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What Is Text Analytics?

Text Analytics is the computer-driven process of analyzing large volumes of unstructured text data, utilizing Artificial Intelligence (AI) techniques to identify new and previously unknown insights, themes, or patterns in text.

The Importance of Text Analytics

The ability to use AI on unstructured text data, such as user reviews, client feedback, customer opinions, and more, can be very powerful and insightful for businesses. Especially in today’s “digital” environment, when such an avalanche of data is available. There is a wealth of information stored in emails, Tweets, call center agent notes, surveys responses, etc. Trying to analyze all this data by manual means is an impossible task!

Text Analytics is the solution to unlocking the undiscovered insights from the types of unstructured data listed above. It uncovers patterns, trends, and themes in the data to reveal wants, needs, and thoughts—in other words, insights. The ability to track this information can provide earlier detection of potential business trouble because it tells us why dissatisfaction exists relating to your company, product, or service.

Gain A Competitive Edge

Using Text Analytics with competitors’ data gives businesses an opportunity to have an advantage. Unveil the hidden areas your business can hold over your competitors. For example, based on competitors’ customer review data regarding product pricing, offerings, location, etc., a company can see where they stand in the market. This allows businesses to find their strengths and weaknesses and adjust their strategies and business decisions accordingly.

Save Time With Text Analytics

Gaining insights from reviews online, survey responses, and social media is not a new idea. What makes Text Analytics so compelling is its efficiency. Before Text Analytics, people had to manually sift through unstructured data, text, and written communication themselves to discover trends (and some still do). This was both labor-intensive as well as time-consuming. Text Analytics uses AI to quickly analyze the data, providing faster results with minimal labor cost. For example, TD Bank, an American national bank and subsidiary of the Canadian multinational Toronto-Dominion Bank, used Text Analytics to create categories for employee benefits mentioned in the annual TD Bank employee survey. The 20,000 surveys had previously been reviewed manually by four groups (5,000 surveys each).

Text Analytics In Your Industry


Healthcare providers, the pharmaceutical industry, and biotechnology firms use Text Analytics to improve patient outcomes, increase drug discovery, and manage regulatory compliance. Unstructured data in pharmaceutical companies may include physician’s notes, pathology reports, operational notes, and electronic medical record data. The strict regulations of record-keeping in healthcare has led to giant databases filled with unused data. Text Analytics opens the door for the healthcare industry to utilize the stacked up unstructured data. Use cases of Text Analytics in this industry include discovering new drug compounds, matching participants to clinical trials, and marketing pharmaceuticals.


Stock market traders must buy and sell stocks at lightning speed, so every second matters. In this environment, any small yet critical piece of information can cause the market to flip. Text Analytics provides easy tracking and detection of breaking news or stories with relevant information, creating an opportunity for traders to form quicker, better, more accurate decisions about their assets and potential buy-sell trading actions


Retailers can now lose the fear of missing out on emerging customer trends. Text analytics helps retailers analyze, understand, and act on data from various real-time customer feedback channels, such as third-party online reviews, blogs and forums, and comments on social media. Yankee Candle, a popular candle store in the United States, used Text Analytics to sift through tons of online text to discover what scents people associate with different seasons. By the end of their research, they came out with a very successful new seasonal scents launch.

Aviana Success Story: Cisco

Insight Into Hearts And Minds

Cisco, a multinational technology company, came to Aviana Global Technologies wanting to find a way to keep their top talent happy and avoid losing them to the competition. Text Analytics was the perfect solution to their problem.

The Cisco team used text mining techniques to analyze more than 18,000 free form responses from employees who completed the optional text sections of the company’s employee questionnaire. Under the guidance of Aviana’s lead consultant, the team built a sophisticated SPSS model which combined cluster analysis techniques with unstructured text sentiment analysis.

The team was able to segment the data by function for a customized view of different business areas, such as Engineering, Sales, Cisco Services, Supply Chain, and so on. The sentiment analysis assessed how positive or negative employees felt about many other cultural issues within the company.

Let’s talk about Text Analytics