How Data-Driven Companies Are Using Text Analytics and NLP

Text Analytics and Natural Language Processing (NLP)

Text analytics and Natural Language Processing are the next phases in the evolution of technology. Industries accumulating unthinkable volumes of data have driven large corporations to resort to text analytics and NLP to simplify numbers and aid decision-making within an organization. Advancements in Text Analytics and NLP will help computers gain contextual understanding and even non-verbal cues like body language, expressions, etc. 

Here are 4 ways how data-driven companies are using Text Analytics and NLP -  

To Build a Data-driven Culture

Text analytics and NLP are used to foster a data-driven culture. Data analysts and professionals alone will not be the only ones handling data input and analysis. The input and interpretation of data sets will be made accessible to everyone. Experts refer to this process as ‘data democratization. Data democratization will equip more people to derive insights from the data and interpret them. Nurturing a culture that relies on evidence to make observations will make a company dynamically data-driven.  

To Develop Professionals

Knowing how to ask the right question powers the quality of an insight or an observation. The advent of Text Analytics and NLP has made data analysis highly accessible to professionals from all walks of life. Knowing how to ask the right questions is a skill that will be essential for administrators, business operators, managers, etc. This will ensure that all employees are capable of deriving critical insights and making informed decisions.  

Manage Big-Data

NLP allows users to analyze volumes of data, even for critical research and development. Machines can seamlessly find, evaluate and summarize critical information from vast amounts of unorganized data that would be impossible for a human to analyze. The speed and precision of machines help us tackle several critical issues that would otherwise take forever.  

Pharmaceutical and insurance companies, for instance, refer to a medical compendium that lists approved and preferred drugs for treatment. This list is exhaustive and constantly under revision, and pharmaceutical companies have a lot at stake with a particular drug moving up or down the list. The review of the compendia has always been done manually, increasing the risks of changes being spotted too slowly or not at all. Machines can help alert the concerned authorities when there are changes made to the compendium, ensuring that these data-driven companies avert possible losses.  

Predict Trends

The inability to predict trends in the market can lead to missed profits. A company that is slow to hop on the trend might struggle to keep up with the trend, resulting in low sales. This could affect the brand image, perception, and credibility. NLP and Text Analysis could help companies and brands hunt for trends and predict demand for their products with ease.  

The scope of Text Analytics and NLP is wide. Both have the potential to make applications and businesses consumer-friendly. They skip the process of having to translate queries into computer speak, which will enable humans to interact with computers in ways we never imagined.