Using a lifecycle grid analysis, you can create states across the customer lifecycle and use the behavior or recommendation scores to trigger communication. A rule library for each state or segment type will allow the machine to trigger communications if a particular rule is satisfied.
After the communication is triggered, the system needs to loop back the responses of the customer with respect to the communication and store data against the pre-existing tag. This ensures that the new responses are added to the existing insights and the new derivative is rendered for next action. Storing against the tag will help maintain single customer data at all times.