Chatbots look simple and function seamlessly, but they require meticulous coding and algorithms that help machines understand and process human queries.
Typically, chatbots are linked to the customer relationship management apparatus. In real time, the chatbot scans historical data provided by the company, and from other sources, and matches customer queries with the best possible answer — by using several permutations and combinations of the keywords used.
But making the machine understand human language is tricky and requires several complex tools. Technologies such as Natural Language Processing and advanced AI tools help developers make the chatbot better understand queries and respond like a human.
While rule-based chatbots stick to a strict regimen of functions and do not necessarily evolve, AI-based bots learn from every interaction and enhance their skills. They process the original conversations to arrive at conclusions and study patterns to find correlations in customer behaviour so they can provide an improved feedback the next time. While rule-based chatbots do not necessarily maintain a human character, AI bots respond like a human and customers won’t feel any difference, especially if it is a text-only service. Though pure AI solutions learn and evolve rapidly, traditional chabot solutions that rely on frequently asked questions and answers, coupled with pre-set parameters, provide more accurate answers to customer queries.
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