You need to create the factCustomerContact table. Which type of table should you create?

A fact table with a non-additive measure still contains a measure column (such as a ratio or balance) that cannot be summed across all dimensions, which is not applicable when no measure exists at all.

A factless fact table captures the many-to-many relationships between dimension keys to record that an event happened, such as a customer being contacted, without storing any numeric facts to aggregate. The factCustomerContact table only needs to record the association between a customer and a contact event, with no meaningful measure to sum or average. This design pattern is standard in dimensional modeling for event-tracking and coverage scenarios.

A periodic snapshot fact table records the state of a process at regular time intervals with cumulative or balance measures, which is not the purpose of a contact-tracking table.

A fact table with an additive measure contains numeric measures like quantities or amounts that can be summed across all dimensions, which requires measurable data that a contact event table does not have.