In your Poool Access tool, you can enable Poool's native segmentation. Thanks to this, we are able to offer you both interesting engagement segments as well as provide key insights to help you define your strategy.
💡 Activating Poool's native segments requires the integration of the Audit.js script. You can find more information on this in our technical documentation.
Engagement groups available
In the Scenario section, when you select the "Use Engagement Groups" option, four groups are natively available in Poool:
Volatile
Regular
Occasional
Fans
For each of these segments, you can configure a dedicated scenario. In other words, you can tailor the user journey, appearance, and/or the message addressed to your readers according to the group they belong to.
User Segmentation in Native Groups
The segmentation works based on several factors:
The quality of the tracking implemented during integration
The duration of the journeys defined in the tool
Whether journeys are present or not
During integration, it’s recommended to tag all pages of the site to gain a comprehensive view of users and thus obtain a relevant engagement rate. The quality of this integration ensures the accuracy of the collected information.
💡When setting up a journey for the first time in a segment, we use the users’ historical data since the beginning of the tagging process to assign them to the appropriate segment.
Calculation Based on Journey Duration
Beyond the initial distribution, segment population is based on journey duration. The journey duration influences the score calculation retrospectively.
For example, if I set a journey duration of 30 days, the user will be re-assigned once this period has elapsed. Throughout the 30 days, the user remains in their current segment.
Their new engagement score will be calculated based on the defined journey period—in this example, 30 days.
Visit History
There are two types of users entering a segment for the first time:
"New" users whom Poool has never seen and who have no existing cookies
Users who visited during a period with no active journeys, thus having a cookie but not a segment
In the first case, the user will be assigned to the volatile segment due to a lack of browsing history. In the second case, we will use their browsing history to place them in the appropriate segment.
Calculation Method
We use two different methods to segment visitors into these engagement groups:
The RFM method (Recency, Frequency, and Monetary Value, where "Monetary Value" is replaced here by the number of pages visited per session)
The F method (based solely on Frequency)
To choose the method to use, go to your Dashboard, under Settings > Advanced Configuration.
RFM: This mode is based on a well-known marketing method used to analyze customer value. Once recency (based on the date of the last visit), frequency (the average number of sessions per day over the last xx days), and monetary value (the average number of pages viewed per session over the same period) are calculated and combined through a complex analytical program, we obtain an engagement score ranging from 0 to 100, allowing us to segment visitors into groups.
In your Dashboard, you can set the period for calculating this score. However, you cannot modify the definition of the engagement groups: they change over time and adjust themselves dynamically.
Frequency: This mode relies solely on the frequency parameter from the RFM method. This requires setting thresholds in your Dashboard to define the native groups by answering a simple question: How many sessions does a volatile/occasional/regular/fan visitor have within xx days?
Do not hesitate to check our guide about this topic.
We are available if you have any further questions!