Going beyond metrics of page views and visitors


This is Part 1 on going deeper in Analytics.

Publishers of digital news sites have a chance to know their audience far better than their print counterparts ever could.

The data available in tools such as Google Analytics lets you see when people are using your site, where they live and how loyal they are. 
Let’s start with the dashboard page. 
Click to see a larger image.
To the upper left, a click on “Visitors”, “Traffic Sources” or “Content” will give you a more detailed profile of your users. To the bottom, the same is true with the six measurements that are visible.
If you click on “Visits”, you can compare the traffic on particular days of the week to see if your users have a preference. 
(Click to see a larger image.)
Tuesday July 26 was a big day for traffic; maybe there was a big story published that day. No other pattern seems to emerge. 
The publisher at the site above should analyze his content to see what was so popular on July 26. 
Within Analytics you can see the pattern for the entire month, or whatever period you choose. One of the participants in a recent session was able to see that Mondays were the big day for traffic on his site.

Possible responses? He could look at the popular content on Mondays and produce some of it on other days of the week to keep traffic steady. Or maybe he should follow his users’ lead and produce more content for the Monday audience. 

(Click to see a larger image.) Traffic starts rising at 6 a.m.

While you are within the “Visits” section, you can change the view from days of the week to hours of the day with the buttons at the upper right. Then you can see the pattern of use by hour for the entire month. 

By looking at the entire day, you can make editorial decisions about staffing levels or deadlines. For example, at El País in Spain, site traffic starts rising rapidly at 9 a.m., so the editorial department starts work several hours earlier to produce fresh content for this audience. A second peak in traffic occurs in late afternoon, so fresh stories and updates are ready for this audience.

Let the data help you decide when to publish and when to update stories during the day.