What is the difference between dimensions and metrics in Google Analytics?
The dimension Page indicates the URL of a page that is viewed. Metrics are quantitative measurements. The metric Sessions is the total number of sessions. … The tables in most Analytics reports organize dimension values into rows, and metrics into columns.
What are dimensions and metrics and analytics?
It is a Count (a total or a sum), an average, or a Ratio (one number divided by another number). Metrics are measurable. Dimension is an attribute of a visitor to your website – where they came from, their location, how many pages they viewed, etc.
What are Google Analytics metrics?
Metrics in Analytics can be sums or ratios. Metrics are individual elements of a dimension that can be measured as a sum or a ratio. For example, the dimension City can be associated with a metric like Population, which would have a sum value of all the residents of the specific city.
What is a dimension in Google Analytics answer?
A descriptive attribute or characteristic of data. Browser, Landing Page and Campaign are all examples of default dimensions in Analytics. A dimension is a descriptive attribute or characteristic of an object that can be given different values. Use them to help organize, segment, and analyze your data. …
What Cannot be collected by the default Analytics tracking code?
What cannot be collected by the default Analytics tracking code? Correct answer is: User’s favorite website.
What are metrics and dimensions?
Throughout most reports, metrics are the quantitative measurements of data and dimensions are the labels used to describe them—or, in even easier terms: metrics are always expressed by numbers (number values, %, $, time), while dimensions are expressed by non-numerical values.
What are metrics?
Metrics are measures of quantitative assessment commonly used for comparing, and tracking performance or production. Metrics can be used in a variety of scenarios. Metrics are heavily relied on in the financial analysis of companies by both internal managers and external stakeholders.
How do you identify dimensions?
Measure any two sides (length, width or height) of an object or surface in order to get a two-dimensional measurement. For example, a rectangle that has a width of 3 feet and height of 4 feet is a two-dimensional measurement. The dimensions of the rectangle would then be stated as 3 ft. (width) x 4 ft.
What are custom dimensions in Google Analytics?
Include non-standard data in your reports. Custom dimensions and custom metrics are like default dimensions and metrics in your Analytics account, except you create them yourself. You can use them to collect and analyze data that Analytics doesn’t automatically track.
What can Google Analytics measure?
Google Analytics is one of the most popular digital analytics software. It is Google’s free web analytics service that allows you to analyze in-depth detail about the visitors on your website. It provides valuable insights that can help you to shape the success strategy of your business.
What is an example of metrics Google Analytics?
Some examples of metrics in Google Analytics include number of visits, pages per visit, conversion rate, bounce rate, etc. All reports in Google Analytics maintain default dimensions and metrics.
Does Google Analytics show unique visitors?
Google Analytics does not report on unique users anymore. According to Google’s own definition: The ‘users’ metric includes both new and returning users. So if ‘users’ metric includes both new and returning users, then certainly the number of users can’t be equal to the number of unique users (or unique visitors).
How do I find custom dimensions in Google Analytics?
First you’ll need to log in to your Google Analytics account, and select the website you’d like to find your Custom Dimension reports in. Then, click the Customization / Customisation tab in the left panel.
Can you add a third dimension in Google Analytics?
However, Google Analytics online interface allows you to use a third dimension. In fact, it allows you to use even more dimensions. … Every dimension results in a greater level of segmentation of data and it may influence the amount of data for every category.