Today Google officially launched the real-time widgets for use on the Google Analytics dashboards. Awesome feature that can make real-time analytics a bit more useful than it was before. These are the new widgets (the second row) you can use to visualize real-time stuff:
The great news is: you are able to put filters on these widgets... really awesome. Google has a more extensive description about all new possibilities, but here's an example I would use these features for.
Google launched a new feature in their ecommerce module that helps international sites in tracking their worldwide revenues. Until now every single site that worked with multiple currencies had to implement some sort of curreny-converter script to get all revenues in the same currency. This is a very time consuming and expensive action that needs constant attention. As of today this is all history.
Google implemented a new feature that can convert the local currency to the currency you specified in your profile settings:
Just a small update from here (haven't been blogging for a while). If you're looking at the Windows 8 stats in your Google Analytics account you will see this graph:
Last October I tweeted that Google Analytics was reporting "Windows 8" as "Windows NT". I like to think they read my tweet and changed this on December 11th 😉 Since the launch of Windows 8 on October 25th you see traffic for "Windows NT" suddenly rising until they changed it to "Windows 8".
For a while I wanted to write this post about the Google Analytics sampling. You know, the dreaded message that appears on top of your reports:
This message shows up when you work with a dataset that contains more than 500.000 visits or more than 1.000.000 items (keywords/url's/etc). Above that Google takes a sample of all those visits to calculate the numbers for your reports. But what is acceptable? In this example Google uses 30.62% of all visits to guess what the other 70% did on my site...
I'm pretty sure a lot of you have dealt with this issue in the past. Someone puts a link on a specific page and after a while they ask you how many clicks it got. But in the main menu and footer are links to the same page also... Google Analytics can only report on how many people went from page A to B, but not which specific link they used.
Take a look at this blogpost:
Last October Google added a cool feature to their Analytics suite called Goal Flows. That feature is really amazing and helped my find a lot of 'problems' in several sites. Back in the old days we had the old funnel that looked like this:
It was a very helpful funnel that provided some insights in the way people went through an ordering process. But there were also some huge problems with this funnel:
Since the start of the new Google Analytics version (V5) we're unable to export more than 500 rows to for instance Excel. I figured there must be a solution to raise that number to 10.000 or more, so I started coding.
In the old Google Analytics there was the "&limit=10000" parameter that you could add to the export URL. In the new interface you can select the amount of rows below the table:
And after everything is loaded you can export those 500 with the usual export button.
With the new release of ga.js this is possible. In the old days a fired event immediately after a trackPageview would cause Google Analytics to report a 0% bouncerate for that visit. But sometimes you don't want that behavior because the event is not always triggered by the visitor.
For instance: I track page load times the same way Google Analytics does, but in an unsampled way (Google only meausures 10%). To do that I fire an event immediately after the trackPageview, but I do that in another profile with a different UA-XXXX-Y number so it won't affect my bouncerates. But now we have an extra parameter:
_trackEvent(category, action, opt_label, opt_value, opt_noninteraction)
If you set this opt_noninteraction (boolean) to true it wil not affect bouncerates!!! That makes it possible to:
A while ago I wrote an article about a method to track page load times in Google Analytics. Short after this article Google came with their own technique to track page load times, but both methods have some disadvantages.
To give a clear understanding about the differences I want to show you this image:
A small blogpost about a new version of the ga.js file that was launched a week ago. As you can see they changed the way customvars are being reported:
"Fixed a bug in Custom Variables that caused some values to be encoded in reports."
Spaces (and other characters) were reported as "%20". So if my name was in a customvar it would look like this: