A/B testing tools like Optimizely or VWO make testing easy, and that’s about it. They’re tools to run tests, and not exactly designed for post-test analysis. Most testing tools have gotten better at it over the years, but still lack what you can do with Google Analytics – which is like everything. Keep reading »
Google might be the holy grail of analytics, and there’s little question that you need it plugged in if you want to track your website’s success. But that doesn’t mean Google Analytics is telling you the full story.
In fact, your analytics could be telling you outright lies.
“Statistics are like bikinis. What they reveal is suggestive, but what they conceal is vital,” said Aaron Levenstein, a former professor of business administration at Baruch College. [Tweet It!]
The same is true of your data in Google Analytics. Most of what you spend your time looking at (and re-looking at) is merely suggestive.
As an optimizer, it’s your responsibility to understand the implementation and analysis of digital analytics. Gone are the days of relying on the IT department to help you with basic analytics tracking. [Tweet It!] Fortunately, Google Tag Manager makes it easy.
Still, many optimizers don’t use Google Tag Manager (or any tag manager, for that matter) because it looks daunting. The truth is that once you understand the basics, it essentially becomes a second language.
Peter Drucker famously said, “What gets measured gets managed.” But what if your measurement data is incorrect? What if you’re not measuring correctly or completely? What if there’s a whole pile of things you think you’re measuring when really… you’re not?
The fact is that a lot of the people relying on Google Analytics are relying on bad data. No, not because Google Analytics is awful. Because their configurations are broken.
When you hear “data segmentation”, your instinct might be to bury your head in the sand or fall asleep. Why? Well, segmentation can seem daunting (or boring) to those unfamiliar with it.
It’s an unfortunate truth because segmentation is perhaps one of the most effective tools at our disposal. The ability to slice and dice your Google Analytics data is the difference between mediocre, surface-level insights and meaningful, useful analysis.
The success of an online business is measured by various indicators.
The data required comes mostly from web analytics tools – the most popular being Google Analytics. But what if the tool isn’t reporting what people expect it to report? What if you can’t trust all of the metrics in GA?
Knowing where to segment your Google Analytics data can be daunting. Where do you start? And how the Hell are you supposed to know if what you’re looking at is going to make any difference what-so-ever?
As more and more business owners are learning about the benefits of the new version of Google Analytics (referred to as “Universal Analytics”) as well as the utility of Tag Management Systems (made even more popular by the release of the free Google Tag Manager), Peep reached out to me to write an article about moving an inline GA implementation to Google Tag Manager. This is work we do often over at Analytics Ninja, so I feel more than happy to provide this guide for ConversionXL’s readers. Keep reading »