Why doesn’t machine learning happen immediately after starting a Google App campaign?
- The system starts by learning from manual management.
- Other campaigns in the account need to be analyzed first.
- There’s a lot of data needing to be processed.
- Manual input is needed from Google employees.
Explanation:
Machine learning doesn’t happen immediately after starting a Google App campaign because there’s a lot of data that needs to be processed. Machine learning algorithms rely on vast amounts of data to understand user behavior, preferences, and the dynamics of the advertising landscape. Before the system can effectively optimize the campaign using machine learning, it needs to gather and analyze data from various sources, such as user interactions, ad performance metrics, and market trends. This process takes time as the system learns and adapts to the unique characteristics of the campaign and its target audience. Once sufficient data has been collected and analyzed, the machine learning algorithms can make informed decisions to optimize the campaign for better performance and outcomes. Therefore, the delay in machine learning initiation is primarily due to the extensive data processing requirements necessary for effective campaign optimization.
