The Importance of Clean and Meaningful Google Analytics data

Ever since returning from Superweek in beautiful Galyateto, Hungary, I’ve been thinking a lot about data and the utility of Google Analytics as a tool.  Yes, I know, I spend a lot of time thinking about those things, but the conference was particularly inspiring in those regards.  Google Analytics is not different than any other digital analytics tool insomuch as it is critical to understand what the values that get reported actually mean and how they get there in the first place.  But that’s not enough.  When we analyze data, we need it to be presented in a meaningful way.  Data visualization is tremendously important in this regards, and I believe that one of the reasons why Google Analytics has such great adoption and market penetration (besides the enticing $0.00 entry price point) is because the UI is crisp, FAST, and easy to use.

One catalyst for this post is a response to this post entitled “Are You Being Misled by Google Analytics?”  While I am about to critique the post, I do want to point out that one of the ideas that Tien Nguyen has (who Chris mentions in his article as the source of this idea)  is indeed insightful.  Namely, that without configuration Google Analytics may not provide as much visibility into traffic sources that one needs.   While I urge you to take a look at the article, I’ll briefly summarize the main idea here. Continue reading The Importance of Clean and Meaningful Google Analytics data

How “Unique” are Unique Visitors in Google Analytics

“Unique” Visitors 25%-39% inflated

I’ve been working on implementations with a number of clients who have a need for visitor level tracking in Google Analytics so that they can start using GA to measure things like customer loyalty and (try to) calculate Lifetime Customer Value. I understand that there are a number of data models available to approach these sorts of questions, and that either Custom Variables or Events can be used (using either visitor level vars, or session level vars populated from server-side values).

In general, I like pushing the _utma cookie value back into Google Analytics, as it uncovers every single visit in the API. There are lots of benefits to doing this. Justin Cutroni wrote a nice post about merging GA data with a data warehouse. This is just one (powerful) thing that can be done using this method.   Google Analytics UTMA Cookie What interests me in this post is “how unique are ‘unique’ visitors?” We all know that a unique visitor is nothing more than the value of the _utma cookie’s unique ID. I don’t know about you, but I certainly access websites from multiple browsers from multiple computers. I don’t find it unreasonable for a “person” to indeed have 6 or 7 unique “visitor” values. Start adding in users who clear their cookies and/or Private Browsing and the meaning of “uniques” really begins to degrade.

Luckily, I have access to data where, in addition to capturing _utma values, we’re also capturing obfuscated member ID values. These values are set as a custom variable upon login. This means that a user will maintain their ID whether or not they switch browsers or clear cookies. Here are some of the numbers that I pulled.
Unique Visitors vs Actually Unique Visitors

Number of Unique Members is 61% of "Unique Visitors"

The data set that is decently large and no data sampling has been applied to these numbers. At first glance, it appears that the number of unique logins is 61% of the number of GA’s unique visitors. Two things that stuck out at me were the number of visits in a 28 day period by some of the most active users. The top ten most active users average 11.68 visits per day. Also, line 7 had a large ratio of unique visitors to visits. Was this one user who cleared cookies often? Was this shared login information?

In order to make sure that this made sense among users who visited the site less often, I filtered by logins that had less than 3 visits per day, 2 visits per day, and visits once every 2 days. The numbers were pretty consistent for members who came 3 times a day or less, though users who visited once every 2 days or less saw a higher percentage of unique visitors to login IDs.          

The Bottom Line:
The “unique visitor” metric was never meant to describe the number of “unique people” that visited a site. Admittedly, this terminology can be confusing for the average person. While web analysts have known that ‘unique visitors’ refers to a count of unique cookie values in the browser, I find it quite nice to be able to quantify this in numbers.  Indeed, from the data above, it appears that the number of unique visitors reported is somewhere between 25% – 39% greater than the number of people who visit a site. If you have any additional data, please feel free to share below.  

Analytics for Eye Doctors

I recently started working on PPC and Analytics for a new launched website.  In this case, it is an Optometrist in Lincoln, NE.  I’m particularly interested in knowing if anyone has any bounce rate benchmark information for medical practice sites.  Please comment below if yes.  It seems to me that many private practices could greatly benefit from a knowledge Analytics expert.  I’ll keep everyone in the loop as to how this newly launched site is panning out.  I’ll even probably share some groovy charts.

Conversion Funnel Analysis – Abandonment Rate by Time of Day

One report that I find extremely useful in the Goals Section is the Conversion Rate Report.  In a moment, I’ll explain how a quick export of data from the Conversion Rate Report can provide valuable insight into one’s abandonment rate.  But first, a quick intro into conversion rates, abandonment rates, and conversion funnels.  In general, I assume that my readership is relatively erudite in Google Analytics.  So if this next paragraph is below your level of expertise, feel free to skip ahead.  That said, I believe it is worthwhile for all us out there who are trying to be successful on the Internet to get back to the basics and remember the fundamentals.

Fundamental #1 –>  It’s all about conversions.

Really.  It is.  Especially when it comes to e-commerce.  There are soooo many people about there who are still interested in how many people come to their site.  But if they aren’t taking the desired action(s) that you would want them to, then most likely you’re wasting time and money.

Take a step back.  Take a deep breath.  And say to yourself, “what do I want people to do when they come to my website.”  The answer(s) should be easy.  Lead generation?  (Filling out a form).  Signing up for an email list?  Online purchase?

Once you define your goal and properly configure it in the settings section, you’re ready for the next step.

goal setup

But before we get there….

Fundamental #2 –>  Lowering Abandonment Rate is the best way to increase conversions.

Continue reading Conversion Funnel Analysis – Abandonment Rate by Time of Day