What Is a Chatbot? Types, Use Cases and How They Work

Chatbots have gained extreme popularity in recent years with the advancements in Machine Learning and natural language processing. The internet works like a platform that creates a web of information that helps the bots to gather this information and respond accordingly. This makes them utterly useful! Everything today works on data and information, for instance, machine learning or its advanced version i.e. Augmented Analytics. With the increased online data and information, companies are now relying on cloud computing as a source of data storage or other services that could be provided using a remote/virtual computer. Before we get into all the technological stuff, let’s have a general idea of what is a chatbot.

What is a Chatbot?

A chatbot has various other names such as Conversational bot, Chatterbot, Interactive Agent, Conversational Interface, and Conversational AI. A chatbot is a computer program that conducts a conversation convincingly simulating a human behavior as a conversational partner. These bots are often designed in a way to be used in practical purposes like Customer services or to gather information. A chatbot is typically used to communicate with humans but with more and more advancements in the field, apps are being built on which two bots can communicate with each other. Generally, chatbots are used in the ecommerce industry, call centers and in internet gaming. This limits the chatbot’s functionality to a specialized range of people. To make you understand this better, let us take an example that would help you visualize the need of chatbots; If you want to buy a t-shirt on Amazon, you would go to their website, look for what you want and then make a purchase once you find what you were looking for. This is a mediocre online shopping experience. Now imagine Amazon has bots, you could simply send a message to Amazon using Messenger and tell the bot what you want and the bot will send you the results that match your requirements. This will definitely clear your thoughts on what is a chatbot. You may like to read: Unicorn Company: Billion Dollar Startups Going deeper into the technical part of ‘what is a chatbot?’ AI chatbot uses natural language learning systems, while some use simpler methods like scanning for keywords and replying accordingly from a database. Chatbots are commonly offered in two ways such as web-based apps or through standalone apps. Natural language processing (NLP) is the core of chatbots. It is also used in the working of ai voice recognition systems like Apple’s Siri and Microsoft’s Cortana. However, chatbots generally work on the text. It interprets and defines the terms entered by the user and then determines a series of responses based on the information researched. It should always be kept in mind that chatbots are not the same as NLP, although it is very well understood that it is a further developed form of NLP. As it is said, every coin has two sides; even chatbot technology has two sides. It has its own drawbacks but in spite of that, chatbots have gradually progressed to be more sophisticated, user-friendly, responsive, and more natural (more human).

“Human in the loop”

Human in the loop means the chatbot is monitored and manually taken charge of by a human when needed. This generally comes in the picture when a chatbot fails to understand the end user's request and the human agent can quickly intervene and take over. But there are many other points to be considered before you make up your mind to implement this method. Let us throw some light upon those;

• Chatbots can generally be used in the customer service section, as they could save up a lot of time and effort by answering the simple and repetitive questions.
• You shall decide whether you want your chatbot and the human agent as separate participants in the chat.
• One of the main reasons of having them as separate participants is to avoid breaching the privacy policy as your end customer might not mind sharing the sensitive data with a bot but have a problem sharing it with a human agent.
• A reason to not show them as separate participants is to build the trust of the end-user on the bot as in their eyes it would perform better than expected.
• Again timing might be an issue here, as humans cannot answer as fast as the bots hence the shift might be suspective.
• Also, keeping them as separate participants will mean the human agent will have no track of chat history of the bot and the end user.

Hence, as a solution to this, the best possible way in the current scenario is to give the end user a choice during the conversation to connect to the human agent. This could solve the above issues. Chatbots are becoming more and more common these days because it has become very easy to build your own chatbot with the help of various available chatbot companies out there. You may also like to read: How does Craigslist Make Money? A Complete Walkthrough

What Chatbots can do?

Chatbots are a medium of engagement between the customer and the brand. In the near future, Chatbots will have an immense effect on the startups and savvy companies by improving customer engagement.

• A chatbot can improve customer service by answering the customers instantly and it could save the time of employees by answering the repetitive questions and also save customers from going to the FAQ which we all know is tiresome!
• It can help in streamlining the shopping process. As we discussed in the example, the customer can tell the bot what they want and the bot can check the same with the sales team. It could also memorize the preferences of returning customers.
• It ensures 100% response rate and this could lead to a greater conversion rate. No more unanswered messages.
• It enables personalized communications. The chatbots emphasize the specific questions of the customers and pay attention to the customer’s needs instead of just marketing the features provided by the company.

After reading about what is a chatbot and what chatbots can do, you must be wondering if chatbots come in different shapes and sizes. Well, to clear all your doubts, continue reading to find out more about types of chatbots.

Types of Chatbots

Not all chatbots respond in a conversation the same way. You may have noticed that some chatbots respond to your quests in a humane way whereas some may literally sound robotic and are unable to answer like an ai chatbot. To understand these different behaviors you must know the types of chatbots. There are majorly three types of chatbots. Take a look at those down below;

1.Scripted Chatbots:

This type of chatbot is determined by rules. They behave in a predetermined way. The user gets explicit choices to respond to, to continue the fixed path of the conversation. Each step of the conversation depends on the features of the chat platform and how the chatbot is programmed and designed. You may like to read - Amazon business model

2.Intelligent Chatbots:

This type of chatbot is built using artificial intelligence techniques. In this type, the users do not face limitations in terms of input. The AI chatbot is flexible in terms of the user input. AI enables the chatbots to improve more as per their usage. But it should be very well kept in mind that these bots have a limited capacity and it is difficult to get the bot to understand the context or to have useful memory. These chatbots work on a keyword. They identify the keyword in the user input and answer accordingly.

3.Contextual Chatbots:

This type of chatbot is the most advanced in all three. Along with Artificial Intelligence, these chatbots also use Machine Learning and in this way, they are smart enough to self-improvise based on what the user is asking for and how the different users repeat the same inputs in different ways. These chatbots have a memory that enables them to learn and grow over time. It is very important to recognize which chatbot type is the right one for your business. While deciding this, you should think from the user point of view. Consider your target users and you can also have a chatbot guide with visuals to guide your users. The contextual chatbots are the most advanced ones but it is not necessary that you choose that one. If the scripted bots suffice your users need then, you shall go with that type!

Chatbot Examples

Well, if you think E-commerce is the only industry in which chatbots are flourishing then you’re wrong. Chatbots can work in almost every industry as they’re a part of the customer service team and they could also work differently. How? You’ll find out by reading these chatbot examples;

• Therapist Bot: With the increasing materialism and solitude, people are facing a lot of problems that they do not want to discuss with other people. The bot can listen to their problems and share solutions.
• Finance Help Bot: This type of bot can help people manage their money. The user can share their account details and necessary financial information and the bot can guide the user on how to save and manage their money.
• Scheduling Bot: Like Evernote, this bot can help you schedule your tasks for the day or week or month, but the bright side is the user can simply tell the bot the tasks he/she wants to conduct and the bot will schedule those accordingly using the memory and AI, considering the user’s priority.
• Friend Bot: With the increased pace of life and the urge of humans to more and more money, many people are missing out on socializing and some are having trouble due to migration or traveling across. This bot helps them have a virtual friend that they could talk to. One can target the introverts with this.
• Weather Bot: This bot can help you get details on the weather whenever you ask. (A bot version of the weather applications)
• News Bot: This bot can help you keep updated any time something interesting happens around the world. You can set your priorities or ask them to tell you updates on preferred time as per your schedule.

These are just a few examples. There are myriad ways of using chatbots. Give some air to your imagination and you’ll find a great business idea for bringing a new type of chatbot in the market.

Chatbot Companies

Now you must be wondering if these chatbot examples are really valid. Well, let us take a look at companies that already work with chatbots which will give you real-life examples of how chatbots can work!

Endurance: a dementia companion bot

A Russian technology company, Endurance, has built a companion for Dementia patients. The dementia patients often suffer from short-term memory loss. This chatbot helps identify deviations in conversations that could indicate a problem with immediate recollection. It is a cloud-based bot that helps physicians and family members review the degradation in communication and memory functions.

Spotify: a music messenger bot

Spotify now gives you a facility of a Facebook messenger bot that helps you search, listen, and share music. It offers you playlists based on your taste in genres or on what you’re doing. If you want to know how Spotify works, take a look here.

Roof ai: lead generation bot

With the increasingly competitive world, it has become too tough for marketers to find successful leads. All companies spend more than enough bucks on the marketers to find and consistently work on the generated leads. Looking at this, Roof ai has built a real estate AI chatbot. It identifies potential leads via Facebook and replies instantaneously to the potential leads. This closes the loops of missing a potential lead due to missing a message or failing to respond quickly.

Starbucks: an order placing bot

Starbucks is keen on making everything extremely easy for their customers. It has launched a chatbot in their app that helps you order giving two options, voice commands or text messaging, whatever you prefer. The bot takes care of giving you details about delivery and bill.

Lyft: a ride bot

Hailing a ride has become even easier with the Lyft chatbot. It works via chat through Facebook Messenger or Slack and through voice over Amazon Echo. It shares the current location of the driver with you and the license plate of the vehicle. Intriguing right? Curious to know more about Lyft? Click here.

Future of Chatbots

As we’ve already discussed what is a chatbot and how they function and what chatbots can do, you must be half-way convinced that chatbots are a new ray of hope in the customer service. It has various other mediums to be utilized and it could play a major role in customer engagement. Though from a technical point of view, it is tough to achieve the true usefulness of the bots due to a few limitations like lack of deep domain knowledge. Using the bots for business might not be feasible for now, but it could very well fit in customer engagement as it could have a deep knowledge of customer information and other relevant data across operations.

Why Chatbots are Important for Your Business?

Looking at the usefulness of the chatbots right now and the success of the companies that have implied it in their business and the increased user engagement is a reason good enough to make one consider thinking about using chatbots in their business. You may like to read - How does Square Work? Today, more people prefer messaging apps than social media apps. It is essential for any company to mark its presence where there lie more potential customers. Hence, it is more important now than ever to use chatbots for your business. The chatbot technology is still premature, now is the time to invest in this latest technology to benefit from its capabilities in the upcoming future!

How much does it cost to build a chatbot?

Cost depends almost entirely on which type you are building, and on how much of the conversation has to be handled without a human.

A scripted bot that answers a fixed set of questions and routes everything else to a person is the cheapest option. In most cases it is a few days to a few weeks of work: mapping the flows, writing the copy, connecting a messaging channel, and testing edge cases. No model training is involved.

An intelligent bot that reads free text and matches intent costs more, because it needs a knowledge base, a defined intent set, and ongoing tuning. That build is measured in weeks, and the real cost is maintenance: as products and policies change, the bot has to be retrained and retested.

A contextual assistant that remembers the conversation and pulls live data from your systems costs the most. It needs integrations into order management, CRM, or ticketing, a fallback path to humans, and a way to audit what the bot said.

Running costs matter as much as build costs. Channel fees, language model usage, hosting, and human takeover time all recur monthly. Budgeting for the build and ignoring the operation is a common mistake.

Chatbot, live chat or AI assistant: which one do you need?

These three are often sold as the same thing, and they solve different problems.

Live chat is a human at a keyboard. It handles complexity well and builds trust quickly, but it does not scale: every concurrent conversation needs an agent, and coverage outside business hours is expensive.

A chatbot handles volume. It answers the same twenty questions thousands of times without fatigue, collects structured details before a human steps in, and works around the clock. It handles ambiguity badly.

An AI assistant sits between the two. It can hold a longer conversation, use context, and call tools or look up records, but it needs guardrails, evaluation, and a clear escalation rule.

The practical answer for most businesses is a layered design: a chatbot for the predictable top of the funnel, an AI layer for free-text questions, and a human queue for anything involving money, complaints, or compliance.

How to plan a chatbot for your business

Most failed chatbot projects fail before any code is written, because nobody defined what success looks like. A short planning sequence avoids that:

1. Start from the transcripts. Export a month of support conversations and count the recurring questions. Those are the flows worth automating first.
2. Define the job. Decide whether the bot is answering, qualifying, booking, or transacting. Each carries a different risk profile.
3. Map the handoff. Write down exactly when and how a conversation moves to a human, and make sure the customer can ask for that at any point.
4. Choose the channel. Website widget, WhatsApp, Messenger, or in-app. The channel determines reply length, formatting, and compliance rules.
5. Write the copy first. Tone is part of the product. A bot that sounds like a legal notice will be abandoned.
6. Instrument it. Track containment rate, escalation rate, and the questions the bot could not answer. That list is your roadmap.
7. Launch narrow. One use case, one channel, measured for a month, then expand.

The most common error is trying to automate everything at once. A bot that does three things well beats one that attempts thirty and fails at half of them.

What it takes to build a chatbot platform

If the goal is not a single bot but a product that lets other businesses build bots, the engineering problem changes shape. You are no longer building a conversation, you are building the tools for conversations.

At minimum that means a flow builder, a knowledge base with versioning, channel connectors, an analytics layer, a human takeover console, and role-based access so a client's team can edit content without touching infrastructure. Add billing and multi-tenancy and you have a commercial platform.

The channel layer carries most of the integration work. Each messaging network has its own approval process, message format, and rate limits. Our WhatsApp style messaging platform write-up covers what that build involves, and the enterprise app development overview explains how such systems are integrated into existing back offices.

The conversational layer itself is increasingly rented rather than built. Most platforms wrap a language model instead of training one, which shifts the hard problems to retrieval quality, prompt design, evaluation, and cost control.

Frequently asked questions

Is a chatbot the same as artificial intelligence?

No. A scripted chatbot follows rules and does not learn. AI chatbots use natural language processing and machine learning, and may call external tools. The word chatbot covers both.

Can a chatbot handle payments?

It can, but carefully. Any flow that takes money needs authentication, encryption, and a clear audit trail, so most businesses route payment steps to a secure hosted checkout rather than collecting card data inside the conversation.

Do chatbots work on WhatsApp?

Yes, through the official business messaging API. Approval, message templates, and per-conversation pricing apply, so onboarding is more formal than adding a website widget.

How long does it take to launch a first chatbot?

A narrow, scripted bot on a single channel can go live in a few weeks. A contextual assistant integrated with internal systems typically takes a few months, including testing and evaluation.

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