Selecting the Best Text Analytics Software

By CIOReview | Wednesday, August 10, 2016
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Text analytics is a fast-growing area, although it is still new for most organizations. It is advisable for CIOs to understand whether the process would be beneficial for the organization prior to implementing it.

Importance of Text Analytics

Text analytics helps an organization in extracting valuable information from emails, blog posts, and other unstructured corporate data to uncover new patterns and themes. As such, by deploying text analytics software in its organization, a CIO can better keep track of the changing work environment.

However, with many content and sentiment analysis tools available, deploying the correct software can be tricky for organizations. Here are some aspects that organizations can assess before finalizing whether the software suits their organization or not:

1. Self discovery and identification of channels—Prior to deploying text analytics software, it is imperative for CIOs to identify the channels through which information flows into the organization. This is an important step as it provides insights into what the organization wants to achieve with the use of text analysis.

2. All kinds of content and users must be identified—Identifying the different kinds of content available as well as finding out its usage patterns is the next step. It is essential in order to carry out any evaluation of text analytics software.

3. Use it as a platform for better results—Approaching text analytics as a platform is another essential step in the selection of the right software. Most organizations look at it as something that is going to be used in a single application. However, they will be better served if they use it as part of a broader operational or analytical solution. This enables the organization to move beyond project-based text analytics into a more comprehensive and integrated analytics.

4. Use it to solve an existing hitch—Another step that CIOs can take is to identify a doable real-world business issue that can be solved in a short timeframe with the help of text analytics. This would help them guage its effectiveness of meeting the organization’s needs as well as save valuable cost as most vendors provide limited proof-of-concept trials free of cost.

5. Ask for proof-of-concepts trails—To learn more about the software, proof-of-concept trials can be run by organizations. Provided by vendors, this enables CIOs to know about how the software works and how helpful it will be for the organization. During this period of evaluation and development, CIOs can figure out the skill sets required to take the project forward.

6. Use the software capabilities and features as evaluation filters—While evaluating text analysis software, it is important to take into account the fact that it is different from traditional software. As one product may vary from the other in regard to what it offers, it is imperative to find what fits all the organization needs.

Conclusion:

With organizations realizing the potential of text analytics in decision making, its use has been on the rise lately. With the software usage expanding across industries, there is no doubt that the trend is likely to continue. As more and more companies come up with text analytics products, this technology is gradually moving toward the realm of cognitive computing leaving behind its traditional approaches. Keeping this in view, it might not be long before we see text analytics impacting every household and business alike.