What is chatbot used for?

Chances are it was a voice chatbot with a pre-recorded conversation script.

Personally, I hate those things!

Many shady companies use “phone call bots” and “automatic robot dialers” for mass-marketing frauds.

Still, not all chatbots are bad! From voice assistants like Siri to virtual support agents, they are becoming a key technology of the 21st century.

But what is a chatbot anyway?

In this article:

Explore Tidio’s chatbot features and benefits, visit our page dedicated to chatbots.

Once you become familiar with chatbot technology, it’s also worth reading:

You can jump straight into the action, too.

Now—

Let’s start with the basics and define chatbots.

Do you remember the last time when you were trying to reach your bank or mobile network operator?

You probably heard something along the lines of:

You have reached [Company Name]. Thank you for calling.

If you want to reach our customer support, press 1. If you want to turn selected services on and off, press 2. If you want to…

You get the idea, right?

This type of automatic attendant service could be considered a very primitive form of a voice chatbot.

Here is an example of a modern customer service chatbot used by a restaurant:

You can interact with this advanced chatbot and book a table, browse the menu, or order food. It is designed in a way that is easier to navigate than a traditional website. This is especially true if you are using a mobile device!

Looking for more chatbot use cases?

OK—

Chatbots seem like a cool thing to play around with.

But what is the purpose of chatbots? Why do companies use bot assistants instead of offering a more personal (human-based) customer service?

Here are some obvious benefits of using chatbots:

Their primary goal, in general, is to facilitate human-computer interaction.

On top of that, this new technology is becoming extremely popular. Over 1.4 billion customers have already used a chatbot!

If you need more, read: Business Case for Chatbots: 10 Reasons Why You Need Them

This looks impressive. Are there any downsides to chatting bots, though?

Well, if users genuinely want to solve their problems, chatbots work fine. But if someone just wants to find out how to break a chatbot and is not cooperating with AI, it is easy to confuse a bot. Your virtual assistant may fall victim to mischievous users who find provoking it funny.

Virtual assistants cannot improvise, defend themselves, or react in a way a human live chat would. But, on the other hand, nobody’s feelings are hurt. Sometimes using bots is the best way to deal with angry customers.

At the end of the day, the advantages of support bots far outweigh the potential risks and downsides. But how do chatbots work? Are all chatbots equipped with artificial intelligence? Does using them mean that I can’t have human agents?

Let’s find out more.

Some chatbots use natural language processing (NLP) to recognize the meaning of the messages they receive. Developers use advanced machine learning algorithms and huge amounts of user conversation data to train AI chatbots.

Real-time natural language understanding (NLU) is a powerful tool. And you don’t need to be a developer to use it. Let’s take a look under the hood. This is what the bot looks like in the chatbot builder.

You don’t even have to write a single line of code to make a project like this. You can design new conversations by connecting triggers and actions. To recognize the meaning of messages automatically, all you have to do is define the language and topic of the conversation.

Other chatbots use simple decision buttons that are based on common questions. For example, here is a Facebook Messenger chatbot that offers a ticket discount.

Phare Circus uses the same solution for live chat, bots, and multi-channel automation.

The majority of customer support automations use simple decision tree diagrams or conversation flowcharts.

It may be difficult to perfectly simulate human interactions with a computer program. But, unless you want to pass Turing’s AI test, it should be more than enough for the majority of typical online situations.

Read more: What Is the Difference Between Conversational AI and Chatbots?

Today, chatbots can carry on entire conversations. Some people even fell in love with virtual companions such as Replika.

But, most of the time, chatbots help businesses with their day-to-day operations. For example, I happen to receive automatic bot messages from Slackbot that remind me about the deadlines for my articles! Would you believe it?

Chatbots help to streamline customer service, marketing, and other business processes.

Here are the basic types of chatbots:

If you want to get your own chatbot now and learn how to use chatbots, you can choose between:

Conversational bots are extremely popular, especially among the younger generation of online shoppers. About 40% of Millennials interact with bots on a regular basis. They provide seamless, conversational shopping experiences.

Here is an example of a customer service bot in action:

It can handle the most typical customer service scenarios on its own. Or it can notify live chat operators if an unusual problem occurs.

Virtual assistants that use artificial intelligence and NLP increase customer satisfaction by:

It is like having a super-hero customer support agent on your team. And there are many providers and chatbot alternatives to choose from.

Read more: Check out different chatbot types and determine which ones can help enhance communication with your customers.

Chatbot subscription messages are far more effective than traditional lead generation popups. Old-school popup ads are extremely intrusive, and 73% of online consumers hate them. With a chatting bot, it feels more like a conversation. And it is easier to encourage someone to speak to you, tell something about themselves, or answer a question.

You should try out several designs for different stages of lead qualification.

Are chatbots effective? You can read an inspiring business story of Whisker Bag. The owners created fully automated customer service and advanced lead qualification flows.

Read more: Best Lead Magnet Ideas

Chatbots are not just a technology for streamlining sales and customer service. They are a great alternative to customer feedback surveys, too.

Imagine a situation where a customer of your online store has a full shopping cart. They browse the store and visit different subpages. They spend a lot of time on your website. Despite that, they do not finish their purchase.

What went wrong?

You won’t know until you ask. And chatbots happen to be made for this job.

You can trigger chatbot conversations with any event on your website. Collecting customer feedback at the right moment is essential for learning more about your customer base. And for finding problems that they may have with your services or products!

You can start it when:

You can also create custom chat triggers with Tidio chatbot APIs.

Read more: Learn about the new Tidio AI features and how they can help your business.

Keeping customers happy is more important than ever. But human customer service agents can be costly—compared to automated support and self-service tools.

What can chatbots do?

Natural language processing solutions are becoming more commonplace and intuitive to use. Consequently, companies are discovering what automation can do for their business. They learn that:

It’s not hard to put two and two together. If customers can find the information they are looking for faster, they are more satisfied. Even more so when they can get help without getting human agents involved.

At a technical level, a chatbot is a computer program that simulates human conversation to solve customer queries. When a customer or a lead reaches out via any channel, the chatbot is there to welcome them and solve their problems. They can also help the customers lodge a service request, send an email or connect to human agents if need be.

If this reminds you of a telephonic customer care number where you choose the options according to your need, you would be very correct. That phone tree is also a chatbot, though a very primitive one. Modern chatbots do the same thing by holding a conversation with customers. This conversation may be in the form of text, voice or a hybrid of both.

Chatbots are conversational tools that perform routine tasks efficiently. People like them because they help them get through those tasks quickly so they can focus their attention on high-level, strategic, and engaging activities that require human capabilities that cannot be replicated by machines.

• Menu/button-based chatbots.
• Linguistic Based (Rule-Based Chatbots)
• Keyword recognition-based chatbots.
• Machine Learning chatbots.
• The hybrid model.
• Voice bots.

A chatbot (coined from the term “chat robot”) is a computer program that simulates human conversation either by voice or text communication, and is designed to help solve a problem. Organizations use chatbots to engage with customers alongside the classic customer service channels like phone, email, and social media.

Chatbot popularity is on the rise. Organizations have increased their adoption of chatbots — often powered by artificial intelligence (AI) — by nearly two-thirds since 2018, according to Salesforce’s State of Service report.

In the workplace, businesses use chatbots to boost agent productivity and efficiency in a range of ways. Chatbots provide service teams the information they need quickly, serving up relevant resources even as the customer conversation changes. Chatbots also speed up self-service options for customers and resolve common issues such as checking claims status, modifying orders, and answering billing questions.

In this article, we learn about chatbots, explore their impact on customer service, and discuss how leaders can take advantage of this technology.

As we mentioned, a chatbot (or the affectionately coined chatterbot) is a computer program that digitally engages with customers and visitors either by voice or text communication to help find a resolution or solve an issue.

Chatbots can be customized and used in a variety of ways. Most of us as consumers are familiar with bots for customer service. They’re also used with popular chat and messaging platforms like SMS, Facebook Messenger, WhatsApp, and WeChat.

With chatbots, people can have a conversation or interact with a software program that helps them find answers quickly. Most importantly, a chatbot can influence a customer relationship by responding to requests faster while meeting customer expectations.

With the potential for delivering instant responses around the clock, chatbots free up customer support teams to apply their emotional intelligence and time to more complex issues.

One of the earliest examples of a chatbot was a program called ELIZA, built by Massachusetts Institute of Technology professor Joseph Weizenbaum in the mid-1960s to simulate a psychotherapist. Using keywords and pattern matching, ELIZA responded to a user’s typed questions with simple open-ended replies, based on a script.

Over the years, developers have incorporated more sophisticated techniques to enable chatbots to better understand questions and provide more useful responses.

While today’s bots still can’t handle all customer queries, they can respond to frequently asked questions or perform straightforward tasks.

“Out of the pool of problems your customers have, there are some that are best suited for a talk with a human,” wrote Greg Bennett, director of conversation design at Salesforce. “But that’s not something as common as ‘reset my password.’ Agents’ time is precious, so save it for the complex stuff … Let the chatbot take care of the simpler jobs.”

The simplest form of a chatbot system parses customer input, then scans its database for articles related to certain words and phrases. In short, it operates like a document-retrieval system based on keywords.

Chatbots follow the rules that they were given. Rules-based chatbot software executes pre-programmed actions based on configuration by the developer.

Rules-based chatbot technology acts based on click actions, like a customer answering “yes” or “no,” or by recognizing a particular keyword or group of keywords. For example, a cosmetics company might create a bot that questions users about their makeup preferences, then recommends products and offers that match their responses. In these cases, the computer program behind the chatbot sticks to a strict set of predefined rules and has little ability to recognize the way people naturally speak.

Think about the times you may have typed a question into a website’s dialogue box and received an answer that didn’t make sense. That’s likely because the chatbot program recognized keywords in your request, but not the context in which they were used. That’s where artificial intelligence chatbots come in.

Chatbot systems have become much more sophisticated, thanks to significant advances in the field of artificial intelligence (AI).

Artificial intelligence chatbots are programmed to have human-like conversations using natural language processing (NLP) or natural language understanding (NLU). In particular, developers are using NLP to build bots that can better understand human speech and talk-to-text. These technologies also make it possible to better understand the intent behind what is being said and to respond more intelligently.

With AI, the chatbot can interpret the context as it is written, which enables it to operate more or less on its own. In other words, AI chatbot software can understand language outside of pre-programmed commands and provide a response based on existing data. This allows visitors to lead the conversation, and the bot to follow.

By harnessing enormous amounts of data and low-cost processing power, AI and related technologies such as machine learning help to dramatically improve the chatbots’ quality of understanding and decision-making.

When chatbots connect to technologies such as NLU, they can learn more complex ways of simulating human conversation, such as:

An AI-powered bot can also be trained to actively learn from any interaction with a customer to improve performance. Yes, that’s right, they are programmed to get better.

For example, such systems can be trained to recognize customer frustration and escalate problems to the company’s support center.

Of course, a chatbot doesn’t need AI-powered features to be a useful support channel. The advantage is, however, that the more the customer interacts with the bot, the better its recognition system becomes at predicting the appropriate response.

As mentioned, chatbots save time for both customers and agents. About 77% of agents say that automating routine tasks allows them to focus on more complex work.

AI chatbots can be custom-built to meet a range of specific needs in both business-to-consumer (B2C) and business-to-business (B2B) environments. Already, 38% of decision makers say their organizations use chatbots. Here are the most widely used business cases:

Automation, including the implementation of AI-powered chatbots, also helps service teams with increasing customer demands. Repetitive, manual tasks slow agent productivity and frustrate customers.

Automating communication workflows can be the key to doing more with less — leading to empowered agents, happier customers, and cost and efficiency savings.

Automation with chatbots speeds things up. The majority of service professionals describe the following activities as mostly automated:

In the examples above, AI is used to augment human skills, rather than replace them. Empathy still matters. For the toughest problems, customers prefer to speak with an agent.

“Companies are not going to abandon human agents in favor of chatbots,” said Sheila McGee-Smith, founder and principal analyst at McGee-Smith Analytics. “But they are going to continue to deploy them for simple interactions and work to make it easy for consumers to reach out to a human agent when required.”

A survey by McGee-Smith found that 82% of consumers are willing to interact with chatbots if they can escalate to a live agent.

The short answer is yes. Digital disruption is raising customer expectations. Consumers and business buyers are more informed and less loyal than their predecessors. They’re looking for personalized experiences based on trust and understanding, and they will shop around to find them.

Out of 7,000 customers asked in the State of Service survey, 80% agreed that the experience a company provides is just as important as its products and services, and 82% of customers expect to solve complex problems by talking to just one agent. The standard for quality, efficient experiences is higher than ever.

Chatbots also reduce costs by enabling self-service in simple scenarios, delivering relevant information faster, and improving the customer experience.

That’s where AI-powered chatbots come in. While chatbots can’t replace humans, they help speed up the customer support experience by answering easy questions. They also collect important information that agents need to solve a case quickly.

More specifically, AI chatbots help companies deliver good customer service in the following ways:

A popular tactic for relieving agents of high-volume, low-complexity cases is deflection, or how fast automated resources can satisfy customer demand. Nearly two-thirds of service professionals credit self-service with easing case volume.

AI chatbots offer enormous potential when it comes to scaling personalized experiences. Personalization becomes even better as they get to know customers and use AI to predict their next action. For example, a customer wants to purchase a pair of shoes. The chatbot can personalize the conversation by adding their name throughout the chat and suggesting complementary accessories to go with their shoe style choice.

Customer service leaders use chatbots with customers and within their own organizations. Here are a few examples of successful chatbots.

Peloton’s chatbot analyzes customer issues and connects them to support from relevant teams to resolve tickets quickly with higher customer satisfaction.

Capital One’s chatbot Eno (“one” spelled backward) communicates with a bank for a customer via text message to help them carry out transactions.

JPMorgan Chase’s COIN, a chatbot analyzes legal contracts exponentially faster than human lawyers can. COIN can also grant employees access to software systems and handle common IT requests.

For customer service teams, Salesforce’s Einstein AI included in Service Cloud delivers AI-powered contextual recommendations.

And here are some successful chatbots blazing the trail across many different industries.