The page depth metric or pages per session (also pages/session or average page depth) indicates the average number of pages visited by a user within a session. This metric is a standard option in Google Analytics that can be used to understand visitor behavior and optimize the site with the knowledge gained. If the pages per session are viewed in isolation, they only provide information about the number of pages per session. However, if this metric is combined with the predefined dimensions of Google Analytics, further analysis of the content, user behavior, and the website can be carried out in general, which goes far beyond the purely quantitative recording of page depth.
The average page depth can be viewed under the main menu item Target group> Overview. Other metrics are displayed there as well. If a specific time period is selected, the data for that time period will be shown. Additional metrics can be clicked and compared with one another at the top of the data view. The overview also shows new visitors and returning visitors as well as different aspects such as demographic features, languages, and system characteristics of the user device.
Google Analytics generally distinguishes between dimensions and metrics. These form the basis of the numerous reports. Dimensions are characteristics of data which is collected. That could be the city from which a page call has originated, for example. Metrics are quantitative data that can be tracked with Google Analytics. These include page views, sessions, and displayed pages per session.
Page depth is a value that indicates the average number of pages that have been visited in a session. It is indicated with a decimal number, such as 1.51 or 5.73 pages per session. Repeated page views are also recorded in the same session (loopbacks). For the sake of completeness, all current metrics are listed here:
To obtain meaningful reports, individual metrics are combined with different metrics or different dimensions, such as demographic features or the characteristics of the system that the user uses. Both primary dimensions and secondary dimensions are possible, although not all combinations are useful and available in all reports. For most data tables, the applicable options are located at the top edge so that they can be rapidly changed. . Another interesting feature is a comparison between different metrics, since in this way metrics such as page depth can be compared with the length of stay or the bounce rate.
Based on different metrics in general and with respect to page depth in particular, various conclusions can be drawn about optimization potential. For example, the average page depth indicates how much interest users have in the subpages of the website.
The answers to these questions can be interpreted as indicators for optimization. For example, low page depth values are an indication of an information architecture that does not draw users far enough into the offer. But having a lot of page views does not necessarily mean that the information architecture is good. The decisive factor is what the website is supposed to achieve and whether readers can find what they are looking for.
A high percentage of returning visitors indicates that remarketing or retargeting is useful (for example, through intelligent lists). That way, recurring visitors can be addressed directly to offer them incentives, for example, so that they can complete a purchase or order a newsletter. The Google Analytics reports can therefore also be used for initial decisions on lead generation or for evaluating landing pages. But in the case of landing pages and affiliate programs, however, the average page depth values should be low, since visitors are usually redirected.
Informative data is the basis for a reasonable web analysis. With its different dimensions and metrics, the Google Analytics tool allows numerous analytical methods that show their effectiveness once used in practice. Although Google offers a lot of help and explanations, the power of the features can only be realized when all relevant aspects are taken into account. For example, in order to draw sound conclusions from the average page depth, the nature of the website, its structure, and its business objectives must be clear. Only then will questions arise about the visitor behavior or the performance of a particular target group. For e-commerce websites, these aspects can be quite different from news magazines or blogs. In any case, it appears that average depth should not be viewed in isolation and should always be classified in an overall context because the questions which can be answered by GA are so diverse.