What makes a great article? Now that is a tricky question – and one that only someone in your position, with years of experience, expertise and carefully honed instinct can hope to answer. But what makes a POPULAR article? That one we can help you with.
In the past, these two questions – and the departments that ask them – were often bitter rivals. Content creators simply didn’t take an interest in what made an article a commercial success, or use the tools available to figure out the answers – that was for sales and marketing to think about. Now, though, these two sides are starting to realize that working together is a smart move for both of them.
While there’s no surefire way to know if something will go viral, the ingredients common to your top rated content are no longer a mystery to you. Quite the opposite: leaps and bounds in data analytics, machine learning and automated content distribution technology all combine to make it more possible than ever to spot trends and patterns in high-performing (and low-performing) content.
The Rise of Editorial Analytics
You may have noticed a recent profusion of job titles in the publishing industry that never existed before. Titles like “audience engagement editor”, “audience development editor” or “growth editor”.
On one side, these types of roles are all about the numbers: how many page views a piece of content gets, how many interactions and shares a post gets, how much time users spend reading, and how many articles they read per visit and so on.
There are a whole bunch of new tools out there to make this analysis easier, too. For example, many provide oversight of your entire social media presence, allowing you to see where your content is making waves and where it’s getting the most genuine engagement.
The Big Shift
In the past, an editor might have been solely concerned with the impact that a particular subject matter or angle has on engagement. Today, the realities of dealing with a multi-device, globally scattered audience, all of whom are interacting with your content through different channels, in different contexts or times of day, means that a vast range of other factors are also at play here, too.
Only now it is possible to translate performance into measures that are meaningful to journalists and editors, moving away from the dominance of page views, and towards newer integrated metrics of engagement that take into account things like time spent, recirculation, volume of articles read per visit, and number of comments.
These are the things that show how well you’re doing, how many people you’re reaching and how enthusiastically they engage with your content – and that, ultimately, impacts your bottom line. In other words, they are the issues you must address in order to survive and thrive.
How to Use These Insights
In the past, this kind of analysis was relegated strictly to sales and marketing departments – and using stats and clickthrough rates to inform editorial policy still seems, to many traditionalists, at odds with running a reputable news source.
This represents a massive missed opportunity, because it misses the true value of editorial analytics.
After all, this isn’t about looking at some derivative stats on media trends and concluding that your foreign policy magazine should close up shop to make cat videos instead (or, for that matter, that your cat video channel should start talking foreign policy!). It’s about figuring out what works best within your niche, identifying totally unnecessary turn-offs in the presentation and delivery of your content. The changeable things that act as barriers to getting your best work in front of the people who will value it the most.
Instead of fighting internally over how to measure the value of your content, this brings two superpowers together for a joint cause. The publishing industry is changing fast and, increasingly, you need to be able to adapt fast to evolving pressures as efficiently as possible: editorial analysis genuinely empowers you to answer the tricky questions. It points out where and how to fix the fixable, improving your ability to package and deliver excellent editorial content so that it will actually get read.
This should never be a tug-of-war between quick sales wins and content you can be proud of. If you’re doing editorial analytics right, these two priorities will pull you in the same direction. The results are improved quality of output, better engagement with your audience, and a healthier, more sustainable business that reaps maximum benefit from ad partnerships in the long term, too.
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