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Text analytics revolutionizes the way business managers collect customer data from across the web. 

With text analytics, managers can obtain customer feedback from blog posts, customer surveys, social networks and other online sources. Managers also can store this information, add to customer data sets and review customer data any time they choose. 

Don't expect the push for text analytics to slow down any time soon, either. 

Markets and Markets has projected the global text analytics sector will expand at a 17.5 percent compound annual growth rate (CAGR) from 2015 to 2020. The market research firm also noted the global text analytics segment will be worth $5.93 billion by 2020. 

What Is Driving the Push for Text Analytics? 

Today's business managers demand the latest and greatest data analysis technologies. As such, many managers are implementing text analytics in the hopes of generating deep customer insights that they may struggle to obtain elsewhere. 

However, it is important to note that text analytics fails to provide a one-stop resources for full data analysis. Although text analytics helps managers obtain customer data from across the web, it rarely, if ever, offers a simple, effective way to analyze large collections of customer data quickly. 

After a manager retrieves customer data via text analytics, he or she then will need to perform data mining ñ something that often proves to be time-consuming and difficult. 

Data mining requires a manager to look at all of the customer data that is available and identify patterns and trends that are hidden within it. 

In many instances, managers lack data mining expertise, which means it may take them many hours to analyze even a single customer data set. Or, managers may be forced to hire data scientists to mine customer data for them, which further increases the costs associated with data analysis. 

Ultimately, text analytics represents one piece of a complex data analysis puzzle. It empowers managers to collect customer feedback quickly and effortlessly. At the same time, text analytics lack data analysis capabilities and makes it tough for managers to transform customer feedback into meaningful insights. 

Managers can use text analytics as a starting point to effective data analysis. And when text analytics is leveraged in combination with Self-Service Text Analytics, managers may be better equipped than ever before to optimize the customer data available to them. 

Why Do Business Managers Need to Use Text Analytics and Self-Service Text Analytics?

Text analytics allows business managers to collect a large assortment of customer feedback from many online sources. Meanwhile, Self-Service Text Analytics works in conjunction with text analytics to help managers transform this information into actionable insights. 

Self-Service Text Analytics visualizes customer feedback via charts, graphs and other illustrations. It also analyzes customer data without the need for data mining to help managers save time and resources when they perform data analysis. 

Perhaps best of all, Self-Service Text Analytics is free, making it a viable data analysis service for managers at companies of all sizes and across all industries. And with the service's user-friendly design, managers should have no trouble visualizing customer feedback in only minutes. 

To create a visualization report via Self-Service Text Analytics, a manager will need to upload an Excel spreadsheet that contains user-generated content ñ a process that requires just seconds to finish. Next, after the upload is finished, the manager will receive a visualization report via email within about 15 minutes. The report may contain dozens of pages of visualizations to help managers understand assorted customer behaviors and trends like never before. 

Text analytics and Self-Service Text Analytics offer the ideal complementary data analysis services. They allow managers to collect and analyze customer data and gain the insights they need to drive consistent business improvements.

Summary

Text analytics is becoming increasingly popular for business managers around the globe, yet few managers possess the skills and know-how to maximize its value. Today, Self-Service Text Analytics is available to aid managers as they search for ways to generate meaningful insights based on structured and unstructured customer data. With text analytics and Self-Service Text Analytics, managers can visualize customer insights and find out why customers may select one brand over another, how customers rank a company's products and services and much more.