Analytics technologies lend enterprise content management a hand

Editor's note

As enterprise content proliferates and generates new formats, having the right information at the right time is becoming increasingly critical to businesses' competitive edge. Companies are turning to analytics technologies not only to reduce the risks of retaining large amounts of information but also to derive additional business value from the data.

Culling data and taking a more careful approach to the creation of content can take a slice out of the problem, but analytics technologies and practices are becoming more important in understanding enterprise content in a way that can increase productivity, enhance customer relationships, boost sales and even generate new product ideas.

As enterprise employees search through large volumes of content to find the information they need to do their jobs, customers outside company walls expect a new level of content accessibility and engagement. Now, social media data has added to the complexity, prompting organizations to wonder how much they should invest in monitoring and analyzing the unstructured data on social media platforms.

Through methods like text mining and sentiment analysis, companies can monitor the unstructured data from social platforms. But these formats pose new challenges in terms of how to parse the data and find meaning. Social conversations are full of slang and nuance that straightforward monitoring and analysis may miss, making the data less valuable.

In general, analyzing data in an accurate, meaningful way isn't easy -- and not every enterprise can afford to hire a data scientist. Fortunately, emerging tools may begin to level the playing field by making data analytics simple enough for business users.

Below, check out our Essential Guide on issues related to using analytics for enterprise content management.