customer to business interaction.

How Do They Work?

The problem of the chatbot may not necessarily lie in what a chatbot is but how it works.

A chatbot analyzes key data-entry points of a specific question asked by end-users and responds appropriately. It picks up on what are mostly keywords - phrases that can help decipher the intent of the end-user.

When it works well, the chatbot can quickly pick up on intent and provide a calculated response. The response could be in the form of a generic text reply or retrieved from an information database. Often, these responses are stored in complex enterprise systems designed to mimic human communication and provide a robust and massive list of possible answers. When it works best, a chatbot is a glorified indexed, user manual.

The Flaw of the Chatbot

Unfortunately, end-user intent is often murky and implied. The end-user intention is partly why so many people seem to get frustrated with chatbots. If it cannot pick up on it, then it must ask probing and often repetitive questions. Once the chatbot gets to this stage, its usefulness quickly diminishes. Many of us have experienced being stuck in a loop with an underdeveloped AI that lacks enough information to provide us with the answers we need. And because it can’t say “I can’t help you,” it continues to regurgitate probing questions to find an answer it may not have.

The problem here is that the end-user intent is not often clear. The framework of the AI restricts the chatbot. It must decipher end-user intent, and it must do so by using one of a variety of strict and predetermined strategies. Thus it is stuck playing by the rules of its creator.

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Making Chatbots Work For You

In the best of circumstances, a chatbot is a powerful bridge between people and services. Ideally, a chatbot can provide a superior customer experience without the high costs often required to get there.

With this in mind, it can be a great addition. It can help redirect customers to the right place. If an end-user doesn’t dig too deep, they can receive the illusion of authentic personal assistance.

But there may be a problem. The code behind a chatbot is almost too easy to acquire. There are innumerable software options available to give any old website the quick chatbot feature. The result is that a lot of similarly-functioning (and flawed) chatbots are flooding the webosphere.

If consumers universally consider chatbots to be pointless, their impact is damaged. Everyone will close the box and continue if it didn’t help the twentieth time - it certainly won’t help the twenty-first time.

The Future of Automated Communication

The damage, however, isn’t irreversible. There are serious and legitimate attempts to improve the primary benefits of the chatbot.

Developers are adding new approaches to improve the vast language pool of the chatbot. Some of these include natural language processing, machine learning, and semantic understanding.

Natural language processing (NLP) may be the most influential. As opposed to closing in on specific keywords, this method relies on the natural voice. It reads the full text, potentially picking up on tone and syntax to provide a more thoughtful and personal response. The response, instead of pointed and non-naturalistic, is more nuanced and authentic. In other words, it sounds more human.

The method has been used in personal assistant applications, Google Translate, and Microsoft Word. NLP even has the potential to decipher sarcasm and other ambiguous elements of human language.

We are a long way from perfecting this system, but it is helping to lead chatbots down a more viable road.

Human Intervention

The most impactful may also be the most obvious - the human touch. Chatbots, in some of their best forms, are simply introductions to a human conversation. A chatbot could help isolate the concern, but it may not always resolve it. A human can intervene and continue the conversation to its conclusion. The most obvious is the use of call funnels. When you make a phone call, you are directed to specific funnels that help narrow down your area of concern. A more nuanced version of this could take priority.

Summary

Regardless, chatbots are at an exciting crossroads. Are they frustrating? Sometimes. Can they be the future of online communication? Perhaps. To navigate a successful route, organizations need to ensure that they have the talent and the resources to create the right solution for their businesses.

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Topics: AI, Artificial Intelligence, Customer Experience, Digital Transformation, Natural Language Processing