Dynatrace can typically show all the sessions of each individual user, even when those sessions are anonymous or when a user tag has changed or gone missing. For mobile apps, Dynatrace stores a user identifier within the application scope, so the same user can be identified on the same device. For web applications, this is achieved by storing a persistent cookie within each user’s browser that enables Dynatrace to assign even anonymous user sessions to identified users. As long as a user has signed in to your application at least once, you can search for and identify that user, even if the user accesses your application via anonymous sessions. This is helpful in situations where a user can’t sign in due to an issue with an authentication service.
Focus on the sessions of a single user
The top of each User overview page includes an infographic that features clickable tiles that convey basic details of the user, including device type, accessed applications, and location data. Click any tile in the infographic to display further details beneath the infographic.
The User sessions page (available by selecting User sessions from the navigation menu) includes a list of all users (both authenticated and anonymous users) who have initiated user sessions in your environment. Click a user name to go to that user's overview page. Here you'll find a list of all the sessions of this particular user (see example below), the devices this user has used to access your applications, which applications the user accessed, and location-specific data.
Note: You can alternatively access a specific user's overview page by clicking in the text field at the top of the user sessions page. Select the User tag attribute and then the tag of the user you want to analyze.
You can further refine your analysis of the sessions of an individual user by using filter attributes. Filter attributes can be selected from the Analyze user sessions based on... drop lists. While the Start time and Duration columns appear in the user sessions list by default, you can use filter attributes to add additional columns to this view. For full details on available filter attributes, see How do I analyze user sessions?
Click any session in the list to view the details of that session, including all user actions and events displayed on a timeline. Here you'll find session detail including Operating system, device Manufacturer, User tag, IP address, and more.
The X-axis of the User actions and events chart shows when the actions occurred during the session as well as the wait time between each action. The Y-axis indicates the user action type (for example,
XHR action or
Load action) or event type (for example,
User tag event, or
Mobile event). Click on a specific action to view the details of that action (see example below). When multiple actions/events take place nearly simultaneously, the clustered actions are consolidated into a single point in the timeline that shows the number of actions that occurred at that point in time.
Following are examples of session analysis for a single user.
Before you can search for a specific user, you must assign user tags to all your users. For details on this, see How do I tag individual users for session analysis? Following this step you can filter users based on user tags, as shown in the example below.
The User sessions page then only displays the sessions of this particular user. The example below shows that this user accessed two applications (
easyTravel Customer Frontend and
Click on the user name to return to this user's overview page, where you can examine further details regarding the sessions of the specific user.
Understand user behavior
To understand how user behavior analysis relates to customer satisfaction, it’s helpful to look at session duration and the distribution of user actions within the session. Was there a lot of “think” or “read” time between actions? Because each point detailed in the user session timeline chart (see image below) is a user action, at a glance you can see bounced sessions and user sessions that included numerous actions. Note in the example below that there is one session that lasted over 9 minutes and another session that included an anonymous bounce.
The User action count attribute can be selected from the Analyze user sessions based on... drop lists to identify those sessions that have a high number of actions.