It is everywhere-from the marketing materials you send through the mail to the incoming queries from customers you get on your website. Text encompasses the life of any business owner, even though for the most part, text is overlooked because it is such a broad and natural component in the business world. The thing is, text in whatever form can be used to harness powerful data through a process known as text analytics. If textual analysis from a place like DiscoverText is a new idea for you, it is definitely time to perk up and listen. Here is what you need to know about text analytics and what it means for you. 

What exactly is text analytics?

In general terms, text analytics involves surveying a piece of text to gather certain data that can then be used for other purposes or stored for later retrieval and review. There are several points that are assessed during text analysis, such as 

• word frequency 
• word distribution
• word patterns
• word associations
• word algorithms 

The data that is harvested can be used and further examined to better understand the underlying goals, intentions, and meanings of blocks of text, whether it is a simple paragraph or a full page of words. 

How does text analytics happen?

There are actually analytical text softwares, programs, and processors that are specifically designed to analyze text. The basic processors can review a piece and rapidly provide feedback on the aforementioned word usage and patterns. However, there are more modern text processors that continue to evolve into far more technical pieces of equipment with the inert ability to basically understand text, not just survey it. In a business setting, basic text analytics software is the most common way the process is integrated into daily processes. 

How can text analytics be used for business marketing purposes?

Text analytics can be highly valuable for various level of business operations, but specifically where marketing is concerned. The data harvested during the processing of text can be stored electronically and pulled up for review, which means you could essentially build a textual analysis profile of customers and use that data to better aim your marketing efforts. For example, if you create a satisfaction survey for customers, the text processor can go through these surveys and give you a broader look at what text was used in open-ended questions. This information can greatly help reduce time and effort of assessing every individual response and gives you a broader view.