For a web analytics analyst or a data-driven marketer, these are words to live by: “Without data, you’re just another person with an opinion.”
Optimization isn’t about educated guesses and hunches, no matter how many years you’ve been in the industry. It’s about doing the research, asking the right questions, digging for clues in problem areas, paying attention to the signs when they appear, and running smart A/B tests.
Web analytics analysis is a big part of that. It helps separate the optimizers from just another person with an opinion.
Peter Drucker famously said, “What gets measured gets managed.” But what if your data is wrong? 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?
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. That’s why you need to conduct a Google Analytics audit.
Where should you start with your mobile app analytics?
If you’re launching a mobile app, you’ve likely considered the differences between optimizing a simple site and a mobile app or game. But have you considered how the measurement and data analysis process will be different?
Without a definitive plan and deep understanding of the fundamentals, your mobile app data will get complicated quickly. There are new tools, new terminology, new reports, new rules for efficiency, and so on.
Would you rather optimize the path your visitor will actually take or optimize the path you think he should take?
If you’d rather the former, then there’s something you need to know about linear funnels… they’re not a completely accurate representation of reality. The question is, what should you do about it and what is an accurate representation of reality?
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.
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.