Day of Week Analysis with Google Analytics + More Date Dimensions

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Have a Date with Google Analytics

I'm really excited to announce the third update to Dimensionator, the first compoment of our Analytics Toolbar platform. As promised in previous Dimensionator updates, we've been working to add access to more unlisted and normally inaccessible dimensions. This latest update makes some of my favorite secret dimensions accessible anywhere in Google Analytics: day of week, hour of the day, date and five more date/time dimensions. If you aren't already using Dimensionator, day of week is a must-have reason to add the bookmarklet now!

Get Dimensionator now: click here!

About these Date and Time Dimensions

New unlisted Google Analytics Dimensions made available with DimensionatorThese dimensions aren't new to Google Analytics - they've been there for some time (I don't know exactly how long, though). The Dimensions of Hour, Day, Week, and Month have been accessible via Advanced Segments, Custom Reports and the Data Export API. However, Day of Week is a Dimension I haven't seen listed in any of these places - yet I've discovered it's there and fully usable. Additionally, the Dimensions in Custom Reports use formatted date values.


Using Day of the Month

What if you want to analyze performance based on day of the month rather than Day (as in Monday, March 1st, 2010). This could come in handy when you want to know how your site is impacted by pay periods. Using Day of the Month you can see how Conversion Rate changes on the 1st and 15th day of the month over an entire year's worth of data.

What Day of the Week is it anyway?

This Dimension is truly one of the most useful Dimesions out there. The fact that it's not listed by default is frankly a big blunder on Google's part, in my opinion. Other Web Analytics vendors provide this - but not Google Analytics? Well, yes, it does, it's just a secret - until now! Sure, you could always use the Date Comparison feature to compare two days of the week against eachother, but identifying true Day of Week cyclicality over any wider range of time is basically impossible with that method, unless you're a presently unemployed Google Analytics specialist and have the hours it will take to perform Day of Week analysis that way.

A fun example of Day of Week and Hour of Day analysis is to create a Pivot Table report in Google Analytics and export the data to Excel. Then, use Excel 2007's nifty coloring tool to create a heatmap of traffic and value by day of week and hour of day. The following image illustrates just this - two heatmaps: one for visits by day of the week and hour of the day (left), and the other using the Per-Visit Goal Value metric, showing when highest goal values occur rather than traffic volumes (right).


Another spin on this is to create a table that combines the value and traffic metrics (I use a simple calculation here of vists * per-visit value). The useful part about this is that it accounts for the importance of volume as well as value. Who case if you can get 5x the average Goal Value if there are only 2 visits to be had at that value? As this report shows, there is a pattern (forgive the home-made annotations!). I've applied both the coloring filter as well as an icon set that makes the obvious winners jump out and say "hi!"


Having fun with Date, Day, Week, Month, Week of the Year and more

The full list of Date and Time dimensions included in this update are:

  • Day of Week
  • Hour of Day
  • Day (formatted date)
  • Week (formatted date)
  • Month (formatted date)
  • Day of the Month
  • Week of the Year
  • Month of the Year

Lastly, A Cosmetic Update to Dimensionator

You'll notice as of today that Dimensionator now has nice "group" delineation between types of Dimensions. As we've added to the list I've found it harder to spot a desired dimension when they're all bunched together! So, this is an attempt to resolve that. Enjoy!

As always, we love feedback! Comments below, questions, consulting requests and anonymous checks for large sums are always welcome.

-Caleb and the Analytics Pros team