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"Data analytics for content management systems" sounds like a topic that might come up during a lull at a cocktail party for diehard fans of the television show The Big Bang Theory.
In reality, CMS analytics can drive better business results and get the notice of the corporate movers and shakers, namely CEOs and the board of directors.
While many content executives have known web content and traffic analytics for many years, enterprise content analytics is now gaining traction for several reasons.
Data lakes have grown beyond our capacity to manually track them. Yet, for analytics to return usable insights, the larger the data set, the better. Therefore, it makes sense to deploy automation to learn what's in unstructured data pools in cloud-based and on-premises networks.
Computing power can now handle the job. Dashboarding analytics information took time, and retrospective views were all these systems could deliver. Now, with predictive analytics running on faster systems, richer real-time and forward-looking trends can be mined.
Organizations are looking to create efficiencies. Why reinvent the wheel and rewrite content, procedures or projects when they already exist?
Content analytics can help find and group ideas residing in discrete locales among your teams. They can offer decision support using cutting-edge technologies such as sentiment analysis, automated categorization and concept extraction. These tools can find trends among seemingly random sets of content that may never have been discoverable otherwise.
This handbook explores the potential for CMS analytics and strategies for implementing it. More importantly, it examines how to translate the benefits of these tools to the business leaders in your organization, so you can show the real-world possibilities to decision-makers who sign off on implementing these systems.