Everything around AI Chatbots – Challenges and Opportunities
Table of Content
What is a chatbot?
Powered by complex Machine Learning algorithms, Chatbots allow computer programs to mimic human conversations and react to written or spoken queries to deliver a service. Because chatbots are powered by AI, they are self-learning and can comprehend human language, not just computer commands. The efficiency, accuracy and overall intelligence of chatbots increase with the number of conversations they have and the unique situations they are exposed to.
How AI Chatbots work?
ML algorithms break down your queries or messages into human understandable natural languages with NLP techniques and send the response similar to what you expect from a human on the other side.
Let us share an example of how Chatbot works.
“Book a flight from LA to New York.”
“How many people are traveling with you?
The response sent back by the bot looks so natural, the way you expect from a real human being. But, do you know a lot of work goes behind to provide you such experience.
Let’s understand all these techniques in more depth.
- Text Classifiers:
In this technique, words and sentences are divided into significant intent. Chatbots understand the intent and respond accordingly.
Text classification is the process of assigning a set of predefined categories to the content. With Natural Language Processing (NLP), text classifiers can analyze text and create a set of pre-defined tags or replies based on the input text.
Bots depend a lot on Natural Language Processing technique. Human language may get chaotic and NLP has the capability to handle all the mess. Made up of various libraries, the NLP engine identifies and extracts entities, which are essential pieces of information provided by the user.
Chatbots are classified into two types:
- Chatbots based on fixed rules
- Chatbots based on machine learning
However, a chatbot based on machine learning incorporates artificial intelligence and can understand the language, not only commands. It can learn with more information or interactions.
Machine Learning is the system’s ability to learn from past experiences without human involvement and use what they have learned.
Computer systems learn by getting exposed to various examples with machine learning. The approach to learn from examples is based on how the brain learns and is called neural networks. Machine learning uses algorithms that are sequences of instructions commanding computers what to do. Algorithms can be arranged and combined in complicated ways.
When a chatbot gets an input prompt, it must identify the prompt and create context so that it can evaluate the required output. Since the chatbot is trained with data input, it finds patterns that it can store for reference.
Also, deep learning is a type of machine learning that employs layered algorithms called artificial neural networks. Instead of task-specific algorithms, deep learning uses techniques where the system explores representations in the data that enable it to make the context of the raw data. Every layer of algorithms contains interconnected artificial neurons. The prior learning patterns and events measure the relationship between neurons. Algorithms can search for patterns in huge quantities of data and conclude how to respond to new data.
Therefore, this approach works in AI chatbots, where a predefined set of responses is not workable or appropriate.
What are the significant advantages of using AI chatbots?
- Improved End-User Experience: Chatbots provide end-user support on a real-time basis in any setting, be it in a retail sales store, product support center/website or a business front or back office. Because these interfaces are readily available to end-users, there is no specific wait time. This means, customers or end-users can readily have the answers to their queries, which significantly enhances the user experience. Based on the query, chatbots can present users with rich content with documentation, videos and so on to help resolve queries.
Furthermore, chatbots can provide 24/7 assistance and support to customers and end-users. They can be programmed to provide automated answers to common queries immediately and also forward the request to a real person when a more comprehensive action is required. This has a significant positive impact on customer and user experience.
- Increased Face-time with Customers: Businesses can use chatbots to increase their face time with customers. Research suggests that modern customers expect a personalized experience with their favorite brands through increased interaction times and more personalized communication channels. Chatbots enable just that and more by providing easier and faster access both ways. Moreover, chatbots can be readily integrated into popular platforms such as Facebook or Instagram, thus enabling a seamless experience for customers and end-users.
- Analytics and Insights: Chatbots serve not only a great communication channel but also as a medium to gather insights around customer preferences and behavior. Businesses can collect instant feedback from customers and end-users through chatbots and then analyze the data to gather insights around their habits and preferences.
Besides, chatbots can also be leveraged to identify purchasing patterns and consumer behavior. It can help businesses make critical decisions around product marketing and launch strategies.
- Lead Generation and Conversion: With all the customer and end-user information that a chatbot aggregates, it is possible to help customers in their purchasing journey through focused messaging using a chatbot. Chatbots can be programmed to persuade and influence user decisions and increase conversion rates.
- Cost Savings and Scalability: Developing and implementing a fully functional chatbot is faster and cheaper than developing a cross-platform app or hiring employees to handle a large volume of incoming queries. Thus, businesses can make significant savings in terms of hiring, training and payroll costs. A typical chatbot would only involve the initial development cost and a nominal runtime cost, which is potentially lesser than the costs spent on actual human resources.
Furthermore, multi-lingual chatbots can be used to scale up businesses in new geographies and linguistic areas relatively faster. Businesses can program the chatbot to easily handle incoming queries without having to augment their staff readily.
Let’s explore some of the best AI chatbots which are being used across different industries.
- Watson Assistant
Built by IBM (one of the leaders in the AI space), Watson Assistant is the advanced AI-powered chatbot in the market. It is pre-trained with data from your particular industry so that it could understand your historical call logs, chat, ask customers for clarity, connect them with human representatives, search for an answer in your knowledge base and provide you training recommendations to enhance its conversational abilities.
Powered with deep learning-based natural language understanding and multi-tasking capabilities, Rulai is an AI chatbot for enterprise brands. It can predict user behavior, analyze the context of the conversation, take actions, move to different tasks, ask customers to get more clarity and understand customer preferences.
Designed explicitly for enterprise brands, Inbenta leverages its own NLP (Natural Language Processing) engine and machine learning to discover the context of each customer conversation and respond to their questions accurately. It has a dialog manager that allows you to design custom conversation flows.
When Inbenta chatbot feels that any of your customers should talk to a human for a specific concern, it escalates the conversation to the right support agent.
By gathering over 20 years of messaging transcript data and feeding it to the AI Chatbot, LivePerson, it can automate messaging for every industry and integrate with messaging channels such as mobile app, website, text messaging, Apple business chat, Line, Whatsapp, Google, Facebook Messenger, Google AdLingo and Google Rich Business messaging.
Bold360 patented its own NLP engine to allow brands to develop chatbots that can understand the customer’s intent without the requirement of keyword matching and know how to provide the most accurate answers. It can interpret complicated language, respond to customers with natural responses and remember the context of the whole conversation.
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