Adapt coupon usage based on conversion probability

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Overview

This example shows how predictive conversion probability segments can be used to differentiate coupon incentives across user groups.

Predictive segments are provided as part of the AI Assistant add-on and can be used in Mapp Engage.

All coupon logic and incentive levels are defined explicitly in the campaign setup.


Example setup

AI-based predictive segments are created in Mapp Intelligence and can be used in Mapp Engage.

In this example, three segments are used:

  • a segment with a high conversion probability

  • a segment with a medium conversion probability

  • a segment with a low conversion probability

These segments represent different likelihood levels and do not apply any incentive logic by themselves.

Lower discounts are applied to users with high conversion probability, while higher incentives are reserved for users with lower probability.

This example illustrates one possible approach. Actual logic depends on your campaign strategy.

  1. Create predictive segments

    Predictive segments are available in the segmentation builder under Intelligence > CI Segments.

    Select the conversion probability segment.

    In this example, three segments are created to represent high, medium, and low conversion probability.

  2. Review segment size

    Check how many contacts belong to each segment.

    You can review this in the Number of Contacts column.

    This helps you assess whether the segment distribution is suitable for differentiated incentives.

  3. Use segments in campaign orchestration

    Use the predictive segments in a whiteboard or campaign setup to control which incentive logic is applied to each group.

    For example, higher discounts can be reserved for users with a lower predicted conversion probability.


Notes

  • Predictive segments classify users by probability, not by guaranteed behavior.

  • The system does not automatically optimize or adjust coupon values.

  • All incentive decisions remain under user control.