What Is a Chatbot? How It Works, Types, & Reasons for Adoption
Chatbots can be a powerful addition to any tech stack.
They streamline interactions between consumers and brands and enable companies to improve the customer experience, reduce operational costs, and increase online conversions.
In this guide, we’ll answer the question, "What is a chatbot?" before digging into critical use cases, benefits, and barriers to adoption.
A chatbot is an automated conversational interface designed to communicate with users by simulating human-to-human conversations—either through voice commands or text.
Chatbots can be on a range of channels—mobile apps, websites, social media platforms, SMS, etc. for many different use cases, including customer service, processing transactions, lead qualification, and more.
It’s also worth noting that while many people define chatbots as a form of artificial intelligence, that’s not really accurate. Some chatbots—known as rules-based chatbots—operate on a system of triggers and actions defined in advance. While this is a form of automation, it’s not AI.
AI chatbots, on the other hand, are designed to provide a more conversational experience. These bots use machine learning (ML) and natural language processing (NLP) to recognize language, learn patterns, and make decisions. They are continually building on their existing knowledge, and if given accurate, complete data sets, they get "smarter" over time.
Chatbots are becoming increasingly important to the customer experience. They allow brands to reach customers on their preferred channel and quickly offer support.
According to a Microsoft report, 56% of people say they’d prefer to message customer service than speak to someone on the phone.
Gartner found that over 40% of live service interactions could be resolved using self-service channels—which includes chatbots, as well as knowledge base content and tutorials.
An Aberdeen Group study found that businesses with strong omnichannel engagement strategies were able to retain, on average, close to 90% of their customers. Those without an omnichannel strategy retained just 33%. What’s more, brands investing in omnichannel experiences reported customer satisfaction rates 23x higher than those that did not.
Chatbots are shaping up to be an enabler of seamless omnichannel experiences that customers now expect. They’re channel-agnostic and can help create a cohesive experience across all pages and platforms.
This graphic breaks down the how chatbots can be used to bridge gaps between channels:
As mentioned, chatbots break down into two main categories—rules-based chatbots and AI chatbots. Here’s what that actually means:
Rules-based chatbots execute sequences of pre-defined actions created on the back end. You create a specific sequence (or playbook) for each page/channel where you’re planning on using a chatbot.
Rules-based chatbots can act based on various triggers—including specific keywords or keyword groups, clicks, or how someone answers a question. A couple examples:
A bot asks something like, "Do you work in sales or marketing?," and when the visitor selects "Sales," the bot might direct that person to a page explaining how a solution caters to sales teams.
A visitor types, "I’m looking for women’s hiking boots" into the chat window. The bot then offers some options based on the keyword "hiking boots" and the category "women’s."
With rules-based chatbots, all possible user queries and potential answers are defined in advance.
That means brands must know exactly what questions visitors ask and understand what they’re looking for when they enter those queries. Because rules-based chatbots are incapable of learning or making decisions on their own, they’re best used in situations where there’s only one right answer.
A few examples:
A banking app might use rules-based chatbots to answer questions like "How do I find my routing number?" or "How do I set up bill pay?"
A company selling sales software might use a rules-based chatbot to help users navigate its knowledge base by surfacing tutorials and guides related to keywords like "Create a report" or "Customize my dashboard."
An e-learning app might use this type of chatbot to help with user onboarding or help users locate specific lessons.
Ultimately, it’s better to think of rules-based chatbots as more of a guided search function than a conversation between human and machine—a way to get people the information they need as quickly as possible.
Conversational chatbots are AI-enabled chatbots that use ML, NLP, and big data to simulate human interaction. This type of chatbot goes beyond translating content into canned responses, it can interpret user intent, provide contextually relevant answers, and process requests.
Unlike rules-based chatbots, conversational bots understand the meaning of words and misspellings. They also "remember" past interactions and adapt to user behavior and preferences.
A few examples of how you might use conversational chatbots:
Customer service. Conversational chatbots can answer questions when your agents aren’t available.
Product support. They can help customers with product research and offer product recommendations. Here’s an example that shows a Facebook Messenger bot helping a customer find a new computer:
Lead generation. Companies can use conversational chatbots to attract potential customers. They can turn anonymous traffic into leads by greeting them upon arrival and adapt messaging based on pages or products they’re looking at. They can also be used to generate leads from other channels—instead of a traditional landing page, CTA buttons can send qualified traffic to Messenger or your website’s resident bot.
Nurture prospects through the sales process. Chatbots can quickly identify customer needs and help them navigate your website based on where they are in the sales process, persona type, interaction history, etc.
Completing simple tasks. Chatbots also make it easy for customers to sign up for an insurance plan, cancel a lost credit card, book a hair appointment, and more.
To truly answer the question, "What is a chatbot?", it helps to take a closer look at the underlying software and technology.
Modern chatbot solutions leverage AI, machine learning (ML), and natural language processing (NLP) to deliver insights in real-time. These technologies can analyze data in an instant and recommend the actions most likely to produce the desired outcome.
While there’s more to it than this, AI chatbots communicate through channels like your website, socials, mobile app, etc., which are linked to a knowledge base and all connected data sources through the NLP layer.
Natural language processing is the ability to analyze and interpret human speech so that chatbots offer the right response in context.
NLP aims to make chatbot interactions feel like a conversation between two people and breaks into two key processes:
Natural language understanding (NLU). This describes a chatbot’s ability to understand human speech and translates it into structured data the software can understand—intents and entities.
Intents represent the user's goal—so, finding information or performing a specific action.
Entities complement the intent and describe details like dates, sizes, location, etc.
Natural language generation (NLG). NLG is responsible for translating that structured data back into text.
Before the chatbot delivers a response, it uses an XML dialect known as Artificial Intelligence Markup Language (AIML) to identify patterns and correlations in your data so it can deliver contextually relevant answers.
So, if a customer enters a query in Messenger, the NLP layer first translates it into intents and entities. Then, it runs that data against behavioral data, usage history, etc., to identify patterns that help it deliver the best possible response to an individual user.
In recent years, we’ve begun seeing chatbots move into a more strategic role.
They’re capturing data, offering personalized experiences, and handling transactions—they’re also getting better at understanding human queries in context.
And like so many other technologies, the coronavirus accelerated chatbot adoption—chatbots played an instrumental role in helping companies and their customers navigate new challenges brought on by the pandemic.
Here’s a look at some of the core benefits that chatbots bring to the table:
According to IBM, chatbots are great for quickly responding to simple service requests—like logging sales data and booking appointments. In fact, they may even reduce customer service costs by as much as 30%
For customers, AI chatbots offer several benefits. They instantly answer common questions—shortening the time to resolution, while allowing agents to focus on solving problems that require empathy or out-of-the-box thinking.
They also help customers help themselves, offering a sense of self-sufficiency and eliminating the need to call the service line or wait for someone to get back to them via email.
Chatbots don’t just streamline interactions on the customer-facing side, they also help front-line agents work more efficiently and effectively. Agents can use intelligent chatbots to quickly pull information from distributed data sets and address each interaction in context—and in real time.
AI-enabled chatbots can also provide guided recommendations or suggested next steps to help live reps deliver the best possible solution without missing a beat.
According to Accenture, 75% of customers are more likely to buy from brands that acknowledge them, remember past interactions, or offer relevant recommendations.
Chatbots enable brands to personalize many aspects of the customer experience—at scale. For starters, customers no longer need to download an app or visit a company’s website. Instead, AI bots can engage customers on their turf—SMS, Messenger, WhatsApp, or phone.
Here’s an example of how chatbot flows might be used for different user segments in a retail setting.
Unlike human employees, chatbots never sleep, they don’t get sick, and angry customers can’t bring them down.
While it’s worth noting that chatbots can’t fully replace human agents, they can answer basic questions and handle tasks that don’t require a human touch—think providing business hours, booking an appointment, or processing a return.
Chatbots ensure that customers always receive the on-demand response they’re expecting—24/7. Chatbots can complete simple tasks or book a customer call with a live agent at a time that works for everyone.
Chatbots also happen to be an amazing gatekeeping tool.
Lead generation chatbots, sometimes called "lead bots" can be used to:
Capture incoming leads
Qualify leads by asking a series of questions
Guide leads through the conversion funnel
Reduce friction throughout the purchasing process
Address visitor queries in real time
Proactively present relevant information
Route prospects to human sales reps at the right moment
If you’re using JivoChat, you can assign live agents to specific channels based on criteria such as role, location, territory, or availability.
That way, when qualified leads are ready to talk to a human rep, they’ll be routed directly to the person most likely to meet their needs.
For example, if a visitor wants to get an estimate, they’d typically need to fill out a form and wait for someone to get in touch. It could be an hour or several days before someone contacts them—by which point, the prospect may have already moved on.
A chatbot can provide pricing information, recommend content, and help leads book an appointment when they’re ready. If it’s still early in the buying process, they can capture contact information and pass it along to a live agent.
Building on our last point, chatbots aid in the sales process by asking qualifying questions, then providing relevant information based on how the user answers.
They also reduce the amount of time it takes to complete a sale.
If a customer might be ready to purchase an item, but they have a few questions they’d like to answer before pulling the trigger. The chatbot can quickly provide that information, then direct them to the checkout process to complete the transaction.
Finally, for companies selling "high-consideration" products, chatbots can guide decision-makers to the right information based on where they are in the sales process, and other data points like industry, location, size, and role. That way, buyers don’t have to search through information they don’t care about and can move through the funnel much faster.
So, if they’re unsure about a product or have a question about the return policy, the chatbot can step in and clear things up—thus giving them the information they need to complete the transaction.
Chatbots can also be deployed on external channels like Facebook or WhatsApp, allowing brands to follow up on abandoned items on the platforms customers use every day. What’s more, they enable customers to complete the transaction without taking them to a second location, increasing the chances they’ll follow through this time around.
For sales and customer service teams, chatbot insights tell them what to do next, allowing them to focus on infusing each interaction with empathy and creative problem-solving.
Marketing teams can capture insights not found in typical reporting tools. Chatbot data can tell you how people ask questions, identify themes, and understand which types of messaging resonate best with different segments.
Because chatbots can take on many customer service tasks and are available around the clock, companies have an opportunity to reduce costs—they can get more done with fewer agents and make the most out of the talent they have.
According to a 2019 Juniper Research report, chatbots could save both brands and customers up to $2.5B by 2023. The firm also predicts that companies using chatbots will collectively save around $8B in operating costs by 2022.
Chatbots are fast becoming the MVP of the customer service stack. They’re making it easier for brands to personalize the customer experience and deliver faster, more consistent support across multiple channels. At the same time, many companies still hesitate to embrace the technology for a number of reasons.
Here’s a look at some of the barriers to chatbot adoption:
Security concerns. Organizations need to ensure the data captured by chatbots is secure and safely transmitted. They also need to make sure to only collect relevant information and obtain customer consent. With regulations like the CCPA and GDPR, the risks of getting this wrong are becoming higher and higher. And as a result, many businesses are hesitant to test an unfamiliar technology.
Brand consistency issues. Another challenge is making sure that chatbots maintain a consistent voice across all channels—but also, that bot communications reflect different personas and situations.
Ensuring bots understand sentiment and intent. Customers expect chatbots to bring some level of humanity into the mix—empathy, humor, the ability to read the room. At the same time, they don’t want to be tricked into thinking that they’re interacting with a person. Organizations need to focus on implementing chatbots with NLP capabilities—though they’ll need to have a clean, connected big data ecosystem for that to happen. And as you might imagine, many companies struggle to move past that initial step.
A few years ago, conversational chatbots were a big investment. Businesses had to invest in expensive tech, AI experts, and spend months (even years) training the algorithm from scratch.
Today, organizations can build custom chatbots with software that comes with pre-set algorithms. Platforms are easier to use, more affordable, and can be up and running ASAP.
Chatbots are a technology that’s already helping businesses bridge the divide between communication channels and improve the customer experience from all sides. Chatbot trends include:
Using Messenger bots for engagement. In a recent expert roundup, respondents told Chatfuel that they see social messaging apps like WhatsApp, Facebook, and Instagram evolving beyond basic customer support and into an enabler for creating meaningful relationships.
Chatbots as a knowledge management tool. Chat Mode’s Head of Consulting, Chad Oda told Landbot he expects more brands to start using chatbots as a knowledge management tool. He explains that building a chatbot layer on top of an existing knowledge base makes it easier for customers to extract information. It’s a simple solution that offers a tremendous impact on value.
Chatbots for internal use. Companies are increasingly looking toward chatbots to improve internal functions like recruiting, onboarding, IT, HR, and more.
Chatbots powering customer engagement hubs. According to Gartner, brands are building customer engagement hubs (CEHs), which connect multiple systems and channels together to engage customers on their terms.
Chatbots play an important role—and when combined with good data and human agents—they allow brands to provide proactive and reactive support, and engage customers in context.
Chatbots offer a wealth of benefits for businesses of all shapes and sizes—and they’re only going to get better. As you can see, brands are finding new ways to deliver value — from improving internal workflows to offering personalized social shopping experiences.
At the same time, companies need to know how to use this technology to extend human capabilities rather than attempt to replace them.
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