My second of two posts this week on using web analytics (read the first one here) comes by way of a recommendation from Mark Briggs. He told me about this “total brainiac engagement person” at Belo, the company that owns the TV station Mark now works for.
So I called Belinda Baldwin, the director of audience development for Belo. Belinda’s goal is to take the metric reports that her department creates for all Belo owned and operated TV stations, and make it understandable for newsrooms. Not just understandable, but meaningful and actionable.
She created a dashboard — using the green, yellow and red of stoplights — that puts the metrics in English according to four categories: growth, engagement, evangelism and loyalty.
I had to sign an NDA to take a look at the formula, but i can tell you this much about how the dashboard works:
— Growth, as you might expect, tracks things like the number of registered users and unique visitors.
— Engagement involves how long people stick around on the site, and how much they do while they’re there.
— Evangelism is about how often content is shared.
— Loyalty is about social media following and how often people come back to the site.
The visualizations are built on a 12-month average, to get beyond anomalies such as spikes for big news.
Belinda wrote in an email that a “share” of any kind is the great complement a user can give, and that the action converts the user to an evangelist. For now, the evangelism metric is based on email shares per unique visitor. When the company figures out how to get the data for the websites’ social media sharing options, those figures be incorporated as well.
One of Belinda’s hopes is that the dashboard can lend some perspective to the chaos around analytics. If a newsroom gets all excited because of a high growth month, for example, it might be because of a big news event that draws new readers. If that happens, the engagement metrics will be down, because users are coming for one story and leaving.
Abandoning the focus on the page view is a consistent theme among the smart people trying to educate journalists about analytics. If we’re smarter about how we use the data, we can take advantage of the opportunity we have to actually understand how users find our content, what they’re responding to, whether they’re sharing it and what they want that we’re not giving them.
Journalists have spent a lot of years wondering how their content gets processed, and whether it gets read. So now that we know, why aren’t we doing more with the information?
If you know of other companies or individual journalists making intense use of their analytics, please let me know.
This was originally posted on the blog of the Reynolds Journalism Institute, where I am a 2010-2011 fellow.
Joy Mayer 