5 Ways Businesses Can Benefit From Text Analytics

Text mining and text analysis are newer contributions to the data science field. However, they’ve already had a huge impact on the business world. Businesses get larger amounts of unstructured data. And these strategies help them turn that data into meaningful and actionable resources.

What is Text Analytics?

In the corporate environment, text analysis can play a variety of roles. Categorization and sentiment analysis are two of the most common examples. Thus, text analytics is all about finding patterns and knowledge in data that could otherwise be unintelligible.

#1. Improving Cybersecurity

It’s a well-known fact that becoming 100% secure against cyber threats is difficult. In this digital age, data breaches are inevitable. Large organizations with technology as their focus fail to prevent leaks and attacks. Meanwhile, smaller businesses with fewer resources are even more exposed. Every day, approximately 2,000 hacks happen, putting businesses of all kinds in danger.

On the other hand, Text analytics can help in a variety of ways, including real-time protection. Through logs and reports, corporate cyberdefenses develop vast amounts of data. Text analytics can help catch trends and weak points way faster than a human can. It works often faster than specialized security tools.

#2. Upgraded Client Management

Client communication and big data go hand in hand. Businesses and their customers generate huge volumes of data. Much of this data never sees the light of day. However, from emails and chatbots to help desk tickets and social media engagements, we’ve got you covered. Text analytics can help firms figure out what their general client base expects. It uncovers potential problems before they become unmanageable. Moreover, it helps get a sense of how people feel about their brand.

Most CRM systems will have text analytics as a standard feature. Once they reach tens of thousands of records, the technology becomes the greatest way to assess and organize data in the future.

#3. Public Relations

Text analytics can be used to gauge sentiment beyond what current customers believe. For example, in a world where a string of bad reviews can cause a tiny business to go worthless, brand and reputation management has never been more important.

Over 90% of internet shoppers read reviews before making a purchase. Therefore, these ratings are beyond a company’s direct control. 

This example demonstrates that text analytics can extend outside a company’s own data. Brands can monitor social media, chat rooms, forums, and review sites with the correct technologies in place. It will help them to see how their reputation is being discussed online.

Text mining is inherently efficient. Thus, it’s possible to follow much more than a human or primary software could. For example, everything from the principal brand name to specific goods, executives, and anything else relevant to the firm has a pattern. One can find these patterns and process the data.

Text mining parses and processes massive volumes of data. Moreover, it discovers patterns and anything else noteworthy in the data on its own.

#4. Lead Generation

Text analytics can be set up to help you to maintain existing customer relationships. Also, it helps you find new ones. While only publicly visible information is useful here, text mining can filter through the reams of shapeless data produced on social media every day to find where a business can fulfill a need.

It could be as basic as a single tweet expressing interest in a product. However, in the past, the few organizations that pursue leads from tweets had to depend on hashtags and mentions to even be aware that their products were being discussed.

Text analytics can outperform even the most feature-rich social media systems. It is all thanks to its ability to recognize and analyze generic phrases. For example, when someone expresses an interest on social media, they may not be aware that the company sells a product or offers a service. Text analytics solutions can spot such a need. Also, it doesn’t matter how vague, alert sales and marketing teams are to a possible audience expansion.

#5. Recruitment

In the recruitment market, technological advances, notably AI, have not always been well received. The rising use of keyword-based screening software and filters has resulted in a degree of uniformity in resume submissions. In fact, job applicants must perform equal search engine optimization on their applications. Only then will they be viewed by a real human.

On the other hand, similar technology can help organizations in more exciting ways. One of them is saving time for hiring managers. It’s comparable to the lead-generating benefit. The only exception is that it concentrates on finding the best personnel possible.

For example, one of the ideal periods to find the top personnel is before they become available on the open market. With less competition, there’s a better possibility of identifying the top talent faster. And text analytics can spot exceptional prospects just by citing that they’re thinking about taking on a new task.

To Sum Up

Brands now have access to more data than ever before. Thus, they’re always looking for ways to make that data useful. Text analytics is a very promising science, and early adoption may only be the beginning. In the end, it will allow businesses to monitor any public material across any platform. Meanwhile, it’ll also decipher the data to help them achieve their business objectives.

Text analytics, when used correctly, will prove to be a critical component of modern brands’ ever-increasing data collection efforts.