AI-assisted text chatbots have made their way into the landscape of e-commerce and online services. They offer help on bank and auction sites, answer questions about restaurant menus on Messenger, provide entertainment and even take care of our health. How have chatbots changed with the spread of AI?
Chatbots without AI support are based on rules entered manually by programmers. They display appropriate texts in response to keywords. The problem arises, however, if the customer does not use the right word, or if the chatbot does not include an algorithm to understand the contextual question, for example, “Will the stationery store be open the day after tomorrow?”. In such a situation, the chatbot repeats the request to change the query over and over again or redirects the customer to talk to a consultant after several attempts. Such problems in new-type chatbots are solved by implementing artificial intelligence.
AI-assisted text chatbots operate on completely different principles than their predecessors. The new chatbots learn by interacting with customers through the use of new technologies:
Because of this, interactions with them feel more natural to customers, while the chatbots themselves become more perfect with their application. Over time, they learn the language used by customers, for example, recognizing and understanding abbreviations, or colloquial product names. AI-based chatbots also correctly interpret words containing typos.
A new chatbot using artificial intelligence can also be taught using a record of conversations conducted by a legacy bot. This is very important for the continuity and consistency of business and customer communication. On the other hand, from the very beginning, the chatbot’s interactions with customers provide valuable material for user experience research thanks to its ability to analyze the emotional overtones of the conversation (Sentiment Analysis).
Such a solution, although very modern, does not have to weigh heavily on a company’s budget at all. This is possible because you don’t need to create a separate technology solution for each company. You can use an AI-assisted chatbots using the AIaaS model and teach it to work on your database.
Of course, implementing an AI-based chatbot also requires time and work from a specialist. However, its operation can produce very tangible business results that are difficult to compare with those of rule-based bots. An example of the difference between the way a rule-based chatbot works and a chatbot using AI is illustrated by the following excerpt from a dialogue:
The quoted dialogue shows the flexibility of a chatbot using AI – from the short question “What time do you close?” it guesses from the context that the question is about the store’s operating hours and today’s day. Such a chatbot can also be taught to answer in a specific style that sustains the impression of a conversation with a specific person.
The role of chatbots in a business context is growing. Most often, they function as virtual salespeople greeting customers as soon as they enter an e-commerce site. They also improve the experience of customers using large-scale websites whose reach would make it too expensive to be served by assistants. An even more advanced application of text chatbots is to use them for detailed, personalized product presentations.
AI-assisted chatbots are also used to carry on conversations with customers on WhatsApp, Messenger and other popular messengers, as well as used as standalone applications. Of particular note is the use of chatbots for:
Chatbots operating with artificial intelligence are very different from their rule-based predecessors. They can answer questions contextually, make inferences based on incomplete data, and provide expert care and advice to customers, for example, when using e-commerce. However, their application potential is much broader – they can dock customer needs, provide training, or act as assistants.
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Author: Robert Whitney
JavaScript expert and instructor who coaches IT departments. His main goal is to up-level team productivity by teaching others how to effectively cooperate while coding.
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