Jul 13 2021
Data Analytics

Which Type of Chatbot Is Right for Your Business?

Powered by machine learning, these conversational agents can streamline processes and improve customer service. But how do they work, and how can businesses choose?

Spending on chatbots is up — way up. The market for these machine learning–driven conversation creators will see more than $1 billion in growth this year, and 50 percent of companies will likely spend more on chatbot creation than mobile development in 2021.

But what exactly is a chatbot? How do they work, what types exist, and how can enterprises effectively implement these solutions? More important, which type of bot is the best fit for your business needs?

Here’s what you need to know about capitalizing on chatbot connections.

What Is a Chatbot?

According to Ramsés Gallego, international CTO for CyberRes, a MicroFocus line of business and member of the ISACA Emerging Technology Advisory Group, “a chatbot is a software application that is designed to interact with the user mimicking humans by providing a service, answering a question or indicating the next step of a process. They are also called 'conversational agents' because they are usually designed to simulate written or spoken conversation and guide the customer to a solution or answer to an issue.”

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In effect, chatbots offer a first point of contact for customers. While they’re not yet capable of accurately duplicating the entire range of human conversation, they provide a way for companies to reduce contact center or customer service costs by offloading easily answered inquiries to automated processes.

Chatbots typically comprise two parts: a natural language understanding (NLU) platform to parse customer requests, and an API connecter service to link with key external systems.

How do Chatbots Work?

Machine learning is the core of chatbots. “At the heart of chatbots, there are a number of algorithms that can interpret what the customer is trying to say or do,” says Gallego. “By monitoring his or her behavior or simply by requesting what is being attempted, the chatbot has different rules and decision-making procedures that can guess what the human being wants to do and provide a solution to make it happen. Some next-generation chatbots can even do the action themselves, but that requires human approval and is more of a 'bot' — that comes from the word 'robot' — than a chatbot.”

Just as the ML connection suggests, chatbots can learn over time by repeated exposure to human interactions. The most common types of learning are supervised and unsupervised: Supervised algorithms teach chatbots through provided examples, while unsupervised ML frameworks allow bots to learn through in situ observation.

WATCH: See how to use artificial intelligence to drive business initiatives.

Chatbots are also getting better at understanding human emotion by using natural language processing. Equipped with advanced NLP algorithms, Gallego notes that “chatbots can provide an answer in a natural way and can even ‘feel’ subtle variations in tone of voice or the way the request is written.”

What Are the Types of Chatbots?

Chatbots fall into three broad categories:

  • Holistic: These bots handle the entire interaction, start to finish, without an option for customers to directly connect with an agent. Services requiring human help will be directed to alternative methods of contact. Holistic bots offer entry-level answers to common questions.
  • Handoff: This type of chatbot takes the lead and then offers to connect customers with an agent once it reaches the end of its capabilities. The challenge? This may lead to significant waiting times if agents are busy.
  • Hybrid: Hybrid solutions use chatbots up front, with agents monitoring the conversation on demand. When human help is needed, agents are alerted and given a history of the interaction to help guide ongoing discussion.

In practice, Gallego says, “chatbots are quite common in any sales process where the customer needs some advice or guidance. They are supercommon in service desks or customer interaction centers because they can filter a large number of requests with zero human involvement, and then pass the request on to experienced, knowledgeable humans when needed.”

How to Implement a Chatbot

“Chatbots can be implemented in different ways,” says Gallego, “but the most common is putting them in the cloud and freeing them from any on-premises deployment. That way, chatbots are always ready, 24/7/365, to help users on any device or platform, anywhere, anytime.”

While on-premises deployments are possible if companies want to keep chatbots closer to home, Gallego notes that this can cause challenges over time. “Although they are not heavy in size,” he says, “they can get heavy if visual solutions and documentation have to be provided as part of the answer. If they have to guide the customer through a process with a video, for instance, then the total size of the chatbot can be huge.”

As a result, cloud-based implementation is the preferred solution for most organizations.

What Are the Best Chatbot Software Solutions?

The best chatbot software solution depends on your use case and business needs. While there are free-to-use bots and startup companies creating bots, both security and customer satisfaction are often better served with robust NLU platforms such as those offered by Google, IBM, Amazon and Microsoft, all cloud-based solutions.

The future of customer service is conversational. The right chatbot solution can help companies reduce costs, boost satisfaction and set the stage for ongoing automation.

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