No matter how quickly technology progresses and businesses experience the subsequent benefits, people are usually looking ahead to the next big thing. The same can be said of big data. Once organizations began compiling massive amounts of data intended to streamline operations and improve revenues, they knew they had discovered a highly valuable strategy with far reaching effects. Big data was put to use quickly and has been a big boost for companies in a wide variety of industries. But what comes next? For many businesses, the impact that big data has had so far is nothing compared to the potential it offers in untapped ways. First and foremost on the list is the barely touched realm of text analytics, also known as text mining. Many view text analytics as the area that may hold the most promise for companies wanting to truly delve into the possibilities of big data.
If anything, businesses for many years have only been taking advantage of one aspect of big data — structured data. Put simply, structured data involves cold hard numbers that can be strictly measured. This might refer to how many people visit a website, how many items of a particular product are sold, how much of a product a company produces, and many other aspects. Structured data can be vast in its scale, but its measurable quality makes it relatively easy to work with and analyze. Platforms and programs have been around for a number of years that take advantage of this fact. What’s far more complicated, however, is the flip side of the big data coin — unstructured data. This is data that is far more difficult to measure through numbers alone. That challenge has made it harder to access for the majority of companies, but businesses that want to have more future success will need to unlock unstructured data’s potential, and that all begins with text analytics.
The goal of text analytics is essentially to turn all that unstructured data into structured data. Considering that roughly 80 percent of all data is unstructured, this is no small task, but it shows how much a company can gain from doing it. Unstructured data can take many forms, from Facebook posts, to tweets, to voice recordings, online reviews, and even videos. Interpreting all of that information comes down to having the right technology to do so. With text analytics, companies can extract valuable data from information that would normally be difficult to quantify, such as a social media post. Such information may be recorded through manual labor, but text analytics is much more efficient and can take into account the entirety of a product’s or brand’s mentions on the web.
Text analytics can essentially determine important questions such as who is making the comments, where comments are being made, what’s being said, and even the context of the unstructured data. All of these findings can then be made into more reliable business intelligence, providing new insights into future trends and patterns that companies can then act upon and prepare for.
The true benefits of using text analytics to measure unstructured data are highly sought after. Text analytics basically allows companies with the technology to listen to all sorts of conversations happening online and elsewhere, giving them a much larger sampling of customer sentiment. Text analytics along with ad hoc analysis also helps organizations better determine the likes and preferences of customers, helping them pinpoint what motivates them, which can in turn help raise revenues. The feedback gained from text analytics is also unfiltered, giving companies a more accurate picture of how consumers really feel from multiple different sources. All that new information also helps businesses come up with innovative new ideas for products, which can drives sales upward as well.
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