AI Chatbot: Deep Learning Chatbot Software

If you’re currently using a standard chatbot, but want to upgrade to an AI program, we’ve put together everything that you need to learn and a list of the best AI chatbots for 2022. Read on to find the right one for you.

What Is an AI Chatbot Software?
What is a Chatbot Platform?
How to Make Chatbots Software?
- Best Model for Conversational AI
5 Best Deep Learning AI Chatbots
Wrap-Up

What Is an AI Chatbot Software?

An Artificial Intelligence (AI) chatbot uses machine learning to converse with people. The first-ever AI chatbot was developed in the 1960s by Joseph Weizenbaum, a professor at MIT. Today, chatbot technology has come a long way. It engages with people on an emphatic and personable level.

AI chatbots are dramatically reshaping the customer service experience. They can understand the context and meaning of the words. They can ask questions to create intent and can help resolve customer problems.

Chatbots are a great way to engage with and sell products or services to your customers. What if your customers could ask you questions and receive answers without having to call, email, or even tweet? The goal of Chatbots is to eliminate the "friction" that occurs when trying to communicate with a business.

How Do Machine Learning Chatbots Work?

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Machine learning refers to the ability of a system (in this case, the chatbot) to learn from the inputs it experiences. One of the ways they achieve this is through natural language processing, or NLP, which refers to any interaction between computers and human language.

AI chatbots use Natural Language Processing (NLP) engines and machine learning to interpret user inputs. This involves extracting user entities and determining user intents. These natural language processing methods are used widely in the technology industry, including for machine translation, sentiment analysis, and user behavior analytics (UBA) in cybersecurity.

This can be a tricky one to understand because deep learning is essentially an evolution of machine learning. But deep learning requires much more data than machine learning, and the difference lies in the way data is presented to the system.

Machine learning algorithms require structured data to learn from and can make informed decisions based on what they have learned.

Deep learning structures the algorithms in layers, to create an artificial neural network that can learn and make intelligent decisions by itself.

Machine learning networks sometimes need guidance from humans when they get things wrong. Deep learning networks do not usually require human intervention, as they are capable of realizing when they’ve made an error and learning from it.

Machine learning is suitable for your business if your data can be structured and used to train the algorithms, in order to automate some of your basic operations.

Businesses that require computers to solve more complex queries—and have a ton of data to help them learn—could take advantage of deep learning.

What Is an NLP Chatbot?

The new generation of chatbots is NLP-powered agents that get smarter each day. They carry information from one conversation to the next and learn as they go. Natural language processing for a chatbot makes such bots very human-like. It reacts to the meaning of the whole question. The AI-based chatbot can learn from every interaction and expand its required knowledge.

An NLP-based chatbot is a computer program or artificial intelligence that communicates with a customer via textual or sound methods.

This deep-trained program is often designed to support much more clients on websites or via phone.

A machine learning chatbot is generally used in messaging applications, for example, Slack, Facebook Messenger, or Telegram. It can order your food, buy tickets, or show the weather podcasts.

Three Pillars of an NLP Based Chatbot

Now it's time to take a closer look at all the core elements that make a machine learning chatbot happen.

1) Dialog System

To communicate, people use mouths to speak, ears to hear, fingers to type, and eyes to read.

Chatbot, too, needs to have an interface compatible with the ways humans receive and share information with communication. That is what we call a dialog system, or else, a conversational agent.

There are no set dialog system components.

But for a dialog system to, indeed, be a dialog system, it has to be capable of producing output and accepting input. Other than that, they can adopt a variety of forms. You can differentiate them based on:

Modality (text-based, speech-based, graphical, or mixed)
Device
Style (command-based, menu-driven, and - of course - natural language)
Initiative (system, user, or mixed)

2) Natural Language Understanding

NLU is an essential sub-domain of NLP and has a general idea of how it works.

Still, it’s important to point out that the ability to process what the user is saying is probably the most obvious weakness in NLP-based chatbots today. Human languages are just way too complex. Besides enormous vocabularies, they are filled with multiple meanings many of which are completely unrelated.

To nail the NLU is more important than making the chatbot sound 110% human with impeccable NLG, more advanced in layman's terms.

Why?

If a chatbot understands the users and fulfills their intent, most won’t care if that response is a bit taciturn… It doesn't work the other way around. A chatbot that can’t derive meaning from the natural input efficiently can have the smoothest small talk skills and nobody will care. Not even a little!

3) Natural Language Generation

Given that the NLP chatbot successfully parsed and understood the user’s input, its programming will determine an appropriate response and “translate” it back to natural language. Needless to say, that response doesn’t appear out of thin air.

For the NLP to produce a human-friendly narrative, the format of the content must be outlined be it through rules-based workflows, templates, or intent-driven approaches. In other words, the bot must have something to work with in order to create that output.

‍Currently, every NLG system relies on narrative design - also called conversation design - into creating that output. This narrative design is guided by rules known as “conditional logic”.

These rules trigger different outputs based on which conditions are being met and which are not.

Pros and Cons of Using a Chatbot

Using an AI chatbot can provide many benefits to businesses. Implementing these can result in improved customer satisfaction. Chatbots are as effective as experienced employees and are about 4x times more effective than inexperienced employees in selling products.

Companies can save costs by implementing chatbots with AI capabilities. These bots can also provide detailed insights about the customers who can be used to improve products and services.

Here's a detailed enumeration of how these machine learning chatbots affect a business:

PROS

Availability

Chatbots are available 24×7 and can respond to your customers instantly which is a lot better than a live chat channel. This means that whenever they message you for any reason, they’ll be able to get a response immediately. As a result, they’ll be satisfied with your brand and you, on the other hand, will be able to move them along your sales funnel.

More Engagement

Chatbots communicate with your website visitors and social media followers in real-time. This is in stark contrast to other content of your brand that’s usually consumed passively. Such engagement can keep people on your website for longer and help in driving sales and improving your SEO.

Data Collection

Chatbots can be a great way to collect your audience data. They can communicate with your audience and gather information such as their names, email addresses, and more. You can easily access these details by integrating the chatbot with your CRM.

Additionally, you can ask customers about their preferences using the chatbots and accordingly customize your offerings to better suit their needs.

CONS

Data Security

When you collect your audience data, it’s your responsibility to keep it secure. The data needs to be transmitted from the chatbot to your CRM in a secure manner. It must also be stored securely and only relevant data should be collected from your audience.

Inability to Understand Emotions

Chatbots are codes and hence, they find it difficult to ascertain the emotions of the user. As a result, they may not be able to understand if the user they are chatting with is happy, agitated, or sad. This might lead to the artificial intelligence chatbot coming across as emotionally insensitive and it can harm your brand’s reputation.

To reduce the chances of such a situation, you should consider using chatbots that allow customer support agents to take over the conversation.

How these chatbots are able to provide a single user a smooth experience during their browsing or purchasing helps a lot in contributing to their decision whether to do an action or not.

A machine chatbot offers a lot of advantages aside from the support it can give to customers, it can make your marketing campaign more effective with its advanced AI powered capacity.

AI Chatbots General Features

These applications use advanced Natural Language Processing (NLP) algorithms to interpret human speech and make appropriate responses. The chatbot software gets improved with each chat and adapts to what customers say and do. Additionally, the chatbot apps can segment customers, collect customer data, and provide insights about customers in the form of a report.

To achieve true general AI software, a machine learning chatbot or dialogue system needs to be able to do three central things:

Offer an informative answer
Maintain the context of the dialogue.
Be indistinguishable from the human

When it comes to that last requirement, we are not quite there yet. Even the best of today’s deep learning chatbot can’t be mistaken for a human. But fortunately for brands, (most), humans are still willing to talk with bots as long as they are helpful, funny, or interesting.

What is a Chatbot Platform?

An AI chatbot platform allows businesses to host multiple AI chatbots all in one place. Chatbot platforms are crucial when companies want to deploy chatbots across multiple communication channels like messenger, SMS, email, and directly on the website. Having all your chatbots organized in one place ensures maximum efficiency and learning opportunities as the AI inevitably gets more sophisticated.

There is a wide range of AI chatbot platforms available to help brands develop suitable chatbots to help them attract and retain customers. These AI chatbot platforms usually contain tools to help you develop and customize suitable chatbots for your customer base.

With their ability to guide customers through the marketing funnel, and keep people engaged after-sales all the while adding personality to a company's brand, AI chatbots are adding new value to brands’ content marketing. These chatbots create more personalized experiences for customers by tailoring companies' responses and content to the customers' queries and interests, which aids reputation management. They are also cheap and can work around the clock without requiring human intervention.

You can choose a chatbot platform online that provides plenty of free features to explore and try on your own provided that a more enhanced and beneficial feature can be accessed via subscription per month.

How to Make Chatbots Software?

You can create an AI chatbot using a chatbot builder tool. Unlike live chat software, this AI software needs deep learning in order to reply to your customers and leads. Some chatbot builders allow you to build without any coding. You can create a chatbot and add it to your website easily using a drag and drop template.

Help customers find what they want quickly and easily - whether it is buying groceries or finding a table at a restaurant. Provide an instant response based on the user's request with a machine learning chatbot.

Another way to create a chatbot is through coding, if you are fond of using programming languages, you can definitely create a more customized one. Most newbies use a builder since it is a no-code creation of chatbot. It is easier and consumes lesser time.

There is no wrong or right way to create a chatbot. If you prefer a complicated and challenging way, go for the coding one but if you are comfortable with using a template and just editing the features, you are very much free to do so. One thing to bear in mind though, is always make sure that your chatbot can provide all the needs your business requires as well as its physical attribute must complement the image of your brand.

Best Model for Conversational AI

Conversational AI is all about making machines communicate with us in natural language. They are called using various names — chatbots, voice bots, virtual assistants, etc. In reality, they may be slightly different from each other. However, one key feature that ties them all together is their ability to understand natural language commands and requests from us-human users.

The architecture model of a chatbot is decided based on the core purpose of development. There are two types of possible responses of chatbot: it can either generate a response from scratch as per machine learning models or use some heuristic to select an appropriate response from a library of predefined responses.

Chatbots should use QA models that can extract answers from a large corpus of text on the fly.

QA (Question Answering) model for conversation can be used where there is a large body of text that customers could query from and creating intent and curated answers for each question-answer pair is an expensive proposition.

It is a sub-field of Natural Language Processing research with the objective of understanding user questions in natural language and extracting answers from a large corpus of text. This as you can clearly see, is a way of reducing the human effort in curating answers to questions that customers ask. It may be nearly impossible to create an exhaustive list of prepared questions and answers.

5 Best Deep Learning AI Chatbots

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Whether it’s on Facebook Messenger, a website, or even text messaging, more and more brands are leveraging chatbots to service their customers, launch a product, market their brand, and even sell their products.

Here are 5 of the best deep learning AI chatbot builder you can choose from:

1) TruVISIBILITY

The gap between “growing” and “great” is automation. From customer attraction to nurturing, to onboarding, and building fans, our AI Chatbot builder gives you the same tools Fortune 500 brands use to automate their processes.

It doesn’t matter if your goal is to:

Generate more leads
Earn more subscribers
Segment your audience
Convert more sales
Build a tribe of fans

If your business relies on one or two sales superstars, your growth is limited. High-performing AI Chatbots can simulate authentic conversations of your top salespeople… and deliver that message 24/7, with consistency, at scale. They’ll also never get sick, demand a raise, or get poached by your competition.

TruVISIBILITY's chatbot software platform offers every feature you need. With their subscription that's free to start and affordable as you go, what more can you ask?

2) Landbot

Landbot is an AI chatbot tool that helps you to convert leads, capture data, and personalize client journeys in real-time. It allows you to manage and automates conversations on the main messaging channels.

It helps you to design, deploy and analyze your conversational strategies from the same place.
Offers tools to create frictionless, engaging, and overall memorable customer experiences.
Engagement leads to better conversion.
It is seamlessly transferring conversations from bot to human and back.
Design your full messaging-based user journey.
You can design automate conversations for WhatsApp, web, or Facebook Messenger and integrate them with the tools you already use.

3) HubSpot Chatbot Builder

Their chatbot supports customer, book meetings, and scale your conversion. It has 200+ integrations that you can customize according to your company's needs.

It is one of the best AI chatbots that offer unlimited personalized conversations at scale.
Create and customize bots yourself without writing any code
The code gives your bots a human touch.
It allows you to add the contact record and manage your lead.
You can add deals to your CRM with just a single mouse click.
It provides email tracking to know your leads.

4) REVE Chat

This application enables you to connect with your customers using video, live chat, bots, and more. It helps you to deliver instant support for your customer on messaging apps like Viber, Facebook Messenger, Telegram.

It enables you to add messaging functionality in mobile applications or on your website.
Offers real-time customer service to your customers and visitors.
You can get real-time customer feedback.
It can be used to drive sales conversations with ease.
Provides a personalized live experience to your customer.

5) Flow XO

Flow XO is an automation software to build chatbots that help you to engage, support, and communicate with your customers across social media platforms, different sites, and applications.

You can welcome new visitors virtually to the e-commerce website by providing greetings.
Gather user details by asking simple questions and validating the answer provided.
A chatbot can answer simple questions or link to any article.
It allows you to hand over discussions to a human on livechat.
It is one of the best chatbot that accepts payment by identifying a particular service or product your customer likes to purchase.

Marketing with a chatbot can be very beneficial for a business. Ads and other marketing campaigns are available but with a chatbot, the customer service support it can give is exemplary. Plus, will save you a lot of money. It is available anytime and can answer inquiries or questions from multiple customers in one go.

But even though most chatbots can handle moderately sophisticated conversations, like welcome and thank you conversations. Also product discovery interactions, the if/then logic that powers their conversational capabilities can be limiting.

For instance, if a customer asks a unique yet pressing question that you didn’t account for when designing your chatbot’s logic, there’s no way it can answer their question, which hangs your customer out to dry and ultimately leaves them dissatisfied with your customer service.

Wrap-Up

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Chatbots are taking business services to the next level by improving customer experience, engagement, and boosting sales conversions. Powered with advanced AI technology, these machine learning chatbots can perform a smooth conversation though may lack emotion but enough to drive a sale into a business.

The best AI chatbot does not only refer to how it looks but also how it reflects your brand's image as well as the functionality and its capability to turn that conversation into sales. The experience that your customers will have through the use of your chatbot pushes these people to make a move. The smarter your chatbot is, the higher your chances of getting more sales.

Choosing the right platform or builder to create your chatbot plays a big role too. Every builder provides different features some of them will be free and some will be paid. If you're trying to save, go for the free ones but consider the features and the functionality. You might have created a free chatbot but what if it's lame? People will still lose interest and will end up leaving your website or platform.

If you’re considering using machine learning or deep learning chatbots for your business, make sure you do some detailed research both internally and externally. It’s a good idea to discuss the pros and cons with your employees to work out exactly how the technology could benefit your business.

The bottom line is that you should only use chatbots if the concept is a good fit for your business, and can be trusted not to alienate or annoy your customers. You don’t want to sacrifice the customer experience on the altar of progress.