The most common instances of online chat bots usually take the form of website support helpers. On heavily trafficked e-commerce sites, you can find a “Chat now” option somewhere to help speed you through the purchase funnel. In other capacities, they can answer questions or log a support ticket.
Although, the simplest function of a chat bot may not be one you typically think of: search engines. You type out a question, it reads and understands the words, and then returns a response as accurate as possible. Of course, a search engine such as Google pulls from a wealth of information to return millions of results and ranks them according to what it thinks you’re looking for. But a standard search engine on a website functions the same way.
In terms of efficiency, they work wonders since a user can talk to a chat bot while still performing other tasks online. Another reason for their popularity is that a chat bot can offset the need for a human to become involved until necessary. Similar to voice recognition, this software acts as a companion element to a user and assisting with administrative tasks.
Processing typed information to digital forms, placing procurement orders, and taking support tickets are just a few ways these AIs can be implemented. Designed for convenience, a chat bot is a secure and easy way to access internal systems, such as requesting a password to be reset or create a new employee account. They are also able to integrate into a wide range of business applications such as Outlook or Salesforce.
Unlike voice recognition, chat bots do not necessarily require a vast neural network to process user input since keystrokes can already be parsed by a computer. However, a variety of natural language processing (NLP) and natural language understanding (NLU) techniques are utilized in an attempt to understand and engage with the user. Because there is no one algorithm that can be used for this task, a variety of processes are put in place depending on the environment and need. Some common NLP techniques include simple pattern matchers, the multinomial naïve Bayes algorithm, tokenization, and named entity recognition.