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Robbin Steif

j Ust a story about Regular People and Regular Expressions . . . Google Analytics is one of the most widely used tools to measure and evaluate websites. The GA team has worked hard to make it easier and more intuitive than ever before. However, you may still feel that you are limited by the Google Analytics out-of-the box functionality. If so, it’s time for you to learn about Regular Expressions and how GA uses them.
When I first starting working with Google Analytics, I was an analyst. A marketing person. Not a techie. Back then, the Google Analytics documentation kept referencing something called Regular Expressions. I could see that my goals and filters weren’t doing what they needed to do, but, not being a techie, I didn’t know how to implement RegEx and fix them. (In fact, I knew so little about this space that when a friend referred to Regular Expressions as “RegEx,” I wondered what he was talking about.) Slowly I taught them to myself, with the help of Wikipedia and a friend in Australia. Then I began to blog about them, using non-techie language. I got a letter from a trainer on the other side of the pond who told me that when he trained people in Regular Expressions, he turned them loose on the LunaMetrics blog. Eventually, Google invited my company to become a Google Analytics Certified Partner. Our company helped rewrite the Google Analytics Help Center section on Regular Expressions. And to this day, I get random emails from random people, asking me to troubleshoot their RegEx.

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In Google Analytics, you can use Regular Expressions to ...

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A word about language.
What would a how-to guide be without some dictionary-type advice? Here are some of the conventions we may use: GA: The abbreviation for Google Analytics RegEx: the abbreviation for Regular Expressions (singular and plural) Plain text: Not Regular Expression Text String: any assembly