10 Ways the New Google Analytics Gets It Right

I have been very skeptical of the new Google Analytics interface.  Why?  Not sure.  Maybe I just don't like change, especially when it effects tools that I use everyday and rely on for my prosperity.  From first glance, you can tell there are some big changes in store.  This was not an update.  This was an overhaul in many ways.  And after using it now for a few weeks, I can say that I think it's a good move but seems only partially implemented.
I'd planned on doing screen shots and making a full instructive blog post, but frankly, I don't have the time.  So here is my condensed list of things I like in the new GA so far.  These are in no particular order.

Getting It Right #1: No All Visits Required
This is a huge improvement in data visualization and something I never understood.  Comparing everything to the All Visits segment crushes the scale and you lose the details in lower volume trends.  Freeing us from the shackles of scaling everything at the maximum is wonderful.

Getting it Right #2: Comparing Individual Keyword Trends
If you go to the Organic Search report, you might notice that things have changed.  The list of keywords have a check box next to them and at the bottom of the keyword table here is a button that says "Plot Rows".  Now, you can only plot 2 rows, but it's a start.  This continues with the awakening that Google Analytics seems to be having that comparing trends is central to what web analysts do.  And the more trends we can compare, the happier we are. 

Getting it Right #3: Persistent Report View when Switching Profiles
This a huge time saver. In the past, when you wanted to look at the same information in different profiles, you either had to have two windows running or do a lot of navigating.  Now, using the profile list in the upper right, you can basically swap back and forth
 between profiles in the same report.  Thank you Google, for this one.

Getting it Right #4: Understanding Importance of Segmentation
Moving the Advanced Segments from a right side little selector thing to a top of page, big obvious drop-down makes a statement.  Segmentation is important.  We've known that for a long time, and now the UI is knowing it to.

Getting it Right #5: Differentiating Reporting Styles
There are 3 styles of reports in the new GA.  Dashboards, Standard Reports, and Custom Reports.  In the old GA, Dashboard was the first report.  The standard reports were basically drill downs from the dashboard.  Custom reports were this little hidden text link below the main left nav.  Now they are all top of page, side by side, and big as day.  The UI and the functionality is completely separated for them.  Standard reports are not just the drill down from the dashboard.  And the Dashboard is no longer just a smorgasbord of snippets from the body of reports.  They are each distinctly different.  This individuation of the reporting styles is a bold move by Google.  Analysts will learn to love it.  There is a lot going on here philosophically in terms of the purpose and presentation of data. 

Getting it Right #6: No Auto Loads
Thank you. I no longer have to sit through the  loading of the Traffic Sources Overview report, when what I really want is the Organic Keyword report.

Getting it Right #7:  Event Goals
Why this was never included from the beginning is a mystery to me.  This update has a lot of impacts and really ups the ante on implementation choices between virtual page views and event tags.

Getting it Right #8:  Multiple Dashboards
I'm calling this one out separately from item #5 above because it is important and is one of the strongest indicators that Google has evolved their concept of the "dashboard". Unfortunately the implementation is incomplete, but this is certainly a strong move into new thinking about data presentation.

Getting it Right #9:  Custom Report Flat Tables
If you go into the custom reports and create a report, you will see an option that was never available before--one little drop down list with an option to create an "explorer" style report or a "flat table" report.  Thank you, Google.  Thank you for recognizing that we export a lot of the data out of your reporting interface and having flat tables makes things much easier.  I don't love the new report designer interface, but I can learn it.  Having new options for creating reports that are designed to be exported is well worth it.

Getting it Right #10:  Easy Access to Settings from Reports
That little cog button just to the right is well done.  Another time saver.  Thanks.

There may be many more things about the new GA interface that is worth pointing out and I just have not discovered yet.  But these are a start. 

How the New Interface Fails
It's not all peaches with the new Google Analytics. In the next post we'll look at all the problems in the new GA.  Some of these problems are really critical issues that, frankly, are keeping me from moving 100% over to the new interface for all my reporting needs.  More on that soon...

Measuring Social Media's Value -- A Simple Twitter Test

The value of social media seems to be a huge question.  Some people are evangelists.  Some people are skeptics. Some are on the fence.  Some are "gurus".  Some are full of [poo poo]. 

The reach of social media seems to be the best part of its promise.  If you tweet something and 50 people see it and some retweet it and 50 people of theirs see it, and some of them retweet it, etc. etc., you could get your message out to thousands of potential customers!  It's so efficient that its almost like a dream come true.

But the truth is that it seldom works out that way.  In fact it seems like there are reports or metrics showing up all the time that dispell the social media nirvanna so many marketers were hoping for.

I got to thinking about this, and one aspect of social that doesn't seem to come up often in articles I read or reports is the time aspect of social.  You can tweet something and all of your followers will get that message.  But they will only get it for so long.  And if they are not online when it is sent, they will not get it at all.  This really really limits the impact of social media in ways that I don't see anyone accounting for. 

A Little Test 
I am not the most prolific twiiter user by any means.  For the purposes of this test, I wanted to see how long i would be exposed to my own tweet.  This is primarily determined by the number of people I follow.  The more I follow, the more incoming tweets I'm going to recieve, the more quickly things will slide off my screen.

I follow 50 people on twitter.  This is apparently not uncommon, although I could not find any definate stats on what the average number of following was. 

Here are a couple things I found:

June 2009:   92.4% of Twitter users follow less than 100 people
http://www.sysomos.com/insidetwitter/

March 2010:  An active or “True” Twitter user has at least 10 followers, follows at least 10 people and had tweeted at least 10 times. By that definition though, only 21% of Twitter users are active users.
http://mashable.com/2010/03/10/twitter-follow-stats/

Average = 398 following
slide 15
http://www.slideshare.net/eefsafe/twitalyzer-the-average-twitter-user

So, I am going to guess that I am around average for the number of people that I follow on Twitter.  Given that, here is what I found:

I sent out a tweet today at 3:55pm.  It took 1 hour and 3 minutes for it to reach the bottom of my screen.  Now, if I have 50 followers and they are all about average like me, then my tweet has a maximum potential of 50 hours of exposure. 

This seems pretty good.  However, this is a bit disingenuous becuase these are simultaneous hours.  At the time my tweet hit the network:

1. Not everyone is listening.  Take some percentage right off the top.
2. Some of these people will be following many more people than I do.  They will have less than one hour to experience my wonderful tweet.
3. Some days and times of days are more active for twitter than others.

The concept of simultaneous hours is pretty important and really puts the kabosh on the notion of the value of a tweet. 

"Time to Conversion" -- A New Social Metric?
One interesting metric to come up with would be "time to conversion".  You could optimize for this by calculating how much time exposure you need in the social space before someone actually buys something from you. 

Using "time to conversion" you could figure out:

• How many tweets to send
• When to send tweets to get maximum exposure time

For example, say you did some math and figured out you need two thousand hours of twitter time to get one sale.  Then you could baseline it and test against it.  Requiring less and less "time to conversion" would represent good optimizaiton, increased social value, and real  marketing savings.

Also, if you figure in the labor costs of coming up with however many tweets are required for 2000 hours of twitter time and put that against the value of a sale, then you have the makings for a real ROI from social media.

"Time to conversion" might be a strange way to see the value of a tweet, but I bet with some further thinking it could be valuable.