Chatbots, also known as virtual assistants, are conversation engines that initiate human conversations with users through voice commands, text chats, or both. They have become very popular in recent years due to dramatic improvements in artificial intelligence (AI), machine learning (ML), and other underlying technologies such as neural networks and natural language processing.
These conversational agents can effectively communicate with any human being using interactive queries. Over time, they can learn how to best interact with humans, answer questions and troubleshoot customer problems, evaluate and qualify prospects, generate sales leads, and increase sales on an eCommerce site.
An interface connects a chatbot to the user, such as an app, a website, a chat pop-up window, or a social network like Facebook Messenger. Various types of chatbots have been introduced over time; the following are the most popular.
Joseph Weizenbaum’s ELIZA was the first chatbot to be introduced to the market. It manages information using keywords and techniques, and when someone asks a question, the chatbot responds immediately using the previously defined keywords. If ELIZA cannot find an answer, it uses other mechanisms to obtain additional information from the user, allowing the conversation to continue and an answer to be found.
Richard Wallace developed ALICE in 1995. To get the user’s response, it employs natural language patterns. Artificial intelligence markup language (AIML) files are used to store all of the data.
Windows created Clippy in 1997, and it was the company’s first virtual assistant. Apple released Siri in 2011 with several new features, including the ability to have voice conversations rather than just written ones.
IBM created Watson in 2011, taking a step forward in providing better service to users by providing additional answers. Cortana is a virtual assistant created by Microsoft in 2014 based on a video game and is compatible with all Windows applications.
Alexa, introduced by Amazon in 2014, provides a wealth of information to users, ranging from locating product information and weather commentary to remembering important dates. Finally, Samsung introduced Bixby in 2017. Incorporation in several languages is pending for widespread use in Samsung products.
These virtual applications are used in many different sectors:
- Sales & Marketing: Chatbots can engage with customers, prospects/leads, generate business, and manage existing and new Customers. This can apply to both customer self-service and e-commerce sales.
- Service: Chatbots help customers register complaints, requests & answer general queries, capture feedback, search for the information they need and fast-track the resolution.
- Back end functions: Chatbots can help internal users, agents, employees, etc., with automation in functions, data extraction via conversational inputs/ queries, raising feedback, or even updating information.
- Agent productivity: Chatbots can assist agents with manual and repetitive tasks, and also replacing them can improve AHT and enable more productive use of time.
Chatbots are classified based on the ease of user interface, algorithms, and the underlying technologies used. Here are some of the most popular types of chatbots you can build for your business.
Menu/button-based chatbots
The most commonly used and the simplest type of chatbots in the market today, the menu/button-based chatbots, are in the form of buttons and top-down menus. Also known as Persistent Menu Options, they have pre-written questions and answers. Instead of giving the user the possibility to give free text input, the user is limited to several buttons. Therefore, a user cannot input a fresh query in these chatbots.
From the start to the end, the chatbots give multiple options for every query. They are sufficient for answering standard questions, which make up for 80% of support queries. Although they control the flow of the conversation, these chatbots fall short when users want to ask more advanced questions. Menu-based chatbots are comparatively slower in performance and cannot be completely reliable to get the desired answer.
Keyword-recognition-based chatbots
Keyword-recognition-based chatbots are an extension of menu/button-based chatbots. With keyword recognition-based chatbots, users can interact by giving free text input. The chatbot then analyses the text on specific keywords and gives an appropriate response based on those keywords.
The chatbot gives users more freedom in input since users can ask more advanced questions. However, when there are keyword redundancies between several related questions, these chatbots will start to fail. For example, if a user asked, “How do I set up an auto-login authentication on my phone?” the bot would most likely use keywords like “auto” and “login” to figure out which response is best.
Contextual chatbots
The most technologically advanced bots in the market today, contextual chatbots are extensions of keyword recognition-based chatbots. They use machine learning (ML) and artificial intelligence (AI) techniques like voice recognition and speech-to-text conversion algorithms to interpret users’ sentiments and interact. Unlike keyword recognition-based bots, chatbots with contextual awareness are smart enough to self-improve based on what users ask and how they are asking it.
Contextual chatbots remember specific user conversations and can learn and improve their responses based on what a user asks and how the user asks it (context of the question). For example, when a user wants to order pizza, a contextual chatbot may remember his previous order and offer him a pizza based on his previous purchase. These chatbots analyze the user’s perspective and suggest recommendations based on consecutive orders and users’ likings.
