You can learn more about how metrics are handled by visiting the Metrics page.
All features on DMP have their own metrics tab, containing data about aspects related to each one, including performance and processing data.
The Cookie Pools Metrics tab contains data about how your website's users interact with it. To learn more about each metric related to this feature, go to the Cookie Pools Metrics article.
The Trackers Metrics tab contains data about your websites' tracked activity. To learn more about each metric related to this feature, go to the Trackers Metrics article.
You can learn more about how metrics are handled by visiting the Metrics page.
Select a cookie pool from the list to access its metrics. It is also possible to select more than one to compare their results.
This metric displays how many cookies have expired within the configured time frame. Cookies expire based on the TTL, which is the number of days after which a cookie will expire, configured when creating the cookie pool.
Example: You create a cookie pool with a TTL of seven days and install it on your homepage. The cookies generated by your users' access will be available for targeting for seven days. After this period, the cookies will expire. This means that in a retargeting campaign, for example, you will impact users who visited your website in the last seven days. In this graph, you can observe that on June 19th, just under 5 cookies expired, on June 20th no cookies expired, and on June 21st just under 5 cookies expired, and so on.
This metric shows the maximum amount of cookies allowed in the pool as configured.
Example: When creating or editing a cookie pool, you can set the maximum amount of cookies in the pool. This will limit the total number of cookies your pool can contain. In this graph, you can observe that a maximum size of 100,000 cookies was defined for this cookie pool.
This metric shows the actual size of the pool, meaning it will show how many cookies are or were in the pool within the configured time frame.
Example: On this graph, you can observe the size of a cookie pool in the defined time frame. This metric can be used for gathering knowledge about how many cookies are generated within the configured time frame, which will allow you to set a maximum size for the pool that is in the same range as the number of users on your website.
This metric shows the number of cookie synchronizations, meaning it shows when a collected cookie has been synchronized with our platform and later with the exchanges as well, which allows you to target users more precisely.
Example: On this graph, you can observe the number of synchronizations that happened in a defined time frame. When a user accesses your website, a cookie will be requested for him, after receiving this cookie, it will be analyzed if this user already has a cookie or not, if he does the new cookie will be synchronized with the already existing one, updating its data on the platform, if he doesn't a cookie will be created for him on the platform.
This metric shows the median remaining time a cookie is still available in the pool until expiring in the determined time frame.
Example: When you create your cookie pool you can set the number of days in which a cookie will expire, this metric shows you how much time you have until a cookie expiration. On this graph, the time frame was 1 week, divided into daily periods, represented as dots, you can observe that on June 20th there was less than 1 day until some of the cookies in the pool expired.
These are all the metrics available in the Cookie Pool feature for analyzing the performance of your cookie pools. Additionally, when checking metrics, you can always check our to access for more information about a specific metric.
You can learn more about how metrics are handled by visiting the Metrics page.
To access the metrics tab select the trackers which you want to visualize data on the trackers' list:
You can select more than one tracker. However, the 'Group by' option is only available when selecting a single tracker. When selecting multiple trackers, the data will be grouped by tracker and this option will not be displayed.
When grouping by tracker all the data collected by the selected tracker will be displayed on these metric cards or in the data table columns:
This metric shows how many actions were executed by your tracker in the configured time frame.
Example: On this graph, you can observe an increase in the number of actions at 6 AM. The graph displays a time frame of 3 hours divided into 5-minute intervals represented as data points. After creating a tracker, you will need to set up events and actions. Each time a tracked event occurs, the configured actions associated with that event will also be executed. For instance, an 'add to cart' event might trigger an action to track the added product in the catalog. This metric indicates when and how often the action is executed within that time frame.
This metric shows when an event has been tracked, however, the action linked to it has failed.
Example: When a user adds a product to their cart on your website and this event is configured to be tracked, with an action to track it in the catalog, the event itself is tracked successfully. However, the action to update the catalog failed, resulting in the product not being tracked. In the graph, you can observe that the action failure rate is typically 0%. However, there are moments where the action failure rate peaks near 40%. The graph covers a time frame of 3 hours, divided into 5-minute intervals represented as data points.
This metric shows the amount of users' expirations that occurred in the defined time frame.
Example: When configuring a tracker, you can set a tracking period after which the user will expire. This metric shows the number of expirations that occurred. On this graph, you can observe that between 4 AM and 5 AM, nearly 50 tracked users expired.
This metric shows the configured maximum number of users to be added to the tracker.
Example: When creating or editing a tracker, you will set the maximum number of users allowed to be added to your tracker. This metric displays that data. In this graph, you can observe that the tracker was configured to accept up to 1 million users
Whenever a user performs a new tracked activity on your website, this will be tracked, this metric will show the number of new activities tracked in a defined time frame.
Example: You have an 'add to cart' event configured on your tracker. Whenever a user adds a product to the cart, it counts as a new activity. On this graph, you will notice that the number of new activities increases after 6 AM. You will also observe that this graph covers a time frame of 3 hours, divided into 5-minute intervals represented as data points.
This metric shows the remaining time a cookie is still available in the pool until expiring in the determined time frame.
Example: When you create your cookie pool you can set the number of days in which a cookie will expire, this metric shows you how much time you have until a cookie expiration. On this graph, the time frame was of 1 week, divided into daily periods, represented as dots, you can observe that on June 20th there was less than 1 day until some of the cookies in the pool expire.
This metric will show how many users were in the tracker in the defined time frame.
Example: After setting up a tracker on your website, your website's users will begin to be tracked. The number of users tracked within a defined time frame is the data shown in this metric. On this graph, you will notice that the number of tracked users between 4 AM and 6 AM was nearly 400 thousand.
When grouping by event, the displayed metrics will be separated according to their respective events. The following metric cards or data table columns are available:
This metric shows the number of actions executed by each tracked event within the configured time frame.
Example: You have a 'product view' event configured on your tracker, linked to a 'track in catalog' action. Every time a product is viewed, the event is tracked, and the associated action is executed. This metric shows this data grouped by event. On this graph, you can observe an increase in actions around 6 AM. The graph covers a time frame of 3 hours, divided into 5-minute intervals represented as data points.
This metric shows instances where an event was tracked but the linked action failed to execute. The data is displayed grouped by event.
Example: When a user on your website adds a product to the cart and this event is configured to be tracked, with an action to track it in the catalog, the event is successfully tracked. However, the action fails to execute, resulting in the product not being tracked in the catalog. On this graph, you can see that the action failure rate is typically 0%, but there are moments where it reaches nearly 40%. The graph covers a time frame of 3 hours, divided into 5-minute intervals represented as data points.
Whenever a user performs a new tracked activity on your website, it will be recorded. This metric shows the number of new activities tracked within a defined time frame, grouped by event.
Example: You have 'add to cart' and 'product view' events configured on your tracker. Every time a user performs any of these tracked activities, it will be counted and displayed in this metric, grouped by event. On this graph, you will notice that the number of new activities increases after 6 AM. The graph covers a time frame of 3 hours, divided into 5-minute intervals represented as data points.
These are all the metrics available in the DMP product for analyzing the performance of your cookie pools and trackers. Additionally, when checking metrics, you can always check our to access for more information about a specific metric.
