Learning Phase

The learning phase in digital marketing refers to the period when an ad platform’s algorithm analyzes and learns about an ad set and its target audience. During this crucial phase, the algorithm experiments with various audiences, placements, and creatives to identify the most effective delivery strategies for achieving campaign objectives. Consequently, ad performance is often sub-optimal during the learning phase as the system refines its approach for optimal results.

Example:

A Facebook conversion objective campaign with three ad sets targeting different audience segments undergoes an initial Learning Phase once the campaign is launched. During this phase, the campaign’s performance is optimized as the Facebook algorithm gathers data and tests various strategies. On Meta platforms, to exit the Learning Phase and improve performance, a campaign must achieve 50 events, dependent on the specific conversion objective, within 7 days. This data helps the algorithm refine targeting and scale up the campaign’s effectiveness.