Save Your Ass With Google Analytics Data Alerts. Let’s face it, we’re all a bit “lazy.” I admit it, I don’t check my website data every day. And when I’m on vacation it can be a bigger challenge. But that’s OK, I use data alerts to stay on top of my data even if I can’t check analytics every day. Are you using alerts? If you’ve never used Google Analytics alerts they’re fairly simple to set up. There are five things that you need to do to set up an alert: 1. I divide my alerts into two groups: those that insure I have good data and those that measure the performance of the business. Alert #1: 10% Daily Traffic Drop This first alert is simply there to make sure that I’m collecting data. A 10% traffic drop alert. Alert #2: Flatline! This is a generic alert that identifies when a metric goes to zero. But I don’t want to wait until the end of the month to find a problem. So for almost every important metric I will create a daily alert to insure that I’m getting data.
A Google Analytics Alert that monitors an Event Alert #3: Daily Error Pages. Analytics. Tracking Google +1 button Interaction in Google Analytics. 11 Pipers Piping: An Introduction to Regular Expressions and Pipes. Well, we’re up to the 11th day of Christmas – the ole ‘11 Pipers Piping’. So, no better time than now to talk about the pipe when used as a Regular Expression and how to use it to your Google Analytics advantage. What are Regular Expressions? Regular Expressions are text patterns that can contain combinations of alphanumeric and special characters. If you’ve ever had the need to use Wildcards, you’ll recognize the similarity. The text pattern that you create with Regular Expressions (RegEx) is used to match and describe characters and words — think of it as more powerful filtering. Using RegEx in Google Analytics can help merge tech with marketing, taking your data beyond the standard goals and filters available to you in Analytics.
Although we’re only talking about the pipe today, know that there are 11 other RegEx symbols that can be used in conjunction with each other in a multitude of combinations to extract really meaningful data. An Example Have you been naughty | nice. Metrics Definitions - Analytics Help. Understand the building blocks of your reports. Overview Every report in Analytics is made up of dimensions and metrics. Dimensions are attributes of your data. For example, the dimension City indicates the city, for example, "Paris" or "New York", from which a session originates. The dimension Page indicates the URL of a page that is viewed.
Metrics are quantitative measurements. The tables in most Analytics reports organize dimension values into rows, and metrics into columns. In most Analytics reports, you can change the dimension and/or add a secondary dimension. Valid dimension-metric combinations Not every metric can be combined with every dimension. For a list of the valid dimension-metric pairs, use the Dimensions and Metrics Reference.
How metrics are calculated In Analytics, user metrics are calculated in two basic ways: As overview totals where the metric is displayed as a summary statistic for your entire site, such as bounce rate or total pageviews. Attribution models. 10 New Google Analytics Features You Need to Start Using. Rachael Gerson spearheads the Analytics division at SEER Interactive. Follow her on Twitter @rachaelgerson. Over the past eight months, Google has steadily released one revolutionary new feature after another.
On March 17, the company announced a new version of Google Analytics. Up until this point, users could decide whether they preferred to stick with the old interface or switch to the new one. However, Google recently announced that the old version of GA will be turned off in January 2012. If you're not already familiar with the new version, take the next few weeks to get comfortable with it. 1. Dashboards got a much needed overhaul in the new GA. At a minimum, these four widgets would benefit the average user. Visits - Timeline (can also include Metric)Goal Completions and/or Transactions - TimelineSource/Medium - TableBounce Rate - Timeline 2.
Rather than viewing a long list of keywords to spot trends, users can now evaluate a keyword cloud. 3. 4. Why is this important? 5. 6. 7. 8.