Visual Revenue, a New York City-based outfit, is rolling out a predictive analytics model intended to help websites maximize the viewing of their content. It analyzes the readership of your web pages by location (top/bottom, left/right, etc.) The dashboard suggests when a story is underperforming for its position, with a further suggestion of where to move it for better exposure. It doesn’t track just views, but also click-throughs.
It does NOT benchmark your performance against the entire web, just the previous 14 days on your website. So you’re analyzing your content against earlier content, which is likely much more valid than comparing your site to perhaps a much larger content outfit that is not really comparable to your content or mission. It seems to take Google in-page analytics one or more steps forward.
Here at RJI, Fellow Paul Bolls is taking a different tack at designing web content to improve readership, click-throughs – engagement. Instead of tracking views and clicks he’s researching how the brain processes news and advertising content with the goal of designing news and advertising that maximizes how the brain processes that news and advertising. If we can learn to tap into those brain processes to further engage the reader, we’ll have roadmaps to create stronger engagement and loyalty among readers
One doesn’t cancel out the other. Creating and delivering content in ways that drive motivation within the brain processes to engage with that content … then following it with analytics that provide an additional roadmap for placement … that sounds like a pretty powerful combination.
Stay tuned to the RJI Blog for further developments. We’ll update you with Bolls’ research as his Fellowship continues.
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