You go to a website and while you’re scrolling through you get a pop up mini window with a write up “How can I help you today?” In the simplest terms, this is how a chatbot is described. An online assistant to guide you through whatever questions you have.
A chatbot is a piece of software that conducts a conversation via auditory or textual methods. Such programs are often designed to convincingly simulate how a human would behave as a conversational partner, although as of 2019, they are far short of being able to pass the Turing test. Chatbots are typically used in dialogue systems for various practical purposes including customer service or information acquisition. Some chatbots use sophisticated natural language processing systems, but many simpler ones scan for keywords within the input, then pull a reply with the most matching keywords, or the most similar wording pattern, from a database. In essence, Bots are computer programs that simulate human conversation through text chats and voice commands.
Evolution Of Chatbots
Intelligent machines didn’t just happen, they evolve over time and so have chatbots. The contribution of chatbots to not only the business world but every aspect of technology cannot be overemphasized. Chatbots have evolved in not just their interface but also their functionality.
In 1960s, Joseph Weizenbaum, an MIT professor developed the very first chatbot and it was called Eliza. Eliza was made to respond the same way a therapist in that era would respond. Since then other chatbots have been developed and introduced to society and there has been a steady advancement of both Bot interface, features and functionalities.
A Chinese company called WeChat, in 2009, created a more advanced chatbot which has since then been loved by many people all over the world culminating in it becoming a highly engaging social media platform. WeChat has made creating chatbots simple and easy, making life easier for marketers and increasing work productivity for businesses.
Since then, there has been an introduction of chatbots to not just websites but also messaging apps and other business platforms. This way, businesses can engage with customers and guide them through their buying process without having to have repetitive conversations. This way customers can access needed knowledge and also carry out basic transactions from the app.
The introduction of chatbots into a community has brought us to the time of the conversational interface. It’s an interface that soon won’t demand a screen or a mouse. The interface will be entirely conversational, and those communications will be indistinguishable from the conversations that we have with our friends and relatives.
Types Of Chatbots
Linguistic Based Chatbots
Also known as rule-based chatbots, these bots delivers the control and flexibility not found in machine learning chatbots. With rule-based chatbots, the correct answers to questions can be planned in advance and tested for efficacy. These chatbots use if/then logic to create conversational flows. They are programmed to identify, not just words and phrases but also their synonyms in order to provide the right answers to varying questions with the same meaning.
The downside to these chatbots is that they are slow and tedious to develop and can be very They are, however, the most common types of chatbots you will find. For example, Facebook messenger and interactive chatbots on e-commerce websites. expensive.
Machine learning Chatbots
These are chatbots powered by artificial intelligence software. These chatbots are a lot more complex than linguistic-based chatbots, Because they are more concise, data-driven and leverage natural language understanding to apply predictive intelligence, they are usually more, interactive, conversational and personalised.
While these types of chatbots are a lot more impressive, they require a massive amount of training data and the need for skilled professionals to run. The resources required to operate AI-based chatbots make them an expensive and impractical choice for more businesses.
A hybrid chatbot combines the best parts of both the linguistic and machine learning-based chatbots and delivers an intelligent, more complex conversational experience. The advantage the hybrid chatbot has over the other two is that it allows the conversational system to be built with or without data. It also ensures that their is a consistency in the personality and that it is tailored to fit the business expectations.
When a hybrid approach is delivered at a native level this allows for statistical algorithms to be embedded alongside the linguistic conditioning, maintaining them in the same visual interface.
Building conversational applications using only linguistic or machine learning methods is hard, resource-intensive and frequently prohibitively expensive. By taking a hybrid approach, enterprises have the muscle, flexibility and speed required to develop business-relevant AI applications that can make a difference to the customer experience and the bottom line.
How They Work
Chatbots work by using Natural Language Processing (NLP) that enables computers to understand, analyze, and create meaning from human language. It then matches commands given with collected data already stored in it to provide suitable responses.
Depending on the function of the chatbot, some other elements can be added to it to make it more helpful, engaging or interactive. For example, carousels, buttons, quick reply, web view, group chat, options to share audio, video, document file, image, GIF, and so on.
The function of the chatbot generally determines what technology developers will use to create them. There are new tools and technologies, however, that can either allow individuals to create chatbots without any coding experience or take it to the next level and create chatbots with more advanced capabilities.
In recent years, C\chatbots have evolved to enable text and voice communication. Working in collaboration with virtual assistants or smart speakers, they allow users to give input and receive output in a voice format. A perfect example of this is Mark Zuckerberg’s JARVIS.
The right chatbot must be able to go beyond just answering questions mechanically to having intelligent conversations and being interactive in nature. An interactive chatbot is designed to not just improve user experience but also provide useful data for future updates, which in turn increases the business bottom line. This means the chatbot has to not just understand the user’s language but also be able to clarify by asking questions to eliminate any misconception.
- Enterprise-Grade Solution
More chatbots should be made with enterprise solutions in mind. This means including features like user roles, version control, automated coding, webhooks to allow flexible integration with other external systems, and ease of transferability to new services, new devices and new languages.
Personalizing conversations with chatbots in all areas is important for both efficiency and user experience. Be it in taking into account the customers favourite route to work or handling financial and business transactions. Some information can be learned simply by choosing a preference from a list of recommendations, but others have to be learned over time by gathering data and input from prior interactions with customers. The implicit methods of learning are what truly uses the power of AI.
Ensure any conversational platform you use can be easily moved from one device to another. It is also important to make sure that moving the platform to a new device does not result in the loss of previously collected data. In the same vein, make sure to figure out how the device can be ported from device to device on the part of the end-user too. They should be able to carry on a conversation on their mobile while they’re walking to work and continue the same conversation on a laptop while they’re in the office without any hitches.
We can learn from Microsoft’s Tay that people can manipulate chatbots and use them inappropriately. Tay was designed as a showcase of machine learning, but unfortunately very neatly illustrated the problem with some conversational AI development tools. Business can prevent mistakes and provide a ‘safety net’ for dealing with unexpected incidences during a conversation if they make sure that there is a level of control within the application.
In the process of using chatbots, people don’t just gather the knowledge they need but also provide a vast amount of information about themselves. Everything fro their preferences to their personal opinion. This information can be used to not just predict future behaviour but also to tailor services to soothe the customer and in turn increase customer engagement and loyalty. It is therefore important for businesses to maintain ownership of this data. Choose a platform that not just gives you end results but also gives you full insight into the details of the data provided.
- Data Analysis
Analysis of data should also be considered when creating a chatbot. Whether you’re developing the chatbot yourself of using a service that helps you create it, make sure you have access to an analytics package that helps you go through the information and understand the customers’ needs and preferences from every conversation.
When dealing with regulatory frameworks, especially those that involve the collection and use of customer’s personal information, it is important to ensure data security. Chatbots should be flexible in order to meet security and legal regulations across all geographical locations. While most enterprises have no issue with a standard cloud deployment when complying with industry regulations, it is important to ensure that on-premise options are available.
Companies can set themselves apart from their competitors by adding artificial intelligence chatbots into everything from smartwatches, smart TVs mobile applications and so much more. It also helps infuse some form of personalization into brand products while increasing brand engagement.
- Proven Technology
The last thing to do when developing chatbots is a real-life test. Go beyond just marketing and luxury features and get other businesses to tell you how the chatbot works. Ask them about the interface and experience, what do they like and what’s not working with the Bot. Find out from them how easy it was to develop and build solutions, have they tried porting to new languages or services, how did they expand into new channels or devices, what benefits have they seen, and how has it helped their digital strategy.