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The Importance of Content Analytics

The Importance of Content Analytics

In today’s business world, the ability to analyze content is vital. Over the past decade or so, computers and processing systems have improved to a point where they are capable of accurately recognizing a variety of different types of content. The added ability to actually analyze the content that’s recognized allows companies to easily match content with various rules put in place via the software. It makes it possible to spot trends and to pinpoint any strange behaviors and instances. Ultimately, it gives companies a greater insight into their own business.

Currently, “big data” is a buzzword that’s been garnering a lot of attention. The sheer amount of data generated on a daily basis is staggering, and even smaller companies are finding that it is nearly impossible to keep up with the influx given their current systems, which are often woefully unprepared to handle large amounts of data.

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The success of content analytics is always based upon the manner in which the content is managed and stored. Too many companies have poorly cataloged content, and it is often spread across a number of different areas, making it difficult to utilize properly and efficiently. The utilization of poor quality tools and software can make accessing the data difficult, particularly when it is spread out amongst a number of different content resources. By using reclassification tools and content correction tools, it is possible to have a much tighter grip on content analytics, and this is something that more and more companies need to consider.

How Does Analytics Work?

In order to perform any type of analytics, you first need to gather the data. This data comes from a wide range of different sources today. It could be searches performed on a company’s web store, emails, plans, and a host of other channels. Everything from simple searches for words and phrases to contextual analysis are all possible, but all of that content needs to be accessible by a single software system to get the best results.

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While many companies have been trying to reduce the amount of data that they have on file to make it easier to manage, that may not be the best solution. In fact, a large number of people believe that rather than deleting the old content and data, they would rather enhance its value using auto classification tools. Therefore, better organization is the key to making content analytics work properly.

A large number of organizations understand that the best way to get control of their data is to implement a better system for content management. However, they also need to make sure that they consider content analytics at the same time. They need to work together for companies to get the best results. Combined, they can help to increase business insight, as well as productivity for the company.

In addition, it is important to take steps to reduce the amount of “dark data” they’ve gathered. This term refers to personal information about clients, customers, and employees, as well as information that may be business sensitive. By eliminating as much of this type of data as possible, it can help to increase the security of the business. It can also help make the rest of the data become more manageable overall.

The Need for a Chief Data Officer

Often companies come at the problem of storing and analyzing data the wrong way. Instead of having someone in charge of the data from the start, they simply try to fix problems as they come along. It’s akin to bailing out a sinking ship with a teaspoon – eventually, it will become too overwhelming and the ship will sink. Instead, it makes more sense to consider appointing someone as the chief data officer or chief digital officer for the company. These officers can help to control the data, raise awareness whenever there is a problem, and take care of ensuring smooth operation of the data analytics. This is a step that companies will have to take sooner rather than later. Data will not stop flooding the company and there needs to be people in place to handle it all.

One of the other benefits of having someone in this position is their ability to focus on the software aspect. They can learn the ins and outs of new content analytics software and see how it can benefit the company. The officer can also teach others in the company how to use the software properly, which can help lower the learning curve, which we will touch on later.

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Adopting Content Analytics Software

Once again, a number of companies remain stuck in the past when it comes to getting an actual handle on their content analytics. They don’t hire personnel to fill the role of chief digital officer, and they don’t’ bother upgrading their content analytics software. The programs used a couple of years ago simply can’t handle the current load. Still, those companies do have some valid concerns. As with other new pieces of software, they worry that it might not be applicable to their needs, or that there will be a huge learning curve to using the program. Companies also don’t have content retention and governance plans in place, which can make using the new software pointless – they simply won’t get enough out of it.

Making the Change

What will it take for companies to finally make the change and upgrade to a new way of handling their data and content? Most likely, it will simply take time. As the data flow increases, businesses will get to the point where they finally realize they can’t handle it the way they did in the past. They will realize that they need to adopt a new tool for handling content analytics and for managing their data. New software that’s hitting the market now has the potential to help change businesses for the better. They simply need to be willing to get over the initial step and actually start using it despite the learning curve.

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Mike Miranda writes about enterprise software and covers products offered by software companies like rocket software about topics such as Terminal Emulation, Legacy Modernization, Enterprise Search, Big Data, Enterprise Mobility and more.

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