Media Metrics

Chartbeat is a company that analyzes web statistics to help content generators maximize revenue. Its CEO, Tony Haile, wrote an article explaining how some of the standard metrics used by most companies don't convey anything at all.

Conventional wisdom says the number of times a page is visited indicates popularity. This is wrong, says Haile, since on the web we go “click, click, click”. It is a myth that “we read what we’ve clicked on” when in reality, “a stunning 55% spent fewer than 15 seconds actively on a page”!

The next myth that Haile dispels is the value ad companies pay to sharing articles via Facebook or Twitter. This actually sounds logical: when someone shares an article, the feeling is that he “has not only read the content but is actively recommending it to other people”. Except it turns out that “there were only one tweet and eight Facebook likes for every 100 visitors”. Worse, “there is no relationship whatsoever between the amount a piece of content is shared and the amount of attention an average reader will give that content”.

This point is easy to believe. Can anyone deny what Jeswin says about Facebook?
“Facebook is godsent for people who love to talk, but have nothing to say.”
and
“Share more, get noticed more. Originality be damned.”
And since more and more of us notice this trend on Facebook, we tend to ignore most shared articles altogether!

Ok then, what can websites do to assess their “true” quality? Jeff Jarvis has these suggestions:
- Follow the Medium approach of valuing “total time spent reading” instead of pageviews.
- But be warned: attention, as defined in the previous point, can be misused, the way Yahoo! did by “trying to bombard you with content and keep you around as long as possible to show you as many ads as possible”.
- Try the Cir.ca approach of using the “follows” metric: “When a reader follows a story, she is telling Cir.ca, “Please bother me and let me know when something new happens here.”
- Or try the Flipboard approach of tracking what people save to read later.
- Google's approach to valuing links makes sense too: if your site is getting a lot of links/references, you must be doing something right.
- Track the times your content is embedded in other sites: if they add you to their content, they must value your content, right?

Ultimately, data mining is like statistics: measuring is the easy part; finding the right thing to measure is the hard part.

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