In the last blog post dealing with Google Analytics and Tableau, we identified random numbers while connecting to a Google Analytics data source from Tableau as a Sampling issue, and discussed a work around.
Let’s look at a couple of other interesting situations that might stump you while building your web analytics dashboard connecting directly to GA using Tableau’s Google Analytics API.
Scenario 1: You have pulled a month’s data for a few measures including Sessions, Pageviews etc. and they all reflect the right numbers, however Users / Unique Visitors numbers don’t appear correctly in your visualization.
The problem here is due to how the Tableau API pulls the data from GA in conjunction with the fact that while all the other measures like Sessions and Page Views are additive in nature, Users / Unique Visitors is not. Let’s take a simple scenario to understand this:
Assume I am the only user to have visited your site on every day of October 2014, once a day. If you pull data from GA in Tableau for the period Oct 1 2014 to Oct 31 2014, ideally you numbers for the month of October should be:
Visits: 31, Users: 1
However, if you have used the Date dimension, you are most likely to see:
Visits: 31, Users: 31
This is because pulling the Date dimension forces GA to export the values at a Date level i.e. How many Unique Visitors on Oct 1, Oct 2 and so on – when Tableau aggregates from a Date to a Month level, the 1 unique visitor shows up as 31 unique visitors in the month of October. Visits, on the other hand, is additive i.e. my visit on Oct 1 is exclusive from my visit on Oct 2 and so on, and aggregates correctly at a Month level.
The way to pull in the correct values at a Month level is to actually use the Month and Year dimension in the Tableau connector – this forces GA to find the no. of Unique Visitors across the whole month of October. You will now get the correct values.
Scenario 2: Now, what you might find is that in spite of fixing the time dimension, you might still be getting values that simply just, try as you might, just don’t add up! Infuriating isn’t it? To understand the problem here, look for extra dimensions that you have pulled in addition to the Month and Year dimension that are unused in your visualization.
For example, you might have pulled in Visitor in the data source because a 2nd visualization requires you to view your data split across New and Return visitors. GA will find Unique New Visitors and Unique Return Visitors for the month of October and add it to find the total Unique Visitors – clearly incorrect!
It really goes to show that when important (and expensive) marketing discussions are taken based on insights derived from your dashboard, a rigorous testing process is imperative to avoid common pitfalls of connecting to Google Analytics via the Tableau connector. Click here to acccess the 3rd part on the Google Analytics topic that will talk about Channels and modeling them in Tableau.
This blog is written by Farid Jalal, Analytics Project Manager at BRIDGEi2i
About BRIDGEi2i: BRIDGEi2i provides Business Analytics Solutions to enterprises globally, enabling them to achieve accelerated business impact harnessing the power of data. Our analytics services and technology solutions enable business managers to consume more meaningful information from big data, generate actionable insights from complex business problems and make data driven decisions across pan-enterprise processes to create sustainable business impact. To know more visit www.bridgei2i.com
The views and opinions expressed in this article are those of the author and do not necessarily reflect the official position or viewpoint of BRIDGEi2i.