This article helps you to understand how accesses from different time zones are tracked in Mapp Intelligence and how they can be analyzed.

All data collected in Mapp Intelligence shows server time, i.e., the point of time when Mapp received the data. Regarding the tracking servers, Mapp Intelligence uses UTC time. In the system configuration, the time zone can be adapted. This setting is used for the timestamp which is saved in the database for the corresponding incoming data. Therefore, this setting does not only affect analyses, but also the underlying raw data.

In general, you should choose the timezone which the majority of the users of the account is also using.

A possible clock change (e.g., from summer time to winter time) is done automatically by Mapp.

Example:

Your website is located in Germany. In the system configuration, choose "Europe/Berlin".


User A is located in Berlin and accesses your website at 10:00 am (local time).

The track server records 9:00 am (UTC). According to the settings in the system configuration, the time is converted to 10:00 am and saved in the database.


User B is located in London and accesses your website at 9:00 am (local time).

The track server records 9:00 am (UTC). According to the settings in the system configuration, the time is converted to 10:00 am and saved in the database.

How can I find out how many users are accessing my website from different time zones?

Especially for marketing campaigns, the local access time of the user (client-side) can be important. It helps to understand which campaigns are used at which time.

For a detailed analysis of the client-side time, there are two options:

  1. Creating a custom figure and filtering on the dimension "Country"

    The advantage is that no further data has to be collected.
    The disadvantage is that creating such a figure can be quite complex (it depends on how many countries belong to the corresponding time zone) and partly imprecise (as some countries stretch across more than one time zone).

    Open the "Country" analysis and look for the countries that belong to the chosen time zone.
    Afterward, create a custom metric. Within this metric, use "visits" as an underlying metric and filter on the corresponding countries.

    Example:

    You also could create a custom formula that shows the share of visits from this time zone on all visits.

    A corresponding analysis could look as follows:

    Especially during holiday season, there may be larger deviations to the annual average because of increased accesses from foreign countries.
     
  2. Passing the timezone via a custom parameter

    Advantage: Very precise, easy to create
    Disadvantage: Data collection has to be adapted

    Pass the timezone via a session parameter to Mapp. For this purpose, read out the deviation to the timezone via Javascript (e.g., "-1", if the deviation is minus one hour).

    We recommend setting a value for the parameter only if there actually is a deviation.
    Open the analysis of the corresponding session parameter to see the values.

    Example: