The advent of bots in 1966 started with text bots like Eliza, and it later evolved to voice-based bots during the 80’s. The simplest way of defining a bot would be a software that can have intelligent conversations with humans.
Though there are various use cases for bots, one of the familiar examples is live chat platforms where users ask questions, which are met with appropriate responses by a chatbot. This is a quick way of resolving queries and providing timely customer service.
What is a Chatbot?
For a deeper understanding of Chatbot, we can define it as a computer program that impersonates human conversations in its natural format, which may include text (since the advent of bots) or spoken language using artificial intelligence (AI) techniques such as Natural Language Processing (NLP) and audio analysis. One of the primary aspects of an AI-based bot is that it is dynamic.
AI-based bots learn from the previous interactions and in retrospect, become more intelligent to handle conversations that are more complex.
How do the Chatbots function?
The main technology that lies behind chatbots is NLP and Machine Learning.
When a question is presented to a chatbot, a series or complex algorithms process the received input, understand what the user is asking, and based on that, determines the answer suitable to the question.
Chatbots have to rely on the ability of the algorithms to detect the complexity of both text and spoken words. Some chatbots perform very well to the point it becomes difficult to differentiate whether the user is a machine or a human.
However, handling complex conversations is a huge challenge; where there is a usage of various figures of speech, it may be difficult for machines to understand.
Types of Chatbots
Chatbots are categorized into two different types. Let us look at both and see how they function.
Chatbots follow a set of established rules or flows to respond to questions posted by a user. All your simple applications contain rule-based chatbots, which respond to queries based on the rules they are trained on. For instance, a weather application, where you ask for weather forecast and it fetches the data from different sources and responds with the information.
Rule-based chatbots may not be able to hold complex conversations. It can only accomplish the tasks it is programmed to perform unless more improvements are made by the developer.
Machine Learning-based chatbots
Chatbots that are based on machine learning can hold more complex conversations as they try to process the question and understand the meaning behind the question. It learns from the previous conversation and enables itself to handle more complex questions in the future.
Now, let’s take a look at some of its use cases.
Use Cases of Chatbots
There are various interesting chatbots, which can make your life easy. For companies, chatbot development focuses around improving their business processes and provide better user experience to their customers.
It is also being utilized to serve customers on social media platforms like Facebook and others. However, most of the Facebook bots are easy to develop and use, as many of them do not need coding, and anyone can create it.
One of the popular modern chatbots is Joy, specifically developed by Danny Freed to track and improve mental health. Joy is developed to be a friend via Facebook Messenger.
It sends daily check-ins, and offers tips on dealing with different emotional experiences, like anxiety, helping you make life more enjoyable. The inspiration behind developing Joy came from a close friend of Freed who committed suicide.
For now, Joy can only ask questions and can generate weekly reports of your mood based on the interactions you have with it. Soon, you will be able to derive long-term solutions and therapies aimed at improving your mental health based on interactions over time.
Let’s take a look at some of the chatbots that are used in various industry segments.
One of the biggest challenges while shopping is finding the relevant products that you are looking to buy.
This can sometimes be a time-consuming process, even if you are looking for something specific. This can make your shopping experience tedious.
eBay has introduced ShopBot, which can assist customers in their shopping and provide them with a better experience. The main aim of ShopBot is to help the customer find the best deals that are available and discover products. Customers can use text, voice or images to inform the bot about what they are looking to buy.
It uses deep learning algorithms along with Natural Language Understanding (NLU) and computer vision to help users express their shopping needs and derive results based on these commands.
Relevant Article: 5 Deep Learning Trends that will Rule 2019
Another interesting bot is Kip, which can handle any number of complex orders of a team. Instead of a single shopping cart for each user, it has the option of group cart. This allows different members on one team to place different orders at the same time and at checkout, the admin pays the final amount. This is a unique way of enabling shopping, especially at workplaces.
UCLA (University of California, Los Angeles) created a virtual radiologist that provides support for clinical decision for patients.
The virtual radiologist bot is based on Artificial Intelligence (AI), and the main aim of the bot is to provide the doctor with the ability to communicate necessary information to the patient with the overview of radiology treatment or inform them about the next steps in a treatment plan, in real-time.
The virtual assistant was built on a foundation of over 2,000 example data points designed to mirror questions that commonly come up during a consultation with an interventional radiologist.
Woebot is another chatbot, which is created to track your daily conversations and other daily activities that give insights into the mood of the patient and help them to evaluate the patient’s mental health and give required responses.
Using chatbots in CRM can be very helpful as it can handle all the mundane tasks, allowing the users to handle other important tasks.
For a sales team, it can help with automating the data entry process, so they can focus more on customer interactions. It has been found that 20 percent of sales personnel efforts are spent in filling out details on the CRM. To address this problem, Fireflies- a bot, fetches or mines data from audio conversations and finds relevant information to be fed to the CRM.
Salesforce has developed a bot, which fetches customer data for the personally talking to the customer on Slack. Though there may be a variety of data present in the database, it only fetches the relevant data to be displayed on Slack.
Effective Project Management
Proper project management is a key element for the success of any project. Some automation at the project management level can help aid in effective and efficient release.
Bots like Meekan help in automatically matching schedules of team members, and help in arranging team meetings, avoiding any schedule clashes, etc. This saves time in co-ordinating through emails or calendar invites and makes collaboration easy by just asking the bot to schedule a meeting based on everyone’s convenience.
Another important challenge can be task management. To streamline task management, the use of chatbots like Howdy can save manual efforts when it comes to promoting content. PMBot can automatically generate status reports, minimizing the need for status follow-ups or meetings with team members.
Tools to Develop Chatbots
There has always been a common confusion when it comes to platforms. There are platforms for chatbot development and others that are for chatbot publishing. The main difference here is that publishing platforms are environments where you can interact with the bot. On the other hand, development platforms are tools that enable the development of bots. Let us take a look at some of the most commonly used chatbot development platforms for custom chatbots.
Chatbot Development Platforms
Watson is one of the most preferred platforms when it comes to building AI chatbots. The advantage of Watson is its capability to serve different verticals and manage complex interactions with ease.
When you are developing a bot with Watson, start by gathering your requirements to understand, what scenarios need to be addressed by the bot. Once the scope is defined, defining personas will help you identify and create an empathy map. Prepare a list of intents, which are the goals and purposes expressed in the input given by the user. You can create an instance of Watson Assistant and use the provided tools to calibrate the Intents and Entities (the appropriate responses against the Intent). This step is followed by defining dialogue flow and testing procedures.
The next phase is to develop the application or microservice that will interact with the Watson Assistant. Implement business logic to handle the context of the interaction and inculcate other components to complement the business requirements.
Watson is ideal to develop bots on various social media platforms along with your website.
Microsoft Azure Bot Service
The Azure bot service provides the developer with SDK and portal, along with a bot connector service that will allow the developer to connect to any social media platform. The SDK also helps with debugging your bot and provides a large selection of sample bots that can be used as building blocks for your bot. This Cloud-based service is accessible from almost anywhere and provides multiple language support.
The tools provided for the developers, assist them to create highly interactive bots and it is considered as a highly scalable service.
This is another bot from Microsoft, which is exactly as the name suggests. It can be of great help to any business that is asked frequent questions from their customers regarding their products. QnA Maker allows you to develop and train your bots for answering simple questions, based on your FAQ URLs, any structured documents, and manuals for the product within a matter of minutes.
Moreover, the use of Microsoft Cognitive Services can also enable the bot to interact as humanly as possible. It also allows you to integrate third-party APIs and solutions, enabling a better user experience.
This company focuses on developing next-generation conversation AI-based chatbots. It was recently acquired by Microsoft to create more lifelike conversational bots. Semantic Machines offer a language independent platform that helps developers to build bots that can have understanding conversations rather than bots that follow a series of commands. Since it supports various use cases, it is ideal for businesses that have specific needs.
The features of Semantic Machines include conversation engine, deep learning, speech recognition and more that will aid the developer in creating intelligent and interactive bots.
Recast.ai is a chatbot development platform that allows developers to build and train their bots according to the tasks they have to perform. You can use Bot Builder to implement conversation logic that will allow the bots to respond to predefined questions in a logical manner. They provide messaging metrics and bot analytics tools to enhance and improve the understanding of inputs and respond to them with relevant entities.
Chatbot Deployment Platforms
Once chatbots are developed, they need to be deployed to a deployment platform. You will have to choose a deployment platform based on your customer base. However, the use of chatbots revolves mostly around social media platforms or virtual assistant features in various devices. Let us look at some of the emerging bot platform ecosystems.
With over 1 billion users, there is no denying that Facebook has a wide reach around the world. For developers who are developing bots, this is a great platform to reach out to a bigger audience. Facebook has been investing in bot development and has provided tools for users to create bots for their specific needs without writing a single line of code. Fast food joints like Burger King has leveraged the use of bots to serve their customers by taking their order via Facebook. Many businesses have used Facebook to their advantage and improved ways of serving their customer base.
Slack is another popular messaging tool that is used mainly by businesses for internal communication or with customers. Bot application like Standuply, integrated with Slack, help you manage and schedule meetings with your team and generate timely reports or surveys. Other bots like Tomatobot, help you manage larger projects with ease by breaking them down into smaller chunks. It reminds you to take breaks in between tasks, allowing you to perform effectively at work.
Another great bot that can be used to manage data is Statsbot. This bot connects other platforms such as Google Analytics, Stripe, Mixpanel and others to Slack. It also reports any spikes or changes in your data while achieving your business milestones.
Skype for Business
This is another popular instant messaging platform utilized by many businesses around the world for their internal or external communication. Bots like Skyscanner allow you to make travel arrangements right in your Skype window. In addition, it helps you to find the most affordable travel options. Bots like Bing Image Preview and Getty Images allow you to search for images right from your Skype search bar.
Facebook has created a platform called Workplace, which can be used by businesses as an internal IM messenger. There have been some interesting bots on this platform, which can assist employees in their tasks. New Starter Bot allows to slowly drip feed information to a new employee rather than the tedious approach of dumping maximum information on them, which may not lead to quick learning. You can use it to schedule training sessions and arrange tests or quizzes to note how much the new recruit has learned.
Other bots such as Mood Bot allow you to understand their satisfaction towards the company, allowing authorities to address their dissatisfaction and retaining your employees.
As more messaging platforms emerge, more bots are also being developed to deal with different business-related scenarios, and improve your business processes along with making your jobs easier to execute.
It is an instant messaging platform, used for internal communication in businesses. One of the most popular bots on this platform is The Weather Channel. It forecasts the weather for you and lets you know if there is going to be any change in the weather. This is great for traveling professionals as they can plan their schedules accordingly.
There are other messaging platforms with interesting bots that have been used to make business operations smoother and easier.
Best Practices to consider while developing Chatbots for your business
Before you proceed with the chatbot development process, as a business, you will need to define the scope of your bot, understand what you want the bot to perform, and what possible hurdles you may face before you can train your bot to reach its full potential. There are a few points to ponder upon before you give a green signal to your development process.
Let’s discuss some of them and see how they can help us in building an intelligent bot.
Defining Role & Setting Goals
Before you look into how you would develop your bot, the first question you need to ask is why. Once you have arrived at the answer, the next step would be to identify the role of your bot. Your business needs to determine the role of your bot. You should also evaluate how the bot will help you save time, efforts, improve efficiency or yield any other benefits.
Set up goals you wish to achieve with your bot. A set of input values that will lead to a set of appropriate outputs. It is always advisable to start with simple goals and gradually progress to ones that are more complex. These goals and roles can be progressive and evolve as business needs evolve over time.
Knowing your Audience
Understand that the needs and wants of your audience are important for the success of any chatbot. You need to know your customers — demographics they belong to, and the kind of questions they might have. You can study previous interactions and equip your bot to respond to queries that they might frequently ask. Knowing your customer base well enough will determine the success of your bot.
Choosing the Right Deployment Platform
There are different chatbot deployment platforms as discussed above which may be internal or customer facing. If the bot you are developing is customer facing, then you need to deploy it on platforms that your customers are most likely to use. If you are using text-based bots, the ideal platforms could be your company website, Skype, Facebook, Slack, Kip, etc. As interactions occur, you will also need to evaluate if the service is adding value to your business.
Building your Conversational UI
A human being can ask the same question in different ways. Therefore, your bot should be intelligent enough to understand the question and provide the user with the appropriate response. The interaction has to be precise and it should be able to solve any query with an accurate response. There has to be a story and flow in the conversation to make it a success. For this, you have to start by building a content model for the conversation. Content model allows your bot to give scalable answers. Content models are always context-independent, that allows you to replicate the same model and structure for other products.
The conversational interface allows the user to tell the bot, what it needs to do. Companies like Facebook and Apple have already implemented such interfaces for their business purposes. It has captured the interests of various companies as it provides an intelligent interface. This not only depends on words but also on the understanding of human language and the meaning behind the words that are being used.
Dialog flow is a key factor for chatbots. You can create a logical dialog flow based on the type of questions encountered by the bot. It should be a detailed response, which requires defining the information for each response. Every dialog flow design should contain the exact representations of the response on each question. The design for detailed answers should happen outside of the actual flow design, as you may want to have variants of the same answers based on the questions. This is known as Random Prompting and it is a technique that you use while developing chatbots.
Recording Previous Chats
Another key factor for developing AI-based bots is to learn from previous interactions with users. Any interaction that users have had with you can be used as a reference to train the bot. If it is for the first time, then it has to be created from scratch. Choosing people with the same linguistic backgrounds can help in your bot designing process by creating data that are more realistic and may include mistakes that may be typical of non-native speakers. So, collecting chat data will help your bot to answer intelligently when posed with questions.
Picking the Platform & Right Development Approach
Different chatbots will have different approaches to understanding a question in natural language. It is important to analyze the question, understand the intent, and identify words to derive the right response. These tasks can be achieved by two different approaches, one is a rule-based response and the other is based on machine learning.
However, many times, the user may not always be asking a question. Applying machine learning will allow your chatbot to learn from previous conversations and give answers that are more intelligent while holding conversations that are more complex. If you do not have training data then you can prepare responses and implement rule-based chat where the bot will identify keywords and give responses based on the rules pertaining to those specific keywords.
One of the key factors for the success of any chatbot is thorough testing. When it comes to testing bots, it is advisable to have a diverse team to conduct real-user testing. Continuous testing is required along with the revision of your NLU (Natural language understanding) components to reach the maximum level of accuracy. These components have to be reviewed from time to time and improvements can be made to make your bot more interactive and accurate.
Once the chatbot is deployed, closely monitor the initial interactions and gather feedback to understand how users are interacting with the bot. Gathering these use cases and adding them to your bot’s arsenal can improve user interaction over time.
Smart solutions are important for the success of any business. From providing 24/7 customer service, improving current marketing activities, saving time spent on engaging with users to improving internal processes, chatbots can yield the much-needed competitive advantage. If you are looking to develop a chatbot, the best thing to do is to approach a company that will understand your business needs to develop a chatbot that helps you achieve your business goals.
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