The conversational AI uses natural language processing or NLP methods which can easily respond to a user’s problem and anticipate something the user hasn’t even asked yet. A robust user engagement strategy uses both types of conversational AI approaches to put NLP in action.

Approaches to AI technology

By using a reactive engagement with the user, businesses provide an easy way to all the people and Clinc is one of the company which provides help and dynamic search bars to simplify the digging through the FAQs, the solution to the repetitive questions. With the help of the amazing Conversational AI, technology businesses can reach out to the users in an effort to keep them moving along with the journey of the users. A proactive approach is taken to conversational AI no matter what channel users are using, time of the day they are usually searching, or any native language they speak, businesses can engage the users with personalized and contextual information. This also helps to create more opportunities to establish new relations, convert more sales, and prevent users churn. This also helps businesses to allow the intervene at the critical time basically when a user toggles back and forth in between two item choices, or they hesitate at checkout time and enables organizations to quickly support their users outside of normal business timing.

When you look at natural language processing examples then you can easily consider what is happening on the back or how the AI is learning to have these proactive communications. The opaque AI or black box AI which is associated with deep learning and potential users is not provided to the computer ahead of time. Instead, the provider customer inputs a few unstructured data and the computer reaches new solutions on its own by using this deep learning algorithm.

Another approach is transparent AI or white box AI which basically uses structured data and preset algorithms so that the result will match a pre-defined set of outcomes. In simple words, all the possible results are referred to ahead of time. This is because it relies on the human programmers to map inputs to the correct result. Many businesses usually prefer the approach because it helps them to stay in control of what the bot is able to speak to protect the brand image.