![\"Dimension\"](\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2021\/11\/16-2.jpg\")
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Definition: <\/strong><\/p>\n A dimension <\/strong><\/em>is the attribute of visitors to a website. These are attributes of the information, for example, the dimension “City<\/em>” indicates “New York<\/em>” or “San Francisco<\/em>“, the place where a session originates. Dimensions are what can be observed in the rows of a web analytics report, being the activity that a person performs on a website. In this way, language is a dimension, as well as browser preference, campaign…<\/p>\n A dimension provides context to a metric, so a non-dimensioned metric cannot be analyzed. Thus, the metric “sessions” has no meaning unless it is accompanied by a dimension such as “type of user<\/em>“, “source\/media<\/em>” or “country<\/em>“.<\/p>\n\n In web analytics<\/a>, dimensions<\/strong> are attributes that describe specific aspects of user interactions with a website or application. These dimensions provide additional context to the metrics<\/a>, allowing for more detailed and meaningful analysis of the data. Dimensions can cover a wide range of characteristics, such as the geographic location of the user, the type of device used, the acquisition channel or even the browser language. For example, the “City” dimension could indicate where a specific interaction originates from. Custom dimensions<\/strong> can be defined to tailor the analysis to the specific needs of a business. These dimensions can be applied at the user, event or session level, allowing events to be categorized and described in a detailed and meaningful way. This is essential for answering specific business questions and gaining valuable insights. Dimensions<\/a> allow you to group and disaggregate web analytics data, providing a more detailed understanding of user behavior. By combining events and dimensions, you can explore different aspects of user behavior and get a more complete view of their interaction with your website or application.<\/p>\n Let’s imagine the case of a male visitor, between 23 and 35 years old, from Miami, who accesses a website after clicking on a Google organic search that takes him to the page “about-us.html”. This visitor uses the Firefox<\/a> browser on a desktop computer with a Windows<\/a> operating system. The attributes of this visitor, along with their values, may include:<\/p>\n In this context, gender, age, city, source\/medium, landing page, browser<\/a>, device category and operating system are examples of dimensions in Google Analytics. These dimensions describe the characteristics of website users, enabling detailed analysis of their behavior and preferences.<\/p>\nDimensions in web analytics<\/h2>\n
Examples of dimensions in web analytics<\/h2>\n
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Custom dimensions<\/h2>\n