A major impediment marketers face is the ability to access, analyze, and incorporate content consumption and usage data into a viable, optimized, customer-centric content strategy. Below, we’ve highlighted three of the biggest challenges and how organizations can successfully integrate data into their content strategies.
Challenge 1: Communication
The sheer amount of data, analytics, and platforms at marketers’ disposal can be overwhelming, which is why it is essential to start with a clearly defined goal: What are you trying to achieve with this data? Without a goal in mind, no one—marketing or IT—will be able to separate the wheat from the chaff.
Having a clear goal is crucial because often times your initial request is turned down because of infrastructure hurdles—“we don’t have stats for that”—or the response is met with a series of unintelligible dashboards. If your goal is clear, you can problem solve what other metrics will help build your case.
If knowing what to look for is step 1, than knowing where to look is step 1A. Unfortunately, the information you need to make your content strategy dynamic and data-based is often siloed in different departments, databases, and applications.
As Charlotte Ziems, VP of content marketing and editor in chief at Sitecore, writes, “We have data by the bucketful. But when it lives in separate applications or doesn’t add up to give a complete picture, it’s about as useful as comparing apples to oranges to pears.”
With a clear goal in mind, you will be better prepared to communicate your data needs to the various players in the IT siloes to get the right information for apples-to-apples comparisons.
Challenge 2: Translation
The enthusiasm for data and the investments in business intelligence and analytics software have primarily focused on technologies that make taming data possible. Technology alone, though, is not enough. As this Harvard Business Review article about the rise of data scientists states, just “as important are the people with the skill set to put that data to good use.” Once you have the data, you need people who can manage it and find insights in it; people who understand the difference between what is useful and what is noise.
To recognize that difference, your analytics team needs to have an understanding of the subject matter and audience as well as the statistical standards. Web traffic stats are notoriously easy to misinterpret in the absence of subject matter expertise. Is a high bounce rate bad? Maybe. Or it might mean that the page succeeded in completely answering all of your visitor’s questions. Are you happy to see an increase in average page views? You wouldn’t be if you learned that your frustrated visitors had to visit 10 pages because they couldn’t easily find what they needed.
Translating data into insights requires subject matter expertise, an understanding of the goal at hand, and data fluency, but just as important is curiosity: A desire to go beneath the surface, combine disparate data sets, and distill them into a set of hypotheses that can be tested. This activity is not the province of one person, but is better accomplished with collaboration from different teams and arenas of expertise.
Challenge 3: Application
The value of data is how it is applied. The analytics alone won’t yield business value. The real value is the diagnosis and the action it produces.
Where many data-driven content strategy recommendations fail is in the way they are expressed to management. The analysis can be iron clad and the recommendations solid, but the chances of your strategy succeeding often depend on the ability to recognize and account for organizational constraints—budget, technology, politics, and so on. Changing minds requires evidence, no doubt, but it also requires an understanding of the obstacles you’re likely to encounter and a plan for working around them.
A constraint-driven plan will succeed if it acknowledges each stakeholder’s ownership of their part of the process and what they need to succeed in their role. What level of requirements detail does the tech team need to build a new publishing interface? Who needs to weigh in on a new taxonomy? If the plan ties each stage together in a practical way, each team can add incremental value that can be put to further use downstream rather than creating more silos.
The last word
All responsible marketers should use data to determine if an initiative makes sense. Understanding the challenges of integrating data into your content strategy is a critical first step in delivering engaging, contextual, customer-focused content experiences.