It’s undisputed that content is a core contributor to business success in today’s digital age. As organizations digitally transform to support the emerging needs of customers and prospects, they too are seeing its crucial to have content intelligence and analytics to look for ways to transform their enterprise content strategies. Managing enterprise content – from idea to creation to omnichannel publishing – is complex, but it doesn’t have to be. It’s both technology and your people’s skillset that, when combined, develop and execute a success strategy.
So, the questions are: how do you measure the success of your content strategy? Do you have confidence that content delivered is reaching and resonating with your audience? How do you know for sure without content intelligence?
This is the fifth and final instalment in a series of blogs that examine each stage of the enterprise content lifecycle. Let’s look at how to get your organization on a path to understanding how content is being consumed by your target audiences using content intelligence and analytics.
Traditional to Digital
Hard copy and print assets are still important forms of content; however, your business cannot track how this content is being consumed, if at all. Content production is a costly endeavor that involves many people across the organization – encompassing design and formatting requirements, printing and distribution methods, and multiple layers of people resources – and if you don’t have the right tools, it’s difficult to measure the ROI of this continuous content investment. However, creating content for multiple digital outputs gives your enterprise the power to accurately know if content published is achieving the desired result through content intelligence and real-time analytics.
For example, is a recently published standard operating procedure (SOP) being read by your target audience? Do you know what section of the SOP is particularly useful or most widely read? Adding metadata properties to content types and configuring automated AI workflows enables you to answer these questions and more. Organizations gain insight into specific consumption metrics as to how your audience engages with the content down to the component level. You can see what sections of the content are of most interest so you know what sections should be reused or repurposed elsewhere and understand when content has reached the end of its cycle and should be retired. It takes the guesswork out of what content is performing well and what content is of no value.
The People Experience
Content automation technologies are the key to not only content strategy success, but content team success. Let’s go back to the SOP use case. The content leader on the team is responsible for instigating, directing and executing hundreds of effective SOPs across different departments and locations. What’s more, additional members are involved in creating this asset, such as technical writers, designers, SMEs and even stakeholders outside of the content team such as regulatory agencies. Infusing content intelligence and analytics is critical to measuring the success of these assets. It’s the only way your content leader can get accurate, granular detail on exactly what content is being consumed most often and can capture all these statistics for easy reporting to business stakeholders. The content leader can show tangible ROI of a content asset investment and learn new narratives to share with the board every day.
The power to analyze enterprise content performance helps you understand if your content strategy is supporting your business objectives and empowers your content team ability to make smart decisions as to when to reuse or retire content.
Ultimately, content intelligence allows your content teams to adjust your organizations’ content creation strategy appropriately and discover new ways to improve the content experience, the digital experience and most importantly, the customer experience.
Learn more about Quark Publishing Platform (QPP) NextGen.
Read Quark’s Top Tips for Next Generation Enterprise Content Lifecycle Management.