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.
Trends in ECM analytics
Analytics tools can provide insight into the way people generate and use content, allowing businesses to improve content accessibility for employees and external parties. Even records managers may benefit from using analytics to keep an eye on governance-related issues like keeping too many documents and for too long.
In addition to enterprise content analytics and Web content analytics, enterprises are also concerned with the complex task of analyzing social media data. The unstructured nature of this data and the richness of language and sentiment on social media platforms make meaningful social media monitoring and analytics tough but valuable.
By applying business intelligence and business analytics practices to enterprise information, content analytics can track the ways workers access and use content, make content more easily accessible and improve business decisions. Continue Reading
Companies need to look beyond basic data such as page views and measure the engagement of their audience. Continue Reading
To prevent loss of business due to social media diatribes, companies are looking to revamp their customers' experience with analytics initiatives. Continue Reading
SharePoint 2013 now provides analytics capabilities that can improve content management and boost business intelligence by providing insight into user trends both internally and externally. But despite the new features, the challenge for enterprises still lies in correctly analyzing and using the data.
Organizations are questioning whether SharePoint -- which has historically not supported complex analytics -- now wields the power to provide meaningful insights on big data. Continue Reading
Videos related to enterprise content analytics
Check out SearchContentManagement's video interviews with experts on using analytics to improve information management.
With the analysis of unstructured data from social media platforms becoming more important to enterprises, an expert weighs in on when it is appropriate to clean up the raw information.
Information management is becoming the competitive edge for businesses. An expert outlines the shift in how companies can use their information intelligently.
Important terms related to analytics and ECM
Check out the definitions below to learn more about commonly used terms related to analytics technologies and ECM and the distinctions among them.