New and old users of the site has become a site analysis for a class of user segmentation methods, site analysis is an important component of the user analysis. Google Analytics on the naming of the new and old customers for the New Visitors and Returning Visitors, but also for many analysis indicators based on the breakdown of the old and new users.

Simply put, new user is the user's first visit to the site or the first use of the website services; old users previously visited the web site or use the web service user. Both old and new users can bring value for the site, this is also the analysis of the meaning.

Analysis of the significance of new and old users

The site of the old users are generally the loyal users of the site, a relatively high viscosity, but also bring value to the main user groups for the site; new users means that the website business development site the rising value of the premise. It can be said that the old user site survival, a new user is the power of the web site development, website development strategy is often based on the basis of the retention of the old users continue to improve the number of new users.

Therefore, to analyze the significance of old and new users is: through the analysis of the old user to determine whether the basis of the site is secure, the existence of the crisis be eliminated; through the analysis of new users, to measure the development of the site is smooth, whether there is greater room for expansion . A focus now, a look to the future.

The identification of new and old users

Previously written an article for the identification of the site users - user identification , which is mainly based on click-stream logs on the basis of the four categories of identifying users, can be used as reference. But for the identification of new and old users may have different definitions of the site itself specific.

The most common form of identification is to see whether the user had previously visited site, that is, whether the user's first visit to to distinguish between the old and new user-friendly way, GA is the use of cookies to define the new and old customers, that is, before the Cookie is the visitor for the old user, or for new users. This definition applies to all sites, but it is not accurate, cookie deletion of the user to replace the PC and so on will cause the deviation of the data.

Another to identify ways relatively accurate, but generally only applicable to the registration login site, that is, the logged on user definition of first registration for new users, once again logged on user for the old users, rather than using the first visit to identify. This distinction is generally to identify the user ID or user name, is relatively accurate, but limited the scope of application.

Analysis of new and old customers

The site's goal is to keep old customers, expand into new user, and site performance data analysis is to maintain the steady growth of the old and the number of users under the premise, to enhance the proportion of new users.

For most of the development site, the site of the old users should be relatively stable, and there will be continued to rise slightly, you can look at the GA on my blog weekly changes in the trend of the old and the number of users:

Returning Visitors can be selected by the GA Dashboard Advanced Segments, and select the appropriate time interval and summary of granularity (day, week, month) shows the trend curve. Smooth rising curve of development of the site is to become normal.

Old user trends but not all sites will be so smooth, such as travel sites, tourism will be significantly influenced by seasonal effects show relatively large fluctuations, so here is to introduce the concept of the year and the chain were analyzed.

The year-on-year is in order to eliminate the effects of seasonal changes, the current data with the data of the same period last year, for example, in February of this year's data, in February last year, the comparison of data;

Chain refers to the issue data were compared with the previous data can be annular, on a monthly, weekly chain, for example, in February this year and January this year data.

Year on year and a large number than was used in the trend analysis based on time series for the site visits, sales, profits and other sites of key indicators can also reference year and the chain were analyzed for the analysis of the trends of these indicators, to eliminate the impact of the seasons are a positive effect. Here is an old user data based on the tourist sites of the year and the chain simulation trend analysis chart:

Can be seen from the chart due to seasonal factors, the volatility of the old and the number of users is relatively large, the corresponding ring growth fluctuations, but year-on-year growth trend has been relatively smooth, has remained at around 10% growth rate above This can be seen that the site is effective to keep the old user, the operational status of the site is more stable.

Some may ask, why use the absolute number, rather than the relative number, such as the proportion of old user total access to the user to conduct trend analysis? Main consideration here to the site will occasionally take the initiative to promote the marketing, or passive promotion effects arising as a result of the impact of certain events or media, this time may attract a large number of new users into the site and the proportion of old user a sharp decline in the absolute data of the old users are relatively stable in terms of the site more useful.

The absolute number of new users and old users so stable, will not necessarily maintain the growth trend, and for the analysis of the new user in order to measure the effect of site promotion, assess the impact of the active marketing or passive event, it is not recommend the use of absolute values, since the old user is relatively stable, it can be to analyze the site of a certain period of time and the effects of trends based on the proportion of new users. New Visits the proportion of other websites baseline trend in the GA's Benchmarking comparison:

Often a substantial rise or fall of the curve to a point in time means that the impact of a marketing event, when the curve continued to decline, it means that the adverse effects of website promotion, you need to increase marketing efforts.

If you have a better insight on the site of new and old users are welcome to comment.

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