For power users of Google Analytics, there is a heavy dose of spreadsheet work that accompanies any decent analysis. But even with Excel in tow, it’s often difficult to get the data just right without resorting to formula hacks and manual table formatting. This is where the Google Analytics API and R can come very much in handy.
A few months back, Justin Cutroni posted on his blog some jQuery code that modifies how Google Analytics tracks content. Specifically, the code snippet changes how bounce rate and time on site are calculated, creates a custom variable to classify whether visitors are “Readers” vs. “Scanners” and adds some Google Analytics events to track how far down the page visitors are reading.
Given that this blog is fairly technical and specific in nature, I was interested in seeing how the standard Google Analytics metrics would change if I implemented this code and how my changes compared to Justin’s. I’ve always suspected my bounce rate in the 80-90% range didn’t really represent whether people were finding value in my content. The results were quite surprising to say the least!
If you’ve spent any time working in digital marketing or analytics, you’re already familiar with the power of A/B testing. A/B testing (and it’s more complicated brother multivariate testing) allows site owners to find out optimal combinations of site design and content for their visitors without having to directly ask/inconvenience the user. All it takes to improve a website is forming a hypothesis of something that could work better, creating multiple versions of a page (or other content), setting up the experiment…and the money flows in faster than you can count it. At least, that’s the hope!
At the enterprise level, there are plenty of testing tools such as Omniture Test & Target, SiteSpect, WebTrends Optimize, and Monetate, but these tools are cost-prohibitive to all but the largest websites. Google provides Google Website Optimizer (for free!), but that has often been viewed as difficult to manage, especially for dynamically created websites. That’s where Optimizely comes in.
Sample Certification Question:
A) I only
B) I and II
C) I and III
D) I, II, and III
You know you’re a web analytics geek when:
I) You run Google Analytics on multiple blogs, just to practice
II) You analyze the hell out of your Google Analytics data, even though your blog only gets 100 pageviews per day
III) Your wife goes out for the evening and you think, “Hmm…I could probably pass the Google Analytics Individual Qualification exam before she gets home”
The answer, sadly, is D. But I suspect you already knew that 🙂
On October 4th, Google announced that the Webmaster Tools/Google Analytics integration was now available to all users. The three new reports (Queries, Landing Pages, and Geographical Summary) are intended to allow site owners and content creators to monitor how well their content is indexed in Google for their keywords of interest across time, all within the Google Analytics interface. However, based on my preliminary research from the first few days of data, I have to question the current algorithm’s accuracy.