With the advancement of technology, companies are paying attention to innovations to start or boost their digital transformation strategies and optimize the customer experience.

Consumers, increasingly demanding and immediate, seek products and services that are easily accessible, with agile and personalized service.

We’ve already discussed here on the blog that no, bots cannot learn on their own, but they can evolve, and for this, technologies like Machine Learning and Linguistic Learning are essential.

Companies have realized that they can save time and money by using customer service bots. And these bots can indeed be great options for customer relationships.

However, rigid service bots, with only pre-set responses, can leave a bad impression, generating customer dissatisfaction, especially when their problem isn’t resolved.

Therefore, organizations of all sizes and from various sectors are investing in innovative technologies to have bots capable of performing complex and natural dialogues.

The ultimate goal is to streamline service, free up human attendants’ time, increase customer satisfaction, and, of course, reduce costs by cutting expenses on personnel or reallocating professionals to more strategic activities.

In this article, you will learn about the concepts of Machine Learning and Linguistic Learning and how these technologies can optimize your customer service. Enjoy the read!

 

What is Machine Learning?

 

Machine Learning, in Portuguese, Aprendizado de Máquina, refers to the ability of machines to learn on their own.

Machine Learning goes hand in hand with Big Data because, from large volumes of data and algorithms, it allows devices to identify patterns and make connections between them.

The goal of Machine Learning, with Big Data, is to collect, analyze, and process data so that machines can learn to perform tasks automatically, without human assistance.

Through algorithms and statistical analysis, machines can, with greater precision, predict possible responses and deliver more accurate results with a very low error rate.

 

Types of Machine Learning

 

Machine Learning can be separated into two categories:

Supervised: In this model, a human supervises the algorithms, controls data input and output, and also conducts machine training.

 

Unsupervised: This is where Deep Learning comes into play to execute unsupervised tasks, that is, independently, without human oversight.

 

What is Linguistic Learning?

 

Conversation is becoming increasingly important for interacting with a variety of technologies, from smart devices to apps and websites.

In this scenario, Linguistic Learning, in Portuguese, Aprendizagem Linguística, appears as an Artificial Intelligence resource that speeds up the construction of conversational systems.

The goal of Linguistic Learning is to build intelligent conversational systems that can be deployed in multiple languages, across different channels, regardless of the operating system.

Through Linguistic Learning, companies can reach a point where their customers respond by stating what they like and dislike, sharing their preferences and other thoughts – whether you ask for their opinion or not.

Thus, it is possible to analyze conversations in real-time to produce even more personalized responses to maintain the conversation and lead the customer to a logical conclusion.

 

How do these technologies complement each other?

 

A hybrid approach between Machine Learning and Linguistic Learning is the ideal world that all companies want to be part of.

These two technologies can provide intelligent machines capable of performing complex dialogues, simulating human interaction as much as possible.

Have you imagined the possibilities of applying these two technologies in your business’s customer service?

 

How to apply them in your customer service?

 

Find out how Machine Learning and Linguistic Learning can be applied to your business’s customer service.

 

Data collection, analysis, and processing

 

Machine Learning can collect, analyze, and process an unlimited amount of data, in real-time, and from this, offer more relevant products and services, with prices and discounts that customers are looking for, for example.

With pattern identification, companies can personalize their actions, from marketing campaigns and customer service to offering more relevant products and services.

With Linguistic Learning, it’s possible to reach the ideal vocabulary and tone of voice, which will generate more empathy and admiration from the customer.

 

Identifying customer behavior

 

Machine Learning provides a better understanding of the wants and needs of customers, both in terms of the products and services they are looking for and the communication platforms they prefer.

 

Identifying areas for improvement

 

Identifying bottlenecks and areas for improvement is another way to apply Machine Learning in your business. With smarter machines, it’s possible to discover, for example, the best days and times to contact the customer and thus increase the chances of closing a sale.

 

Supporting the customer support area

 

Machine Learning has the ability to gather all customer information, as well as all the problems encountered during past contacts and the best solutions for each situation. Linguistic Learning, on the other hand, identifies the best way to address the customer, for a more assertive conversational flow.

That’s it! With Machine Learning and Linguistic Learning, the possibilities are endless. And who benefits from all this is your customer, who has a better experience, and your business, which improves its results.

 

Thank you for reading. See you next time!

 

Also read: Learn how to increase customer satisfaction in your business