While for many, the words, sentences, and numbers contained in texts may only represent letters and numbers, in the world of computer science, behind those symbols lies a world of answers. Just like social media platforms, through artificial intelligence, are able to know and understand people’s interests by showing them ads of things they have already searched for, numbers and letters can also reveal and disclose valuable and interesting information.
Machine Learning, for example, is one of the branches that has the ability to develop techniques for computers and devices to learn to identify patterns among certain data. One of the allied systems to reveal the meaning of these symbols is Amazon Comprehend, a service that simplifies processes and allows for understanding information by identifying key elements in the data.
However… What are those data? They are called unstructured data, and among them, the following stand out: audio-to-text, product reviews, social media comments, emails, and insurance claims, among others.
In relation to the above, what this system does is process natural language (NLP) using Machine Learning to uncover valuable information and connections in texts. One of the main objectives of this service is to understand what the customer is experiencing and take actions to provide a better experience and engagement with them.
Some examples analyzed include: Call center analysis exploration, which means detecting customer sentiments and analyzing their interactions to improve products and services. On the other hand, another highlight is: Customer service ticket optimization, which involves automatically categorizing incoming support documents, such as product reviews, and extracting important information to resolve customer issues more quickly.
In conclusion, it can be said that through Amazon Comprehend, data is analyzed to cross-reference and understand customer behaviors. All of this is done in order to satisfy their needs.
