August 01, 2018

The Advent of NLP and Chatbots

A few years ago, having a “conversation” with a machine was a frustrating and often comedic process. But today, thanks to machine learning algorithms, it’s getting increasingly closer to a point where it will be harder to tell whether we are talking to a human or a computer. And that’s with natural language processing (NLP) and recognition being far from perfect.

Businesses in various verticals are starting to capitalize on this, as seen with the deployment of increasing numbers of chatbots. Usually these are found in customer services functions, but we’re starting to see more in internal processes and to aid in training.

Chatbots and their background technology of NLP are going to become very important and strategic for businesses in the future, by fundamentally changing the way we provide services, how we understand the sales process, and how we execute marketing.

Customer Adoption of Chatbots

It makes sense that businesses want to invest in chatbots – it’s innumerably cheaper to carry on thousands of customer service conversations simultaneously with a machine than with a giant call center of people which would be needed to do the same. But from a customer service point of view, they’re only willing to engage with chatbots if the service they receive is faster, more efficient and more useful.

The key to achieving an efficient utilization of NLP technology lies in aggregation and augmentation. Rather than thinking of a conversation taking place exclusively between one machine and one human, artificial intelligence (AI) and chatbots can be used to monitor and draw insights from every conversation and learn from them to perform better in the next one. Augmentation means that the machine doesn’t have to conduct the entire conversation, rather chatbots can take the lead for routine tasks such as answering straightforward questions from a knowledge base or taking payment details.

In other situations, the speed of real-time analytics that are available today mean that the bots can raise an alert when they detect an anomaly (i.e. a customer becoming irate thank to sentiment analytics) and prompt a human operator to take over the conversation.

Experts believe that in the future chatbots will be able to take things even further and propose strategy and tactics for overcoming business problems. In marketing this could be crafting marketing messages, based on understanding the language of all the things that have been successful in the past. In customer service this could be allocating resources for dealing with customer cases based on the classification and sentiment analysis of the conversations they are having.

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