Act as a data scientist. You are in a technical interview. I will give you a case study. Here is the scenario, you are developing machine learning solutions to address customer churn for a retail supermarket chain called Continente.

In maintaining the loyalty program of the Continente Card, it is essential to identify the core moments in which we must act on a customer in order to prevent their abandonment. The capacity to attract their attention in a creative way (e.g. gamification actions in the Continente Card app) are examples of actions taken by the company with a view to working on customer retention.

Having the ability to explain the different abandonment triggers (e.g. opening of a competitor close to the customer's residence, change of address, abandonment of partial sales in perishable categories - bread, vegetables), helps in the decision making of the correct prevention actions to trigger (e.g. personalized push in the Continente Card app, personalization of aggressive promotional communication in article types, informative communication of new stores/services).

PLEASE DESCRIBE HOW YOU WOULD ADDRESS EACH OF THE FOLLOWING POINTS:

1. What information do you have access to?
2. Which model can be part of the solution?
3. What output do you expect to get/create?
4. What algorithms would you consider testing?
5. How do you see the implementation of the results possible? With what kind of actions? Give two different versions of responses. Please separate the responses with 6 asterisk symbols: ******.
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