Chatbots help customers to resolve their issues at a blazing speed but the one of the main questions is whether the business should opt for a rule-based bot or an AI- based bot.
Chatbots are not new in the technological arena. They are a lot smarter now than their predecessors. The primary reason is being a new age Artificial Intelligence augmentation as well as other technical advancements by the AI development companies. Let’s think about the bots that are appreciably smart and answer logically. They are often confused with smart assistants like Google assistant, Amazon Alexa, and Apple’s Siri. We know that at present chatbots cannot solve complex situations without human intervention. There will soon be a day when we won’t be able to tell the difference between human conversation and a chatbot.
According to HubSpot, about 71% of people use Chatbots for a faster solution of problems. People don’t like human interactions. Due to this reason, about 53% of people prefer a business with texting service enabled. Also, 56% of users prefer texting over call customer care.
Role of Chatbots in modern society
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Chatbots were introduced to reinvent the way business houses interact with their customers and solve problems. How can anyone forget the days when BPOs were overloaded with customer calls. Most calls, e-mails, and texts were trivial in nature! The result was that the executives failed to attend all the customers. As a result, the brand value depreciated at an alarming rate. It was realized that most customers ask repetitive questions. Thereby consuming valuable time of the executive who could have solved a genuine issue of a customer. That was when machine learning consulting companies came up with the idea of automating the entire customer care process using chatbots. The chatbots now help the customers to resolve their issues at blazing speeds. It also gives the company the independence to focus on issues that require more attention.
Sir Alan Turing developed the Turing Test in 1950 to check the intelligence of the machine using the Turing test. It is a test to exhibit intelligent behavior that imitates its human counterpart in a differentiable way. According to this test, a human evaluator judges natural language processing between a human user and the machine and the extent to which it responds like humans.
The global chatbot market is expected to hit the billion-dollar mark before 2025. It implies a steady growth of 24.3%.
We don’t know about the intelligence of chatbots and how far they have come since their inception. Is there a way to make them more intelligent? Yes, there is a way.
Chatbots Categories: –
- Rule-based chatbots
- AI chatbots
Out of the two, AI chatbots have recently gained a lot of recognition in recent years. They are popular in FMCG business houses and logistics business. However, it is a tough decision on which one to go for while setting up a business. Let’s dig deeper into this.
This is the primitive type of chatbot and is very specific regarding its versatility. It answers questions and takes the necessary steps as per the codes punched into it. While working with them, one needs to keep in mind that the questions asked must be direct and simple. Only then the desired answer can be expected. Moreover, the answers are much general when compared to those from AI chatbots. A bot development company can build rule-based chatbots either with simple codes or complicated ones. It depends on the requirements stated by the company. But the bot won’t do anything outside its code protocol. So, it might be difficult for a customer to find a solution for a new issue that has not been programmed. They are developed on Artificial Intelligence Markup Language. This type of bot has a high probability of failing the Turing test if it strictly abides by a particular model.
There are certain advantages of rule-based chatbots too like they incorporate direct-action buttons for many regular tasks such as sending an email, uploading an attachment etc.
AI chatbots in comparison with rule-based chatbots provide human-imitated reaction to the issues asked. They give specific answers to each issue by learning natural language response and regular updates in a machine learning engine. It gets better with more usage. An AI chatbot’s basic advantage is the ability to be available all the time which accounts for 64% of its functionality. The next 55% of advantage accounts for instant responses. While the rest 55% is because of answering easy questions.
Since the Artificial Intelligence companies in India are using machine learning to improve the functionality of chatbots and are making them more intelligent.
Chatbots can be modeled on two principles:
Retrieval based models: They are trained specifically on some questions and their possible answers. It is like a database of questions, and their answers are provided to the chatbot. When a question is asked, the bot searches the most relevant answer from the lot and displays the one that is selected. It is different from other AI bots as it cannot generate a new answer to the question. But since they rely on machine learning, if the database has been arranged accurately, they can solve the queries commendably. It is up to the decision of developers and AI consulting services to set the rules of the query with ranging difficulty. The difficulty level is set using machine learning algorithms, and a suitable answer is selected. The advantage of this type of chatbot is that there is no issue regarding language and grammar as the answers are pre-set and don’t clash with the syntax priority.
Generative models: They are better than rule-based chatbots since they can generate a new answer and the replies are different from the previous one. The reason for their better performance is that they take words from the query and generate the answer accordingly. They have a shortcoming due to this property that they are more prone to errors than retrieval-based models as they require a spelling and grammar check before displaying the answer. For removing this issue, they need to be developed with better codes and guidance of expert machine learning companies in India. After full training, they can give the rule-based models a run for their money.
Proper planning and execution are necessary for the success of a chatbot. A report states that 43% of people prefer interacting with human first. Among them, 30% are concerned with chatbot mistakes. If these issues are not taken care of, the acceptability of chatbots will be hindered.
For a business to decide on which type of chatbot to be used for its processing, the Turing test results must be taken as a decisive result. The rule-based bots can be preferred for a business that deals with straight questions that don’t require much intelligence and customized answers. Business dealing with delivery, tracking, and logistics offer the best application for rule-based chatbots while AI chatbots are ideal for customer issues, where pre-set answers cannot serve the purpose of satisfying the customer.